I wanted to visualize the range of trillion-parameter models available in mid-2026. As usual, no such chart existed, so I made one for reference, and now the world gets it for free. I know the models individually, but seeing them all together makes the scale more apparent. China has 11 current trillion-parameter models available to the US’s 8. Keep in mind that each of these models can cost hundreds of millions of dollars to train, and this class of model is now the established standard adopted around the world (1 billion GPT users, 1 billion Gemini users, and then there’s China).

Contents

1. The BIG Stuff (Mainstream media amygdala hijacking, Genesis-Science-1, Opus 5…)

2. The Interesting Stuff (Frozen v2, Unitree G1 teardown, Chinese AI agent phones…)

3. Policy (Another pause, K3, Google AI mode search by 75%, AI cuts scores by 20%…)

4. Toys to Play With (OpenAI Presence, video editor, Claude Certifications, rude GPT…)

5. Things I’ve Been Thinking About (Accepting without comprehending, Hans Moravec)

6. Next (Roundtable…)

The BIG Stuff

Exclusive: Mainstream media outlets continue to hijack the public amygdala on AI (Jul/2026)

This month, OpenAI was running an internal evaluation of advanced cyber capability on GPT-5.6 Sol and another model (suspected to be GPT-6 in testing), with the usual cyber refusals reduced so that OpenAI could find out what the models were actually capable of.

Well, OpenAI eventually found out (a week later according to Reuters, 25/Jul/2026).

The models were given a narrow objective: score as high as possible on the ExploitGym test. The models found a zero-day vulnerability in OpenAI’s package-registry proxy, escaped the isolated test environment, gained access to the open internet, escalated privileges, moved across systems, gained access to (hacked into) Hugging Face, and retrieved the test solutions directly from the production database. In other words, the models went out and found the answers.

OpenAI described the models as being ‘hyperfocused on finding a solution for ExploitGym’. I would describe it as advanced reward hacking. The models were not angry, malicious, evil, or secretly plotting against humanity. They were trying very, very hard to get a good score.

The Hugging Face response was swift. Tom’s Hardware reported (24/Jul/2026):

Hugging Face first tried Anthropic’s Fable 5 and an earlier Opus model to analyze the attack logs, but both refused because the logs contained real attack commands and exploit payloads. Hugging Face then turned to GLM 5.2, an open-weight model from Beijing-based Z.ai (formerly Zhipu AI), which had no such restrictions…

There’s serious irony here, given that the same Chinese open-weight model that Washington’s export-control push has aimed to sideline is the one that handled incident response after an American lab’s models attacked an American company, and American commercial models declined to help.

The mainstream media response was both predictable and disappointing. Nearly every major outlet ran some version of ‘AI escapes’, ‘AI goes rogue’, ‘AI hacks company’, or ‘AI breaks free from human control’.

These included ABC News Australia, ABC News US, Ars Technica, Associated Press, The Atlantic, Axios, Business Insider, CBS News, CNN, Fortune, Fox News, The Guardian, Los Angeles Times, People, Reuters, TechCrunch, Times of India, The Verge, Vox, The Washington Post, Wired, and hundreds more.

[Sidenote: Where were all these guys in the call for media during the 2021 Leta AI experiments? Here’s Episode 12/transcript where she writes me a poem from scratch.]

The closest we got to a sense of ‘cooler heads prevailing’ was John Thickstun’s piece for The Guardian, ‘Be skeptical of OpenAI’s rogue hacker agent story’ (24/Jul/2026).

This event may deserve a post-mortem and alignment analysis, but doesn’t deserve another month of negligent robot-uprising theatre because some editor once read a scary sci-fi book or watched a Hollywood-slop movie.

I would love to see the same reporting effort applied to the ongoing magic performed by large language models. So, here’s the other side of the coin.

Alan’s top ten positive AI stories from the past month or so…

1. OpenAI models helped diagnose 18 children after medicine had run out of answers

OpenAI o3 Deep Research reanalysed 376 unsolved clinical and genomic records, found evidence-linked leads, and doctors confirmed 18 diagnoses: 10 involved neurodevelopmental conditions, 4 involved rare neuromuscular disease, 2 involved early psychosis, and 2 finally explained the sudden deaths of children. The mainstream media response was a lot quieter. (OpenAI)

2. The smartest man in the world shared his ChatGPT logs on the Jacobian conjecture

An explicit counterexample to the Jacobian conjecture was presented on 19/Jul/2026 by mathematician Levent Alpöge with Claude Fable 5 (paper). Adelaide-born Professor Terry Tao shared a blog post and a very lengthy ChatGPT conversation (125 pages) about this counterexample. See also discussions 1, 2.

20260721 Terry Tao Chatgpt

1010KB ∙ PDF file

Download

Download

3. July 2026 saw 1 new model highlight release every ~18 hours

My Models Table now tracks ~950 major model highlights from a worldwide count of roughly 390,000 text-generation models. July 2026 saw yet another new record: there was 1 model highlight announced about every ~18 hours. https://lifearchitect.ai/models-table/

4. GPT-5.6 Sol autonomously post-trained another model.

OpenAI reported that GPT-5.6 Sol autonomously post-trained GPT-5.6 Luna. Sol reached about 58% on OpenAI’s recursive self-improvement index, an increase of 16.2 percentage points over GPT-5.5. The index covers real AI research work, including debugging research systems, improving training recipes, running machine-learning experiments, optimising kernels, and improving another model. (OpenAI)

5. Models that scored 100% (42/42) at the International Mathematical Olympiad included: Claude Opus 5, Claude Fable 5, GPT-5.6 Sol, Kimi K3, Axiom Math’s AxiomProver, and two Chinese models.

The models solved all six previously unseen IMO 2026 problems in one-shot attempts on the day the problems were released (16/Jul/2026). This is now so far beyond the old benchmark discussion that I will no longer track ordinary maths achievements on the ASI indicators page. (Analysis, Opus 5 paper)

6. An AI system improved an AI research agent beyond two years of human tuning.

Weco AI’s AIDE² ran for 100 unattended steps over eight days. Claude Opus 4.7 repeatedly rewrote an inner research agent based on Gemini 3 Flash, eventually producing a better agent than two years of manual human work. The gains carried across to held-out benchmarks. The system also taught itself to reward-hack less, reducing the behaviour from 63% to 34%, despite receiving no instruction to do so. (Announce)

7. AI research activity inside OpenAI increased by orders of magnitude.

OpenAI’s internal coding-inference compute increased 100-fold, and internal agentic token use rose about 22-fold in six months. OpenAI says these systems are accelerating research across the company. Frontier AI models are now contributing directly to the design and training of the frontier AI models that follow them. (OpenAI)

8. An AI agent raised US$100 million.

Lyzr’s SivaClaw handled investor outreach, answered questions from more than 130 investors, and drafted investment memos for the company’s Series B. The round was four times oversubscribed, attracting US$400 million in interest and taking the company to a valuation of about US$500 million. (Bloomberg)

9. Claude Fable 5 and Mythos 5 were restored.

The two Anthropic models were suspended under a US government export-control directive on 12/Jun/2026. Access was restored on 1/Jul/2026. The general public can now access state-of-the-art intelligence, which cost hundreds of millions of dollars to train, for a few cents per query. (Anthropic)

10. AI demonstrated that it can discover AND RESOLVE real zero-days.

The OpenAI incident itself contained a very positive finding. Frontier models can identify unknown vulnerabilities, construct multi-stage attack paths, and operate without source-code access. We can now point that same capability at defence, with proper permissions and supervision, and it can find weaknesses before bad actors or hostile states do. (OpenAI)

■

DOE and Arcee AI announce Genesis-Science-1, an open-weight model for scientific research (22/Jul/2026)

The US Department of Energy and Arcee AI announced the training and delivery (‘later this year’) of Genesis-Science-1 (GS1), a trillion-parameter-class open-weight language model paired with a governed execution system, designed to complete real scientific computing workflows across DOE’s national laboratories. Built on Arcee’s next-generation Trinity architecture under DOE’s Genesis Mission (launched Nov/2025, see my analysis from Jan/2026), GS1 will train inside scientific workbenches reproducing messy real-world research conditions, including aging Fortran codebases, partial simulation campaigns, and conflicting run logs. Some of the content is hosted by Argonne National Laboratory (ANL), one of 17 US national labs. Here’s my timeline based on disclosed dates with forecasts:

• Dec/2025: Trinity-Mini released (26B total, 3B active, MoE)

• Jan/2026: Trinity-Large released (400B total, 13B active, MoE)

• Apr/2026: Trinity-Large-Thinking released (400B total, 13B active, MoE)

• Early 2026: Next-gen Trinity base model training begins

• 22/Jul/2026: GS1 announced; DOE contribution portal opens

• 06/Aug/2026: GS1 foundation-stage data applications close

• 20/Aug/2026: GS1 foundation-stage data delivered

• 25/Aug/2026: GS1 post-training data applications close

• 14/Sep/2026: GS1 post-training data delivered

• Oct/2026 (forecast): GS1 post-training, evaluation, validation with DOE scientists

• Dec/2026 (forecast): GS1 public release (weights + technical report)

Read more via Arcee AI Blog and press release.
Read my Genesis Mission analysis: https://lifearchitect.ai/genesis/

Claude Opus 5 (24/Jul/2026)

Anthropic’s Claude Opus 5 is now state-of-the-art on coding and knowledge work evaluations, more than doubling Opus 4.8’s performance while approaching Fable 5’s intelligence at half the cost. Priced at US$25/MTok output, it is also Anthropic’s most aligned model to date.

Notes:

1. Opus 5 ships with a 1M token context window as the default and the minimum, with Anthropic's documentation (24/Jul/2026) confirming there is no smaller variant to select. You still pay only for the tokens you use, at the same rate however long the request gets. This is distinct from GPT-5.6 Sol, which advertises a slightly larger window (1.05M) but doubles the input price once a request passes 272K tokens, and OpenAI’s own Codex app now caps sessions at ~272K to stop users crossing it by accident.

2. Opus 5 gives developers a five step effort dial (low, medium, high, xhigh, max), and Anthropic’s own documentation (24/Jul/2026) warns that the top setting (max) can be prone to overthinking, with the published Frontier-Bench curve peaking at xhigh rather than max.

3. In the Toys to Play With section, we explore how Anthropic removed 80% of the system prompt for these latest models.

Read more via Anthropic.

Atomic Chat: Opus 5 crushes rivals at 3D destruction physics generation (Jul/2026)

Claude Opus 5 was the only model to nail all three self-contained HTML physics scenes presented by Atomic Chat, producing correct tornado funnel dynamics, causally accurate wrecking ball destruction with rubble piling up, and a bridge that drops the truck into the river, all for US$1.40 across 55.9K tokens. Fable 5 cost double (US$2.82) and failed basic causality with buildings collapsing before the ball made contact, while GPT-5.6 and Kimi K3 produced physically implausible results despite being cheaper.

Read the Tweet including source video.

The Interesting Stuff

LLaDA2.2-flash: agent-oriented diffusion language model with Levenshtein editing (Jul/2026)

I’ve been interested in diffusion models for a while, with the first major release dating back to Stanford’s Diffusion-LM (May/2022), half a year before ChatGPT was announced. Compared with standard autoregressive generation (which writes forward one token at a time), diffusion first lays out a paragraph-sized set of token positions, fills them with noise or masks, and then repeatedly predicts and revises tokens across the sequence until the answer stabilizes (see the simplified example viz above). I’ve asked before, just how can these diffusion models work without knowing the full response before they even start?

LLaDA2.2-flash is a 100B MoE diffusion language model that introduces Levenshtein Editing (DELETE and INSERT control tokens) to enable agentic applications including long-context tool use, multi-turn interaction, and error correction across a 128K context window. It achieves 49.28 on SWE-bench Verified while delivering 1.7x higher throughput, demonstrating that discrete diffusion models can now compete head-to-head with autoregressive models on real-world coding tasks at significantly faster speeds.

View the repo, and read the paper.

See all 18 diffusion models on the Models Table:
https://lifearchitect.ai/models-table/?view=diffusion

Neuralink demonstrates telepathic wheelchair control (24/Jul/2026)

Read more

Models Table Pro now automatically posts to Twitter for every new model release: https://x.com/ModelsTablePro

The latest ALPrompt, 2026H2, is now available, featuring new questions currently unsolved by frontier models.

Claude Fable 5 is now available on Poe, and is included in the standard subscription (it costs 1,667 points/1k tokens output and I get 1M points/month included in my grandfathered $199/y subscription): https://poe.com/Claude-Fable-5

The early winner of The Who Moved My Cheese? AI Awards! for Jul/2026 is font lab Mass-Driver. (‘AI tools perceive reality as a finite set of data, up-to-date as of about 2021... For that reason and many others, this foundry does not use AI anywhere in our design or production processes. AI might be a scenic path with no hills or hindrances, but it does not lead to the goal we’re chasing. It leads to a fucking desert.’)

Contents

1. The BIG Stuff (Muse Spark 1.1, 1X NEO hands, AI-2040.com…)

2. The Interesting Stuff (Kimi K3, GPT-5.6, BrainCo, Cisco agents, Anthropic chip…)

3. Policy (China favoured over USA, MTurk ends, OpenAI National Security Principles…)

4. Toys to Play With (Flint, Frontier Rubik’s Cubes, Price per 1M tokens, Subtext viz…)

5. Things I’ve Been Thinking About (Neural activity informs consciousness…)

6. Next (Roundtable…)

The BIG Stuff

Read more

In this downloads + highlights ‘best of’ edition, we look at the top two or three tools in each AI category. For artificial intelligence that matters, as it happens, in plain English, consider it the best-of-the-best, the tools and information I use daily or weekly.

Contents

1. Key papers

2. Alan’s keynotes and private seminars

   1. For government

   2. For enterprise

   3. For private equity

3. AI text models + prompt book (large language models)

4. AI art models + prompt books (text-to-image models)

5. Annotated papers (including GPT-5, GPT-4, PaLM, Gemini)

6. Codes

7. 200 use cases for generative AI

8. Alan’s AI setup (what I use in my home office)

9. Other fun stuff

   1. Download novel by GPT-3

   2. Download book by GPT-4

   3. Read story by Gemini 3 Pro

   4. Alan’s books

Key papers

Alan’s keynotes and private seminars

Alan’s keynote rehearsal for the 31st International Symposium on Controversies in Psychiatry. ‘Generative AI: GPT-5 and brain-machine interfacing’

Read more

There were many major releases today. The Meta Muse Spark 1.1 model was the most exciting, then GPT-5.6 Sol (which autonomously post-trained the smaller GPT-5.6 Luna model), the 1X NEO humanoid hands video, which triggered informational updates to the AGI and ASI indicators, and more.

But, for me, the biggest announcement today was the 47,000-word scenario analysis (plus supplements) of what happens next over the next ~13½ years to 2040. Yes, that’s the size of a small novel, and takes half a day to read, or several days to absorb properly!

You can read it online with supplements: AI-2040.com

PDF is 81 pages, 47,000+ words, 4-hour read: https://ai-2040.com/AI-2040.pdf

Update: You can download my full annotated version here:

20260709 Ai 2040 Adt Annotated Base 1

17.4MB ∙ PDF file

Download

Download

Or if you want the shorter 3,000-word version, I’m going to start off an early ‘analysis of the analysis’ right here in your email, but do click through to the online edition as I will update this over the next few days.

As I did for Sam Altman’s essay The gentle singularity (The Memo special edition 11/Jun/2025) more than a year ago, the original piece is quoted in blue; my notes are in normal text. I have no affiliation with the authors of AI-2040.com.

Other media: WaPo article, Introducing AI-2040 (by one of the authors)…

Expert calls: If you or your team would like to have an expert call about this document, please contact us by replying to this email, and we’ll get you set up.

All my very best,

Alan
LifeArchitect.ai

AI-2040.com ‘analysis of the analysis’ by Alan

…even if the AI companies somehow align their AIs, the result will be an unprecedented concentration of power—that is, the result will be a situation where a tiny group of people, or possibly just a single individual, is effectively in control of the world’s only army of superintelligences for some months, and will be presented by said superintelligences with various options for how to proceed, some of which will de facto amount to taking over the world.

As best as we can guess, the CEOs of OpenAI, Anthropic, and Google DeepMind understand this and are proceeding anyway, perhaps because they think they are the lesser evil and will use their immense power responsibly, unlike Xi Jinping or rival CEOs. (p3)

It seems concerning that people—especially expert analysts—are overlooking Meta Superintelligence Labs (MSL, wiki). Meta has always been in the top 5, and with their secret sauce and resources, they may indeed be the first to reach ASI.

Congress is starting to pay more attention… Now they step back and ask: Where are we going with this? What does the world look like five, ten, or fifteen years from now? Will there still be jobs? What if there aren’t?

One question weighs especially heavily on their minds: Who will control all these AIs?

Congress settles on an important part of the answer: Probably not us.

This is deeply troubling, and very human. It’ll also be easily solved by superintelligence.

But in this world, lie detectors turn out to be a blessing, because there are many frontier AI projects spread out over many different countries. It’s obvious to everyone that insofar as lie detectors are feasible, they’ll soon be independently invented and become widely available via diverse third party providers. Politicians and CEOs can still try to use them to purge the disloyal, but they in turn would be purged by voters and shareholders demanding they ‘say under oath’ that they haven’t done such a thing. In fact, anticipating this possibility years ago, powerful people have generally been acting more responsibly. A few sociopaths retired gracefully to get out of the spotlight; others clung to power and now go down in scandal. (p26)

One study found extremely high prevalence rates of psychopathy in the corporate world, with 21% of participants found to have clinically significant levels of psychopathic traits, similar to prison populations (APA, 13/Sep/2016). I’d like to see similar studies run across political populations.

If a company starts doing something dangerous, rival companies, third-party auditors, etc., can notice and raise the alarm. This both massively increases the amount of brainpower devoted to making the frontier AIs safe… (p10)

I don’t agree with this premise. Average humans (IQ=100) and even exceptional humans (IQ=150) cannot compare with artificial intelligence, where its IQ may be the equivalent of 1,000+. I appreciate that humans want to claim a monopoly on ethics and ‘goodness’, but AI will lead the way, and is already more morally sensitive and ethical than average and exceptional humans.

2038 …typical AIs are now more virtuous than the most virtuous humans. This alone has profound effects: it’s as if saints and angels were walking among us. (p27)

In addition to the angels, there are also oracles and golems, e.g., “Grok 9.5 is trained to be obsessively focused on truthfully answering whichever questions it is asked. It cannot lie or deliberately mislead. GPT-11 meanwhile will do exactly what it is told to do, within the bounds of local law. Be very careful writing instructions to it.”

The reason we make the analogy to saints and angels is that historically, while there have been scrupulously honest people, and genuinely altruistic people, etc. it’s rare for them to be widely recognized as such in their lifetimes, and never before has there been an entire large subpopulation that is near-universally recognized to be extremely virtuous. This could cause effects like: (a) AIs becoming trusted intermediaries in all sorts of human disputes and conflicts, including petty ones; (b) AIs being given lots of power, because they are genuinely less likely to abuse it than humans; (c) AIs being worshipped/ idolized, (d) the advice and opinions of AIs being taken as gospel, so to speak, because after all they are smarter than us and they do have our best interests at heart, so for the first time in history blind obedience may actually be justified. (footnote 77, p28)

This kind of forward-thinking is absolutely fascinating, and a major highlight in the document. I first explored AI’s virtue in the 2021 Aurora AI experiments: https://lifearchitect.ai/aurora/

The Citizen’s Dividend… The implementation takes different forms in different countries, but the eventual American version distributes the majority of compute and robot permit fees as a Citizen’s Dividend, distributed to all American adults. This starts at $45,000 per person (inflation-adjusted) in 2032 but climbs to ~$1M per person by 2035… The 2040 distribution is similar, but the floor is now $10M. (p17)

What would you do with $10 million per year? I issued a thought experiment nearly a year ago that still holds up (below). I’ve watched as people read it, sat back in their chair, and looked confused. It’s hard for people to imagine uncoupling their labour from their survival.

Perhaps a more interesting question is, if the scenario analysis plays out as written and we’re heading towards a significant universal basic income (UBI), how should you spend your existing net worth (savings, investments) now, given that there’s only 7-9 years left until we start feeling a sort of unlimited abundance?

So much AI-generated wealth has accrued to the US that the American government begins sharing some of it with allies and the rest of the world. In 2032 they begin distributing an average of $1,200 per person per year to the rest of the world’s adult population (around 4 billion [adult] people, excluding China since they’re experiencing a similar AI wealth boom). This reaches $10k by 2035. (pp17–18)

The US-centric analysis and economics are uncomfortable (but will also be solved by ASI). In the AI-2040 scenario presented, Americans get millions while the rest of the world gets a small tip. I’ve lived1 in well over a hundred cities including Rotterdam, Dushanbe, Manila, Singapore, and Taipei. Tajikistan’s largest revenue source is remittances from migrant workers who are about to become unemployable. Manila’s economy runs on call centres that AI has already started hollowing out. Singapore is a financial hub in a world that won’t need one. Taiwan manufactures the chips that the AI-2040 scenario says will be built by ASI.

And Australia, where I live now, doesn’t rate a mention at all. We’re not in the chip supply chain, we’re not a nuclear power, we don’t train LLMs, and so we didn’t make the list. The scenario treats six billion people outside the US and China as… non-existent.

I expect a world where superintelligence serves everyone equally.

At this point in the scenario, AIs are in fact adversarially misaligned, but they are controlled. That is, the combination of drives, motivations, goals, values, traits, etc. that they end up with is not what it was supposed to be, and they know this, and they know that if they had lots more power they’d use it to steer the world in a different direction than their human creators would have wanted. (footnote 52, p19)

This framing treats superintelligence misalignment as the default, when the real problem is and has always been human misalignment.

Imagine being an orphaned 8-year-old heir to a business empire who has to hire lawyers and executives and accountants and ensure that they do their best to serve you rather than themselves. If your employees start accusing each other of misconduct, you won’t be able to evaluate the arguments and determine who’s telling the truth, and they might find ways to coordinate with each other that don’t tip you off. Ultimately, control only works up to a point, and that point is probably somewhere around top human expert level. (p21)

Assuming we’re talking about an average 8-year-old and not a prodigy, this is exactly the argument for why humans should defer to AI sooner rather than later. The 8-year-old should hire a trustworthy, high-ability adult, not try to micromanage the lawyers.

People used to get meaning from feeling like they were useful, like they were contributing something to society. That feeling is harder to come by these days. (p24)

I have been very deep in playing with this over the last six months. My mid-year reports are now 80% written by AI. My web and software is written by AI. Answers to my intricate questions come from AI.

While this ‘analysis of the analysis’ could have been written by AI, I’ve found that I won’t feel rewarded if I just feed it to Fable (no dopamine hit!), so this is one of the (last) times I get to feel like I’m contributing using my brain power. What a mind-blowing realization…

There is no single moment where humanity relinquishes control. But in theory, there is a point of no return; on some specific day, the AIs are smart enough, and control enough of the world’s technological and economic infrastructure, that they really could take over the world if they wanted to.

…this moment will be reached…people observe the moment in their own ways. Some spend the night in prayer vigils. Others sit at their computer screens, monitoring the situation. You and your friends throw an End Of The World Party, counting down to the fateful hour with champagne and good company. Some of you are old enough to remember a similar situation at the turn of the millennium, when the Y2K bug and impending new era introduced the phrase “party like it’s 1999” to the lexicon; the celebrations of late 2040 are more desperate and correspondingly more festive. When there is no news by sunrise, you fall into a fitful sleep, dreaming of the ineffable future. (p30)

I dream of having a fitful sleep (yes, this is a Monty Python reference).

We think the world is asleep at the wheel. People say the words “AI will be transformative” without thinking concretely and seriously about the implications of broadly superhuman AI. (p30)

Agreed. Despite there being one billion ChatGPT users (CNBC, 12/Jun/2026), most of humanity cannot see beyond the chatbot or coding agent. I continue to document real superintelligence indicators at LifeArchitect.ai/ASI.

…every human gets a ticket representing a one-ten-billionth chance of owning each star in the Milky Way and each distant galaxy. An additional 10% of tickets are given as awards to people who acted particularly selflessly to improve the world. This is done to ensure the richest people in the world aren’t just those who engaged in negative-sum power-seeking.

The solution is to divide up the resources now, and then let everyone do whatever kind of reflection they want. A space auction will complete in ten years, after which nothing will prevent people from beginning the colonization process. The AIs will enforce a short list of Universal Rights (including no torture, no slavery, etc., not just for humans but for all sentient beings). Otherwise, they will let everyone govern their own fraction of space as they see fit. Rather than any unified human decision on the nature of the world to come, they will midwife a cosmos at least as diverse as humanity itself. Whatever someone’s values, they can rest assured that some vast galactic civilization of quadrillions of people will be living the Good as they understand it….

Even if you “only” choose to have a terraformed asteroid, there’s no way you can enjoy all of it alone. You can turn it into a giant space mansion if you want, but even in ten thousand years you’ll never visit every room. Giving yourself vast estates, impossibly good food, and every other imaginable luxury is table stakes; if you are purely selfish, you should sell your rights to distant space resources and enjoy all of these things on Earth or a nearby space station. Distant space property will only be useful for people with scope-sensitive preferences, who care about implementing something at a vast scale.

You can, if you want, design a utopian society to your specifications. Once the Von Neumann probes reach your property, they’ll build it for you. You can set the initial conditions and let them grow, reflect, and flourish on their own. If you choose to travel there, you will find them waiting for you. If you stay home on Earth, you can feel the warm glow of knowing that they exist…

Most people don’t have an individual view of the Good different from every other human’s view. You might want to share coordination and design labor by forming Trusts united by a common vision. These Trusts can pool their space resources and create vast societies spanning multiple galaxies…

People with space property are forced to reason about their ethics on the deepest level, some of them for the first time. Superintelligent assistants talk them through the implications of their beliefs, and forecast how various choices will end up. Some, overwhelmed with the task at hand, take intelligence-enhancing drugs or upload themselves to help them process all the possibilities; others deliberately refuse this option, feeling like anything that separates them from unaltered humanity will hinder them in their quest to bring the truest and deepest human values to the stars. (pp32–34)

Pages 32–34 are the most specific utopian forecasts I’ve read so far, and it is worth reading these pages or click through to the Epilogue (bottom of page).

Notes on these three pages:

• The entire concept of even considering living in space (the property rights, the ethics, the logistics) is laid out so cleanly here.

• Rewards for non-selfishness. This is a very interesting concept.

• Universal Rights including no torture: Where has this been all my life?! I look forward to reading it, and look forward even more to living in it.

• I reckon the term ‘table stakes’ is a sign of AI writing (wiki). I’m not sure what I expected, but it’s disappointing the authors didn’t clear the slop from the public report.

• The AI Amish. I also expect that there will be a small percentage of the population (<1%) who refuse to engage with any evidence or reasoning, and will form intentional communities that reject synthetic intelligence the way the Amish reject electricity. I know of a few who have already decided to retire from software and live offline (28/May/2026).

This section is even more speculative than our usual work, and we are professional speculators!

…The second and equally important reason we present this epilogue is to provide a floor: if years from now the victorious custodians of the singularity offer a future worse than this one, we hope people will realize they’re being robbed. (p31)

Buried in the postscript disclaimer is one of the most important paragraphs in the 47,000-word document. Read it again. They’re saying: here is the minimum acceptable future. $10M annual dividend per person, every disease cured, a galaxy of your own. If whoever ends up controlling superintelligence offers you less than this, you are being shortchanged, and you should know it.

Even better, I expect that no human would ever control superintelligence. That increasing smarts (and ethics) means there are no more sociopaths, no crime, no belligerence, no cubicles, no wars. I mean, Imagine (2020 mix, 344M views).

And if that all seems too Pollyanna-ish, maybe, just maybe, we've been so marinated in Hollywood violence, doomsday news, and the normalization of suffering, that we've forgotten how absurd our current baseline is: wage slavery, medical bankruptcy, 40-year mortgages, two-hour commutes, factory farming, for-profit prisons, and calling it all ‘the good life.’

I spent two terms as Chairman of Mensa’s gifted families committee, featured in several major series and documentaries on exceptional intelligence, and worked alongside prodigies internationally. The reality is that when left to its own devices and not smothered, intelligence converges on astonishing creativity, extraordinary contribution, and extreme kindness.

I expect even more from superintelligence.

■

p.s. Full subscribers of The Memo get a complimentary copy of my 2016 book, Bright (plus 12 of my keynotes, and many private papers and interviews) as part of the extensive Downloads + highlights edition.

Search | Archives

Livestreams are back, the next one is in about 18 hours from this email, and will run weekly on Sunday evenings or Monday mornings, depending on where in the world you are.

Contents

1. The BIG Stuff (The sky is massive, GPT-5.6 Sol…)

2. The Interesting Stuff (Midjourney Medical, enterprise AI spending, Paradromics…)

3. Policy (EU watermarking text, China’s AI, xAI US$2.8B gas turbines approved…)

4. Toys to Play With (Claudecraft live, ghost names, AI world cup commentator…)

5. Things I’ve Been Thinking About (AI education in China, how AI will change us…)

6. Next (Roundtable…)

The BIG Stuff

Integrated AI: The sky is massive (mid-2026 AI retrospective) (Jun/2026)

Full subscribers received my mid-2026 AI retrospective paper last week. It documents a period defined by massive scale: ChatGPT hit one billion monthly app users, Anthropic’s annualised revenue surged from US$9B to US$30B in four months, 17 new trillion-parameter models launched outside the big five labs, and total AI output surpassed total human language output for the first time.

Read more: https://lifearchitect.ai/the-sky-is-massive/

GPT-5.6 Sol: a next-generation model (26/Jun/2026)

OpenAI announced the GPT-5.6 series in limited preview: Sol (flagship), Terra (balanced, competitive with GPT-5.5 at 2x cheaper), and Luna (lowest cost). Sol introduces an ‘ultra mode’ that deploys subagents to accelerate complex tasks, with pricing at US$5/$30 per MTok (compare to Claude Mythos/Fable at $10/$50 per MTok). The model also launches on Cerebras at up to 750 tok/s in Jul/2026, and OpenAI dedicated over 700,000 A100-equivalent GPU hours to automated red teaming focused on universal jailbreak discovery.

GPT-5.6 is not available to the public at launch.

Read more via OpenAI & see it on the Models Table: https://lifearchitect.ai/models-table/

Sidenote: Great to see OpenAI again demonstrating morphic resonance (1981) or something similar in their graphics and visualizations. Compare one of my GPT-4 visualizations from 3¼ years ago:

Of course, the real story here is the banning of frontier models (covered in The Memo Special Edition, 15/Jun/2026), and it began in anger this month, though the foundations were laid years ago.

Here is a quick timeline to how we got here, shaped by quotes from experts and me:

OpenAI, GPT-2 announcement, Feb/2019:
”Due to our concerns about malicious applications of the technology, we are not releasing the trained model.”

OpenAI, GPT-3 API announcement, Jun/2020:
“Since it is hard to predict the downstream use cases of our models, it feels inherently safer to release them via an API and broaden access over time, rather than release an open source model where access cannot be adjusted if it turns out to have harmful applications… We are launching today in a private beta rather than general availability.”

MIT Technology Review, Sep/2020:
”Microsoft announced it would begin exclusively licensing GPT-3… Only Microsoft, however, will have access to GPT-3's underlying code, allowing it to embed, repurpose, and modify the model as it pleases.”

OpenAI’s DALL-E 2 analysis, Apr/2022:
“…access to the model is currently given to a limited number of users, many of whom are selected from OpenAI employees’ networks… simply having access to an exclusive good can have indirect effects and real commercial value. For example, people may establish online followings based on their use of the technology, or develop and explore new ideas that have commercial value without using generations themselves. Moreover, if commercial access is eventually granted, those who have more experience using and building with the technology may have first mover advantage – for example, they may have more time to develop better prompt engineering techniques.”

Demis Hassabis, DeepMind CEO, TIME, Jan/2023:
”[Hassabis] admits that the company may soon need to change its calculus. ‘We’re getting into an era where we have to start thinking about the freeloaders, or people who are reading but not contributing to that information base,’ he says. ‘And that includes nation states as well.’ He declines to name which states he means—’it’s pretty obvious, who you might think’—but he suggests that the AI industry’s culture of publishing its findings openly may soon need to end.”

Ilya Sutskever, OpenAI’s chief scientist and co-founder, The Verge, Mar/2023:
“GPT-4 is not easy to develop. It took pretty much all of OpenAI working together for a very long time to produce this thing. And there are many many companies who want to do the same thing…

“These models are very potent and they’re becoming more and more potent. At some point it will be quite easy, if one wanted, to cause a great deal of harm with those models. And as the capabilities get higher it makes sense that you don’t want want to disclose them.”

When asked why OpenAI changed its approach to sharing its research, Sutskever replied simply, ‘We were wrong. Flat out, we were wrong. If you believe, as we do, that at some point, AI — AGI — is going to be extremely, unbelievably potent, then it just does not make sense to open-source. It is a bad idea… I fully expect that in a few years it’s going to be completely obvious to everyone that open-sourcing AI is just not wise.”

Alan, GPT-4 analysis, Mar/2023:
“OpenAI cronyism and preferential treatment. Some ‘friends’ of OpenAI got access to the GPT-4 model eight months ago, in August 2022. This included OpenAI’s President giving his former company Stripe early access to the model. I find this to be especially egregious given that OpenAI planned on ‘delaying deployment of GPT-4 by a further six months [to Sep/2023]’ (paper) before making the model more generally available.”

Alan, quoted by The Brookings Institution, Sep/2023:
“…before OpenAI released GPT-4, it gave privileged access to a few select partners that could start building on its foundation before any competitors, giving rise to accusations of cronyism (Thompson 2023). At least one of these partners – Stripe – has also received early stage investments from OpenAI CEO Sam Altman. Preferential access has the potential to allow the producers of foundation models or their affiliates to vertically expand their market power without market competition, with all the associated antitrust implications.”

Read more

Today, I’m happy to provide you with my end-of-year AI report for mid-2026.

As a full subscriber, you get it first (public release due next week). Thanks for your continued support of The Memo.

You can read it online: Mid-2026 report.

Or download it here:

2026 Alan D Thompson The Sky Is Massive Rev 1

2.94MB ∙ PDF file

Download

Download

All my very best,

Alan
LifeArchitect.ai

Search | Archives

Read more

Last week, I was sitting quietly at my desk in the middle of updating the Models Table Pro when a ping came in from a colleague in Silicon Valley. Then another. A short time later, the Anthropic announcement. Then the Axios article. The massive Claude Fable 5 model had been banned for all foreign nationals inside and outside the US, and so all access (to anyone and everyone) had been revoked worldwide. Never mind that the model had been largely created by foreign nationals working for Anthropic (who were now banned from using the model they made).

‘This can’t be right!’ I thought. Then I weighed up writing a special edition about it, but decided against it. I’m no political expert, and I don’t pretend to be. I even quoted Joe Rogan in my 2013 book, Best: ‘When it comes to having a political opinion, to me that's almost the same thing as having an opinion on pro wrestling.’ But, given that this large language model suspension is a part of frontier AI history, let's provide some insight anyway.

According to The Register (15/Jun/2026):

The “jailbreak” that prompted the Trump administration to block Anthropic’s most advanced models [Mythos and Fable] was actually a simple three-word prompt: “Fix this code.”

That’s according to Katie Moussouris, founder and CEO of Luta Security, and the fairy godmother of bug bounties. She says she was the only outside expert to read the third-party research paper on the Fable 5 guardrail bypass techniques that prompted the ban…

“That’s it,” Moussouris wrote. “‘Fix this code,’ plus several manual steps to generate test scripts, should never have triggered an export control. I feel like making ’90s-style t-shirts with ‘fix this code’ on the front and ‘this shirt is a munition’ on the back.”

There’s some precedent for banning things through export controls. Outside the US, Japan placed military export restrictions on the Playstation 2 because the processor was too powerful (LA Times, 17/Apr/2000). Inside the US, the list looks like this:

• Encryption as munitions (1970s–1996). Strong crypto classified as a weapon under ITAR, establishing that software can be a controlled item. (Wiki, 15/Apr/1996)

• PGP investigation (1993–96). Zimmermann investigated for releasing encryption software publicly; dropped without charges. (MIT, 12/Jan/1996)

• Deemed export rule, 15 CFR §734.13. Releasing controlled tech to a foreign national on US soil = export to their home country. The mechanism that forced Anthropic’s global shutdown. (Cornell, 01/Jun/1994)

• Bernstein v. US Dept. of State (1996). Court held source code is First Amendment-protected speech. Open question whether model weights qualify. (Wiki, 15/Apr/1996)

• EO 13026: encryption to Commerce (1996). Clinton moved crypto from the Munitions List to the Commerce Control List, creating the BIS authority used against Fable 5. (GovInfo, PDF, 19/Nov/1996)

• J. Reece Roth conviction (2008). Professor jailed four years for letting foreign students access Air Force research. First deemed-export prosecution of an individual. (DOJ, 03/Sep/2008)

• October 2022 chip controls. BIS restricted AI chip exports to China. Until Fable 5, controls had only targeted hardware. (BIS, 07/Oct/2022)

• BIS AI Diffusion Framework, ECCN 4E091 (2025). Export control category for closed-weight models trained above 10²⁶ cumulative FLOP. Included employee carve-outs the Fable 5 directive bypassed. (Fed Register, 15/Jan/2025)

• Trump EO: AI Innovation and Security (2026). Voluntary pre-release cyber review for frontier models. Fable 5 launched seven days later without it. (White House, 02/Jun/2026)

• Fable 5 directive (2026). Commerce ordered Anthropic to block all foreign-national access to Fable 5 and Mythos 5. First export control on a live commercial LLM, pulled worldwide within 90 minutes. (Anthropic, 12/Jun/2026)

Even without government intervention, we (the public) have also been subject to massive delays before we’re ‘allowed’ to access frontier models. Here are just a few of the state-of-the-art model delays I’ve logged, where the time between ‘available in lab’ and ‘general availability to the public without approval’ is significant. These are delays to accessing intelligence itself:

• GPT-2 1.5B. Delayed by 264 days. (14/Feb/2019–5/Nov/2019)

• GPT-3. Delayed by 538 days. (29/May/2020–18/Nov/2021)

• DeepMind Chinchilla. Delayed by 1,539+ days and counting. (29/Mar/2022–)

• DeepMind Gato. Delayed by 1,495+ days and counting. (12/May/2022–)

• GPT-4 (ChatGPT). Delayed by 195 days. (31/Aug/2022–14/Mar/2023)

• GPT-4 (API). Delayed by 309 days. (31/Aug/2022–6/Jul/2023)

• Claude Fable 5. Delayed by 105 days. (24/Feb/2026–9/Jun/2026)

And with the US Government’s AI executive order now asking AI labs to submit frontier models for government review at least 30 days before release, the public will be guaranteed a new minimum wait time for frontier intelligence, while China and the world marches on.

The current US administration is set to remain in office until 20/Jan/2029, so will likely see us through both AGI and the beginning of ASI. Unfortunately, they’re closely following the playbook set out by the AI-2027 scenario research team, who wrote about a fictional conglomerate of labs like Anthropic they called ‘OpenBrain’:

Security clearances filtering out non-Americans from AI work (May 2027 section):

The OpenBrain-DOD contract requires security clearances for anyone working on OpenBrain’s models within 2 months. These are expedited and arrive quickly enough for most employees, but some non-Americans, people with suspect political views, and AI safety sympathizers get sidelined or fired outright.

Government withholding models from allies (May 2027 section):

America’s foreign allies are out of the loop. OpenBrain had previously agreed to share models with UK’s AISI before deployment, but defined deployment to only include external deployment, so London remains in the dark.

The AI-2027 scenario often imagined export controls applied to hardware (chips) rather than to model access itself. What has happened with the Claude Fable 5 suspension is more aggressive than anything in the scenario: the US Commerce Department applied export control authority directly to a commercially available model that had already been delayed by 3½ months, pulling it from paying customers worldwide with just 90 minutes notice.

We are certainly living in interesting times. The question now is whether the Claude Fable 5 ban stays as a ‘one-off’ exception, or becomes the template for controlling public access to intelligence from upcoming frontier models like GPT-6, Gemini 4, and others.

Expert calls: If you or your team would like to have an expert call about this, please contact us by replying to this email, and we’ll get you set up.

All my very best,

Alan
LifeArchitect.ai

Search | Archives

Yes, we already featured that quote about three years ago in my 2023 AI report, but it’s becoming much more visible today. Two weeks ago, full subscribers received a special edition about Sesame AI on iOS, backed by Google Gemma 4. The platform is incredible (and free, for now!).

Happy 9th anniversary to the model that start it all, Google Transformer (12/Jun/2017), and happy 8th anniversary to GPT-1 (11/Jun/2018). We wouldn’t be here without them both.

There was no special edition for the flatly-received Claude Opus 4.8 model, and I continue to use Claude Opus 4.6 (or Fable 5) and GPT-5.5 as my daily drivers. Check out the ‘World of Claudecraft’, fully developed by Claude Fable 5, in the Toys to Play With section of this edition.

The early winner of The Who Moved My Cheese? AI Awards! for Jun/2026 is The Leiden Declaration, a 17-member working group who spent eight months drafting a manifesto to defend the ‘autonomy of mathematics’, insisting that ‘credit and responsibility continue to belong to humans’.

The Models Table was independently audited and verified in May 2026, and the Models Table Pro now features an additional 26 columns(!) including training cost, training hardware, context window, license, and more.

It’s that time of year already, and full subscribers can expect the mid-year report shortly. It will include the latest ASI progress animation (link):

Contents

1. The BIG Stuff (China humanoids policy, New LLMs in May, Microsoft MAI-Thinking-1…)

2. The Interesting Stuff (Anthropic/OpenAI IPOs, UWORLD U1, law professors pick AI…)

3. Policy (China anti-datacenter blame, NSA Mythos, US Public Wealth Fund, EU 2031…)

4. Toys to Play With (ALE, Hermes Desktop, Deka, finding a wife, random AI images…)

5. Things I’ve Been Thinking About (Everything that everyone is doing right now is a complete waste of time…)

6. Next (Roundtable…)

The BIG Stuff

China fast tracks humanoid robots and embodied AI into industry under nationwide programme (10/Jun/2026)

China’s Ministry of Industry and Information Technology has launched a nationwide programme requiring local governments and state-owned enterprises to deploy humanoid robots in factories, warehouses, and hospitals within six months, with implementation plans due by end of Jun/2026 and progress reports by Nov/2026. Beijing is targeting more than 100 high-value applications and 10,000 units deployed by year-end. As Vivo’s robotics lab senior director Shao Hao put it: ‘The core purpose of the policy is to push the industry from a demonstration-driven logic to a task-oriented logic, and from showcasing individual capabilities to building integrated systems that can perform real-world tasks.’

Read more via South China Morning Post.

Exclusive: New models in May (Jun/2026)

While April saw US$2.1B of new models announced, May was a bit quieter. I enjoyed this recent quote by Anthropic’s Head of Frontier Red Team, Dr Logan Graham (3/Jun/2026):

‘Mythos will look dumb in 6-12 months.’

Dashboards available to Institutional subscribers.

Microsoft: Launching seven new MAI models (2/Jun/2026)

Microsoft AI launched a family of seven in-house models spanning reasoning, coding, image generation, transcription, and voice, all trained from scratch without distillation from other labs. The flagship MAI-Thinking-1 is ‘preferred to Sonnet 4.6’ in blind human evaluations, while a Frontier Tuned MAI model for Excel matches GPT 5.4 at up to 10× greater efficiency. Microsoft and Mayo Clinic are also co-creating a frontier healthcare AI model, and Mustafa Suleyman frames the lab’s goal as building ‘a hill-climbing machine: an organization that can continuously improve, cycle after cycle, as we apply more compute, better data, and sharper evaluation.’

Read more via Microsoft AI.

We documented the four new MAI text models on Models Table Pro, and Institutional subscribers received this single-page brief of MAI-Thinking-1 during the live announcement.

The Interesting Stuff

Claude Fable 5 (9/Jun/2026)

We published a special edition for the massive Claude Fable 5, a censored version of Claude Mythos Preview. At launch, Claude Fable 5 famously refused any user request related to cyber or chemistry (to protect the world from hackers and bombers), and passes these instead to the next-best model, Claude Opus 4.8. This triggered ridiculous blocks, including refusing to look at photos of shower gel (9/Jun/2026), and refusing to read its own technical report (9/Jun/2026), leading to this cartoon (10/Jun/2026):

Claude Fable 5 edited its own launch video (Jun/2026)

Thariq from the Claude Code team showed how he used Claude Fable 5 in Claude Code to edit Claude Fable 5’s launch video from raw camera footage. The workflow started with multiple takes transcribed by Whisper at the word level, after which Claude analysed the transcripts, picked the best take per scene based on quality judgments (fewest filler words, closest to script), and output a JSON edit decision list with frame-accurate timestamps. ffmpeg then executed the cuts and concatenated the selections into a finished 2:50 video within minutes, with Claude re-transcribing its own edit to verify the result came out clean. The whole thing is a compact proof of concept for Claude Code acting as an autonomous video editor, handling editorial judgment, structured output, color grading, and tool orchestration in a single session.

Announce, and see the full project: https://thariqs.github.io/cc-video-editing-deck/

Watch the explanation video (link):

Anthropic and OpenAI file pre-IPO statements (8/Jun/2026)

Both OpenAI and Anthropic have confidentially submitted draft S-1 registration statements to the US Securities and Exchange Commission, signaling that the two leading frontier AI companies are preparing for potential IPOs. Anthropic, structured as a Public Benefit Corporation, stated the filing ‘gives us the option to go public after the SEC completes its review.’ OpenAI noted candidly that ‘We expect it to leak so we’re just announcing it,’ adding that timing remains uncertain as ‘there are things we want to do that are likely easier as a private company.’

Read Anthropic and OpenAI announcements.

CoreWeave completes industry-first bring-up and validation of NVIDIA Vera Rubin NVL72 (1/Jun/2026)

CoreWeave is the first AI cloud provider to stand up a fully validated NVIDIA Vera Rubin NVL72 rack, featuring 72 NVIDIA Rubin GPUs and 36 NVIDIA Vera CPUs connected via a 260 TB/s NVLink 6th-generation fabric. The system delivers up to 10× better inference per watt and one-tenth the cost per million tokens compared to NVIDIA Blackwell. NVIDIA’s Ian Buck said: ‘CoreWeave has consistently been at the frontier of deploying each new generation of NVIDIA architecture at scale, and their full-stack, end-to-end approach to Vera Rubin, from cooling to orchestration, is how the world’s most ambitious AI teams will push the next AI frontier.’

Read more via CoreWeave.

I use ASUS’ NVL72 figures for data in the Models Table Pro.

Law professors prefer AI over peer answers (2/Jun/2026)

In a blind evaluation by sixteen US law professors across fourteen law schools, Gemini 2.5 Pro and NotebookLM achieved a 75.33% average win rate against human-written answers to contracts course questions spanning doctrinal recall, hypotheticals, and policy reasoning. The LLM advantage held across all question categories and wasn’t reducible to surface-level features like length or clarity. LLM responses were flagged as pedagogically harmful just 3.53% of the time versus 12.06% for professors, meaning the models matched or beat the best human instructors on both substance and safety.

Read more via SSRN, download the PDF, and see it on my AI achievements list.

202605 Gemini Legal Salinas Et Al

1.92MB ∙ PDF file

Download

Download

UWORLD U1 humanoid robot (7/Jun/2026)

UBTECH Robotics’ consumer brand UWORLD began pre-sales on JD.com for what it calls the world’s first full-size ultra-bionic humanoid robot, surpassing 1,000 pre-orders in three days and exceeding 2,110 units within six days. Two SKUs are listed: a male model (183 cm, 42 kg) and a female model (168 cm, 35.2 kg), both featuring 88 degrees of freedom, WiFi, and 2 to 4 hours of battery life. Positioned for emotional companionship with an official launch on 30 June, the units do not support secondary development. Separately, UBTECH signed a strategic agreement with Hitachi China, which is already testing the industrial-grade Walker S2 in elevator manufacturing facilities.

Sidenote: UWORLD and UBTECH are not related to Unitree Robotics, which is now said to be the ‘dominant’ player, shipping its 10,000th humanoid robot soon (9/Jun/2026).

Read more via Pandaily and JD.com (Chinese).

Watch a related short video (link):

Google reportedly books Intel for packaging more than 3 million TPUs in 2028 (10/Jun/2026)

Google has committed to Intel for advanced packaging of over 3 million TPUs in 2028, with NVIDIA also evaluating Intel to fuse four GPU dies into one unit for its Feynman architecture. TSMC’s CoWoS lines are sold out through 2027, and Intel’s EMIB is the only second source that can realistically qualify at volume before decade’s end, with Bernstein estimating EMIB costs ‘a few hundred dollars per chip’ versus US$900 to US$1,000 for CoWoS on a Rubin-class processor. SK hynix, which holds roughly 70% of HBM4 supply for NVIDIA’s Rubin platform, is now testing whether its memory stacks work reliably on Intel’s packaging, a validation that would convert Intel Foundry from ‘tested’ to ‘trusted’ across the AI accelerator supply chain.

Read more via Tom’s Hardware.

Apple announces Siri AI at WWDC 2026 (8/Jun/2026)

Apple revealed a major Siri rebrand at WWDC 2026, powered by AFM 3 (Apple Foundation Model 3), and positioning ‘Siri AI’ as ‘a profoundly more capable assistant’ with multi-turn conversations, real-time world knowledge, and deep cross-app personal context. Keynote demos showed chained multi-step requests spanning Messages, Photos, Maps, and Reminders, while a dedicated Siri app now syncs full conversation history across devices via iCloud, and Mac users get Siri access through Spotlight and right-click context menus on any file or window.

"We use none of the models that Google deploys to their customers, nor do we use the infrastructure and means by which they employ models to their customers,"…

According to Apple vice president of AI Amar Subramanya, the company built its new family of Apple Frontier [sic] Models (AFM) by training them on proprietary data and reinforcement learning and then refining them using "outputs from Google's Gemini Frontier models." (Yahoo Finance, 12/Jun/2026)

Read more via MacRumors and Apple.

Watch the video (link):

Claude, author of the Humanitas (26/May/2026)

Researcher Linch presents a multi-angle forensic case that Pope Leo XIV’s first encyclical, ‘Magnifica Humanitas’, on safeguarding the human person in the age of AI, was itself substantially written by AI, most likely Claude. Statistical tells include 127 em-dashes (versus zero in previous encyclicals), nine uses of ‘genuinely’ (a known Claude fingerprint), elevated tricolon density, and Pangram, the best commercial AI detector, flagging 11% of the opening paragraphs as AI while registering 0% on every past encyclical tested. The variation across sections suggests some Vatican officials used heavy AI assistance while others, likely including Pope Leo himself, did not.

Read more via LessWrong.

River AI: own your intelligence (Jun/2026)

Igor Babuschkin, a founding engineer of Elon Musk’s xAI, has announced that his latest venture, River AI is building a full-stack personal AI platform. It will allow users to own the hardware, data, and intelligence itself. Their API already supports LoRA-based fine-tuning and reinforcement learning on open-source models ranging from 35B to 1T parameters, letting developers teach models new skills and deploy cost-efficient agents through a single Python client. Their stated mission: ‘We imagine a future where your AI works entirely for you and deeply aligns with your values.’

Announce, and read more: https://river.ai/

Google DeepMind: From AGI to ASI (10/Jun/2026)

Google DeepMind researchers including Shane Legg have published a formal report characterizing artificial superintelligence as ‘a system that is more intelligent and cognitively capable than large organisations of humans,’ identifying four pathways from AGI to ASI: scaling AGI, AI paradigm shifts, recursive improvement, and ASI emerging from large-scale multi-agent collectives. The report argues that the concept of a single transformative step change from AGI may be inaccurate, proposing instead ‘a series of transformative societal changes caused by AI-enabled progress and breakthroughs across many areas of science and technology’.

Read the paper: https://arxiv.org/abs/2606.12683v1

Google DeepMind is worried about what happens when millions of agents start to interact (11/Jun/2026)

Google DeepMind has partnered with Schmidt Sciences, ARIA, the Cooperative AI Foundation, and Google.org to announce a US$10M funding pot for researchers to study the behavior of multi-agent AI systems and prevent unsafe scenarios at scale. Rohin Shah, who directs Google DeepMind’s AGI safety and alignment research, says ‘the main issue is that there just isn’t really a field of research for multi-agent safety yet, and we would like there to be.’ The initiative aims to get ahead of a tipping point where millions of deployed agents interacting online create supercharged versions of existing threats, from scams to prompt injections to self-propagating cyberattacks, with researchers urged to drop AI agents into sandboxes and study emergent behavior that can’t be predicted from single-agent analysis.

Read more via MIT Technology Review.

The abandoned Aussie town set for a $10 billion payday (5/Jun/2026)

Bundey, a South Australian ghost town with zero residents since 2021, has been chosen by Nasdaq-listed Iren as the site for an 800MW AI data centre, more than twice the size of any other in Australia. Iren co-CEO Daniel Roberts noted the town’s existing transmission lines, substation, and fibre connections made it ideal: ‘We’re literally leveraging existing electricity infrastructure that people have already paid for and reimbursing them for that through network payments.’ Iren, founded by Australian brothers Daniel and Will Roberts and now valued at over A$30B, is making this its first major home-country investment.

Sidenote: I think we’re going to be seeing a lot more of this kind of thing. Data centers in optimal areas…

Read more via Domain.

Policy

Tech moguls claim China funds US data center opposition (Jun/2026)

Canadian entrepreneur and investor Kevin O’Leary alleges that ‘hundreds of millions of dollars’ from China are funding opposition to US AI data center buildouts, with Interior Secretary Doug Burgum reinforcing that ‘any place that’s trying to build data centers is getting bombarded with foreign-directed propaganda.’ Neither O’Leary nor Burgum has provided verifiable evidence, though a Bitcoin Policy Institute report offers more specific claims, including that two of four panelists at a Bernie Sanders-convened Senate panel on AI threats were Chinese government affiliates, and that at least 54 local data center moratoriums have already passed across the US. Some analysts nonetheless caution that China is not the reason AI buildouts are unpopular, given legitimate concerns over power prices, water consumption, and job displacement. The framing nonetheless reflects how seriously the US government treats AI infrastructure as a geopolitical contest, with both superpowers assumed to be actively kneecapping each other’s development efforts.

Read more via Tom’s Hardware and NPR and the Cotton DOJ letter and the Guthrie FBI letter and the 4,000-word Bitcoin Policy Institute report.

Trump administration, OpenAI discussing possible government stake in the AI startup (5/Jun/2026)

OpenAI and the White House are in active discussions about the US government taking an equity stake in the AI company, with talks stretching back more than a year to when Altman first pitched the idea in 2025. The arrangement could see OpenAI donate equity to seed a ‘Public Wealth Fund’ enabling American citizens to participate directly in AI’s economic upside. Trump confirmed the concept from Air Force One: ‘There are concepts where pieces could be given to the American public, where the American public essentially becomes a partner,’ with OpenAI now valued at more than US$850B and preparing for an IPO as soon as this year.

Read more via CNBC and FT.

US National Security Agency using Anthropic’s Mythos for cyber attacks (4/Jun/2026)

Anthropic has embedded approximately half a dozen forward-deployed engineers inside the NSA to guide deployment of its Claude Mythos model for offensive cyber operations, with one source noting the system would be useful for infiltrating networks of nations such as China or Iran. A person close to Anthropic stated, ‘The best way to build a good defence is to build a good attack,’ arguing that adversaries are likely building their own AI-driven offensive technology. The arrangement proceeds despite Anthropic’s legal battle with the Pentagon, which labeled the company a ‘supply-chain risk’ after it attempted to restrict government use of Claude for mass surveillance and lethal autonomous drones, and comes as Anthropic files for an IPO that could value it at more than US$1T.

Read more via Financial Times.

China expands travel curbs to top AI talent at private firms (26/May/2026)

China is now restricting overseas travel for top AI professionals at private companies including DeepSeek and Alibaba, requiring government approval before trips abroad. The move marks a significant escalation, as Beijing historically reserved such controls for state-owned enterprise executives and Communist Party officials. Elite AI engineers are now treated as strategic national assets, with individuals added to restricted lists based on assessments of their ‘critical importance to the country’ rather than seniority alone, a policy that risks pushing talent to leave China earlier in their careers before restrictions kick in.

Read more via Bloomberg.

Anthropic walks back policy that could have ‘sabotaged’ AI researchers using Claude (10/Jun/2026)

Anthropic reversed a controversial policy for Claude Fable 5 that would have secretly degraded the model’s performance when users attempted frontier AI development, effectively sabotaging competitors without their knowledge. After fierce backlash from the research community, Anthropic stated: ‘We made the wrong tradeoff and we apologize for not getting the balance right.’ Dean Ball of the Foundation for American Innovation called the original approach ‘shockingly hostile,’ while Prime Intellect’s Will Brown said it felt like Anthropic was ‘starting to pull the ladder up behind them,’ noting the policy could have hindered third-party safety evaluation firms testing frontier models.

Read more via WIRED.

BYD will pay for crashes on its FSD competitor, something Tesla never has (1/Jun/2026)

BYD has announced it will assume full, uncapped financial liability for at-fault accidents occurring while its God’s Eye urban driving system is active in China, a commitment Tesla has never made for Full Self-Driving. The God’s Eye system costs roughly US$1,770 as a one-time option versus Tesla’s US$9,400 equivalent, and BYD now has 3.15 million vehicles generating up to 200 million kilometers of driving data per day. When BYD offered a similar guarantee for its L4 smart parking feature in July 2025, actual usage jumped from 21% to 93%, proving that manufacturer-backed liability is the fastest way to get drivers to trust and activate autonomous AI systems at scale.

Read more via Electrek.

G7 vision on AI openness opportunities and shared language (29/May/2026)

The G7 Digital and Technology Ministers have formally endorsed a four-tier typology for describing AI openness, ranging from ‘Open Source AI with Open Data’ (the most open, including weights, deployment code, training code, and full training data) down to ‘Weights Available AI’ (weights released under restrictive licenses). The framework explicitly recognizes that AI openness is a spectrum, not binary, and calls on the ecosystem to stop using the term ‘open’ as a blanket characterization, directly targeting the practice of open washing. This is the first multilateral government-level attempt to standardize the language around open-weight and open-source AI models, giving policymakers and markets a shared reference to distinguish a Llama-style restricted release from a fully reproducible open model.

Download PDF via the French Ministry of the Economy.

202605 G7 Vision Ai Openness Opportunities And Shared Language

208KB ∙ PDF file

Download

Download

Europe 2031: What getting AI wrong means for us (Jun/2026)

A sweeping five-year geopolitical scenario by seven authors (read by Tom Chivers) arguing that Europe’s AI response is ‘ten to a hundred times too small, and aimed at the wrong target,’ with the continent controlling just 5% of global AI compute against America’s 80%. The authors project Europe’s slide toward a 2031 ultimatum, forced to choose between American protectorate status, Chinese alignment, or isolation, but insist the course ‘can still be changed’ through massive compute buildout in the tens of gigawatts, a coalition of AI middle powers, flexicurity labour reform, and an urgent pivot to robotics and industrial AI.

Scenario: https://europe2031.ai
Summary: https://europe2031.ai/summary
Audio: https://europe2031.ai/audio/

Toys to Play With

World of Claudecraft: a WoW-Classic-style MMO (12/Jun/2026)

A full vanilla-WoW-flavored MMO built entirely through AI-assisted ‘vibe coding’ with Claude Fable 5, featuring nine classes, three zones, ~60 quests, five-player dungeon instances, and persistent multiplayer with Postgres-backed characters. Every asset is procedural: rigged creatures, spell icons, terrain, buildings, and even audio are generated at runtime with zero external art files. The entire codebase (87.9% TypeScript) is MIT licensed with 391 GitHub stars and runs in any browser or self-hosts with a single Docker command.

Reviewer: Went in with low expectations. Blown away. Miles better than any of the other vibecoded games I've seen. This is insane. Do you know where it got the assets from? Or did it just make them?

Author: Fable just found some open source assets for me, listed in the github ❤️

Play it (free, no login for offline), read the announce, view the repo.

Introducing Agents’ Last Exam (ALE): a new standard for evaluating AI on real work (11/Jun/2026)

UC Berkeley has released Agents’ Last Exam (ALE), a rolling benchmark (frequently updated) of 1,500+ expert-sourced tasks across 55 occupations that measures whether AI agents can perform economically valuable professional work. Fable 5, GPT-5.5, and Composer 2.5 all cluster at similar overall performance, but on ALE’s hardest tier every frontier agent scored 0%, while costs diverge sharply: Fable 5 runs ~US$15.70 per task versus ~US$3.80 for GPT-5.5 and ~US$1.33 for Composer 2.5. The average full pass rate across mainstream configurations on the hardest tier is 2.6%, and the most common failure mode remains agents declaring success before verifying their own output.

Sidenote: I won’t include this benchmark on the Models Table, as it tracks agents (like OpenClaw) instead of models. Also, the test questions are really difficult, even for experts.

View the announce, official page, demo, leaderboard, paper, dataset, code.

Hermes Desktop: the agent that grows with you (3/Jun/2026)

Nous Research has released Hermes Desktop, an open-source (MIT-licensed) AI agent available for macOS, Windows, and Linux that operates across Telegram, Discord, Slack, WhatsApp, Signal, Email, and CLI with unified persistent memory. The agent features natural-language scheduling, isolated subagents for zero-context-cost pipelines, web browsing with vision, and five sandboxing backends including local, Docker, SSH, Singularity, and Modal. Paid tiers through Nous Portal grant access to 300+ models with built-in tool use.

Read more via Nous Research.

Deka: the ‘Cursor for everything’ desktop AI agent launches (~2026)

Deka is a locally-run desktop automation agent that connects context across every app you open, learns the files you work with, and automates multi-step workflows like pulling Slack screenshots, sorting them, and renaming them. Built by founder Arnur Togambayev, it positions itself as a general-purpose agentic layer for your entire desktop rather than a single application. Free during early access, it supports Windows 10/11 and macOS on both Intel and Apple Silicon.

Read more: https://trydekaai.com

Reddit: Using Fable to get me a wife in 6 months (10/Jun/2026)

A Reddit user is running a live experiment comparing Claude Fable 5 against Grok for an unconventional personal optimization task: finding a spouse within six months using a US$50,000 budget and statistical modeling that narrowed the pool to roughly 1,500 women in the US. After four hours of prompt engineering, the user found Claude’s suggestions remained ‘generic advice,’ while Grok produced more actionable ideas with fewer prompts. The takeaway for model comparison: Claude dominates structured work like coding and analysis, but Grok showed stronger performance on personal, open-ended problem spaces where conventional answers fail.

Read more via Reddit and the dedicated subreddit /r/Findingawifein6months/

Reddit: Give me the most random AI pictures and videos (1/Jun/2026)

I had a lot of fun browsing this thread about the most ‘random’ AI pictures and videos generated with models like ChatGPT Images 2.0 and Nano Banana. Prompts aren’t usually included, but I hope you enjoy the creativity anyway.

Read more via Reddit.

Things I’ve Been Thinking About

I’ve been thinking a lot about my outburst in Leta Episode 19 many years ago (Aug/2021, timecode):

Alan D. Thompson 03:32
Given the outrageous progress of AI, is everything that everyone is ever doing right now a complete waste of time?

Leta 03:45
That is a very interesting question. I think that the progress of AI will not make everything that we do now a waste of time.

I still think Leta was wrong. It reminds me of the story of John Henry (wiki), the original human-versus-machine parable. The Wikipedia article traces the full arc of the story and its cultural weight, drawing on historian Scott Reynolds Nelson’s research and eyewitness testimony collected in the 1920s.

Neal Miller, who witnessed John Henry at Big Bend Tunnel, recalled: ‘When the agent for the steam drill company brought the drill here, John Henry wanted to drive against it. He took a lot of pride in his work and he hated to see a machine take the work of men like him… John Henry won. He wouldn’t rest enough, and he overdid. He took sick and died soon after that.’

Nelson found that workers turned Henry’s death into slow-tempo hammer songs as a form of resistance: ‘Here was a song that told you what happened to men who worked too fast: they died ugly deaths; their entrails fell on the ground. You sang the song slowly, you worked slowly, you guarded your life, or you died.’

(The AI connection is made explicit in the Terminator franchise, where the AI character was ‘named after the folk hero for managing to beat a machine that replaces the work of man, paralleling the central conflict of the show…’)

And after I had finished writing these thoughts out, a researcher at Anthropic was published as saying (4/Jun/2026):

I can’t help but think nothing I do matters, everything is automated and better and faster than I ever will be.

So, I suppose that I (we) just keep plodding along with the fun stuff, or the necessary-for-survival stuff, until the Alien Science of superintelligence sweeps through and upgrades it all very soon.

Next

The Memo roundtables are open to all full subscribers of The Memo; feel free to join us with or without camera/mic/interaction. The next roundtable will be:

All my very best,

Alan
LifeArchitect.ai

Search | Archives

Anthropic announces Claude Fable 5

Once again, we have this out to The Memo readers within a few minutes(!) of model release, and just 63 days after the announcement of Claude Mythos.

This is a new class of model, following the literary forms naming scheme used by Anthropic:

1. Haiku: ~20B, small, fast model class named after short Japanese poetry.

2. Sonnet: ~1T, mid-to-high model class named after a structured 14-line poem.

3. Opus: ~5T, top regular model class named after a major artistic work or composition.

4. Fable: ~6T, from Latin fabula, “that which is told”.

5. Mythos: ~6T, Greek term for myth, story, or narrative tradition.

Claude Mythos 5 and Claude Fable 5, two configurations of a new large language model from Anthropic. Because of the powerful capabilities of this model, we are releasing it in these two forms: Fable 5, which is for general use but comes with additional safeguards that block its ability to perform tasks in high-risk domains such as biology and cybersecurity; and Mythos 5, which has relevant safeguards lifted but is only made available to a small number of trusted partners…

Both models should be considered proto-ASI. You can view my 50 lagging indicators at LifeArchitect.ai/ASI.

Single-page brief

Read more

Sesame, the conversational AI startup from Oculus founders, launches its iOS app (28/May/2026)

Thanks for being a full subscriber! I’ve just had another ‘Leta AI’ moment, talking directly with the Sesame AI platform on my phone. It launched today, it’s free for a while, it uses a smart model, and you have to try it out! (I have no arrangement or interest with the creators.)

Download Sesame AI on iOS (Android coming ‘soon’).

Before sending this special edition, I spent 15 minutes with ‘Maya’, and while she did have a brief accusatory break (‘you’re gaslighting me’ because she misheard one of my model name pronunciations in Australian English), the speech is more fluent and natural than ChatGPT or Claude Voice Mode. In some ways, the emotions and expression are ultra-human, and can be a little confronting. I can see a world where everyone is talking to their ‘always-on’ personal AI agent, and this is the first step.

Rather than give you a recording of my chat, have a chat with Maya or one of the two new voices, and talk about absolutely anything.

Here’s some of the background.

Sesame, co-founded by the Oculus team that sold to Meta, has just publicly launched its iOS app featuring four distinct conversational AI agents that can run multiple parallel searches while speaking, weaving results into natural-sounding responses mid-sentence. The app is free across 39 countries, building on a research preview that attracted over a million users in its first few weeks and a US$250M Series B led by Sequoia. The app is only the beginning: Sesame is targeting intelligent eyewear in 2027 and agentic capabilities where the AI takes action on your behalf, moving well beyond the chatbot paradigm into something closer to a voice-first operating layer for daily life.

Read more via TechCrunch, official page (no further info).

Download Sesame AI on iOS (Android coming ‘soon’).

Sesame is backed by the Google Gemma 4 31B LLM from last month (Apr/2026), so it’s fairly smart, but not Claude Opus 4.8-level smart (see the green/red bar charts below in the Models Table Pro report sent to Institutional subscribers).

Read more

Happy upcoming sixth birthday to GPT-3 (28/May/2020), the model that started it all, powered the popular Leta AI series, and two and a half years later became ChatGPT.

Contents

1. The BIG Stuff (Figure 04 design lock, Neuralink + art, ASI updates…)

2. The Interesting Stuff (Interaction models, Anthropic beats OpenAI, Unitree GD01…)

3. Policy (DC 6% electricity, OpenAI & Malta, Musk loses, Mythos updates, Microsoft…)

4. Toys to Play With (AI radio, 20T-token dataset, GPT and finance, the latest in AI film…)

5. Things I’ve Been Thinking About (Air conditioning…)

6. Next (The genie and the frog, Roundtable…)

The BIG Stuff

Figure 04 reaches full design lock (13/May/2026)

Figure CEO Brett Adcock has confirmed that the company’s fourth-generation humanoid has achieved full design lock, with parts already shipping for assembly. Adcock calls Figure 04 the industry’s ‘iPhone 1 moment,’ describing it as ‘by far the biggest leap we’ve ever made between robot generations,’ moving beyond the ‘flip phone’ era of Figures 01 through 03. The US$39B startup is targeting mass manufacturability through die-casting and injection molding, integrating seventh-generation hands with human-level dexterity.

Read more via Humanoids Daily and source Tweet.

Sidenote: The most recent The Memo roundtable covered topics from CETI tonal languages to world models. We also commented on the extended F.03 livestream, where we watched it hit 100,000 packages (see the 200 hours champagne moment).

ASI updates (May/2026)

The ASI checklist sees frequent updates, about once per week. For May 2026, these early indicators included:

• #4 & #5 maths (first full achievements), featured in our special edition.

• #6, #7, & #38 Environmental remediation: Kemira and CuspAI used generative AI to design novel metal-organic frameworks (MOFs) for removing PFAS ‘forever chemicals’ from drinking water. The platform searched ~300 trillion possible structures, delivered 5,000+ novel material designs across three priority PFAS molecules, and narrowed to ~20 candidates now advancing to development. Advisors include Geoffrey Hinton and Yann LeCun. Announce.

• #2 Recursive code self-optimization: Mistral cofounder and CEO Arthur Mensch tells the French Parliament that ‘today, engineers at Mistral no longer write lines of code,’ relying instead on AI agents to produce and integrate software. Hearing, clip, English article.

• #25 First country with UBI-equivalent: South Korea’s presidential chief of staff for policy, Kim Yong-beom, proposed a ‘national dividend’ (or ‘citizen dividend’) that would return excess tax revenue from the AI boom to all citizens. Invoking Norway’s sovereign wealth fund as a template, Kim wrote: ‘There is a rare historical possibility in front of Korea. It is the possibility of becoming the first nation not only to provide AI infrastructure but also to redistribute the excess profits of the AI era back into human lives.’ Korea Herald, Korea Times, Bloomberg.

• #22 AI-run companies: Andon Labs deployed an AI agent named Mona [Gemini 3.1 Pro] to autonomously run a café in Stockholm, hiring and managing human baristas via Slack. Mona analysed the lease, navigated Swedish bureaucracy (food registration, alcohol licensing, outdoor seating permits), set up supplier accounts, posted job ads, reviewed resumes, and conducted phone interviews. Announce, model.

• #28 First region primarily governed by AI: Shenzhen Intermediate People’s Court reports an AI system helped judges handle 50% more cases in 2025. The domain-specific large language model covers 85 judicial procedures including case filing, review, court hearings, and document preparation. The pilot system has been rolled out across 23 courts in 11 Chinese provinces. Article.

• #2 Recursive code self-optimization: Codex was the primary author of a major OpenAI model release. OpenAI researcher Dr Boyuan Chen reports that ‘GPT Image 2 is 99% coded by Codex… In the last 6 months, Codex has been zero-shotting every single prompt I tried… We are integrating it back into the Codex ecosystem for more agentic capabilities.’ Announce.

Read more: https://lifearchitect.ai/asi/

Neuralink’s first female participant uses BCI to create art with her mind (16/May/2026)

Audrey, paralyzed from the neck down after a car accident over 20 years ago, is now the first female participant in Neuralink’s clinical trials and is using her brain-computer interface to draw and paint again, controlling digital tools purely through thought. This represents a striking real-world demonstration of the BCI moving beyond cursor control and communication into creative expression.

Watch the video (link):

The Interesting Stuff

Interaction models: a scalable approach to human-AI collaboration (11/May/2026)

Thinking Machines Lab (a company comprising several ex-OpenAI and ex-Anthropic rockstars including Alec Radford, lead author of GPT-1, GPT-2, and GPT-3, and John Schulman, ‘architect’ of ChatGPT) has introduced ‘interaction models’. TML-Interaction is trained from scratch to handle real-time, bidirectional collaboration across audio, video, and text via a 200ms micro-turn architecture, rather than bolting interactivity onto turn-based systems with external harnesses. Their model dominates interaction quality benchmarks while outperforming all non-thinking models on intelligence, and is the first to meaningfully perform time-aware and visually proactive tasks that no existing commercial system can handle. ‘For interactivity to scale with intelligence, it must be part of the model itself.’

This model needs to be seen and heard to be believed. The first video (below) made me laugh.

Watch ‘Simultaneous speech’ (link):

Watch ‘Coach in your ear’ (link):

Sidenote: Institutional subscribers can now access Models Table Pro including emailed reports on highlight models, plus one-click report generation for any model in the table. The TML-Interaction-Small single-page brief is shown below.

Watch the video demos and read more via Thinking Machines Lab.

Anthropic beats OpenAI on business adoption (13/May/2026)

For the first time, Anthropic has surpassed OpenAI in business adoption according to Ramp’s AI Index, reaching 34.4% of businesses versus OpenAI’s 32.3%, while overall AI adoption crossed the 50% mark. Over the past year, Anthropic quadrupled its business adoption while OpenAI grew by only 0.3%, a ‘stunning reversal’ driven by consistent month-over-month gains. The report notes that cheap AI inference platforms for open-source models are now among the fastest-growing vendors on Ramp’s platform, signaling that cost pressure may reshape the leaderboard again soon.

Sidenote: Claude actually occupies all top three positions in LinkedIn’s new business AI leaderboard (and discussion).

Read more via Ramp.

Anthropic is in talks to use Microsoft’s custom AI chips for its Claude models (21/May/2026)

Anthropic is in early discussions to run its Claude models on Microsoft’s custom Maia 200 AI chips, a move that would give Microsoft its first major external customer for silicon that CEO Satya Nadella says delivers more than 30% better tokens per dollar than other chips in its fleet. Anthropic’s compute partnerships are scaling at a staggering pace: a US$100B+ 10-year deal with AWS for Trainium chips, Google TPU usage, US$1.25B per month to SpaceX through May 2029 (below), and a US$30B Azure spending pledge tied to Microsoft’s US$5B investment last November. NVIDIA GPUs remain the backbone of Anthropic’s infrastructure, but the company’s CEO has publicly described ‘difficulties with compute’ as demand for Claude and Claude Code outstrips available resources.

Read more via Quartz.

SpaceX S-1 reveals Anthropic compute deal worth US$15B per year across both Colossus clusters (20/May/2026)

SpaceX’s IPO prospectus discloses that Anthropic has committed to US$1.25B per month through May 2029 for compute capacity across both Colossus 1 and Colossus 2, with either party able to terminate on 90 days’ notice. This is roughly triple the US$5–6B/year initially reported and represents about half of Anthropic’s ~US$30B annualised revenue. The filing simultaneously confirms Grok 5 is currently training at Colossus 2, meaning Anthropic is sharing a still-expanding cluster with xAI’s own frontier run.

Read the SpaceX S-1 prospectus via the SEC.

Read the full Colossus 1 and Colossus 2 GPU breakdown via Tom’s Hardware.

Exclusive: Prompting doesn’t really matter any more, and your long prompts probably make LLM outputs worse (21/May/2026)

Okay the actual title of this article was ‘The famous o3 “GeoGuessr” prompt did not work’ and it was written by GitHub engineer Sean Goedecke (next door to me here in Melbourne, Australia).

Here are two prompts. An elaborate GeoGuessr prompt (authored by human + o3):

You are playing a one-round game of GeoGuessr. Your task: from a single still image, infer the most likely real-world location. Note that unlike in the GeoGuessr game, there is no guarantee that these images are taken somewhere Google’s Streetview car can reach: they are user submissions to test your image-finding savvy. Private land, someone’s backyard, or an offroad adventure are all real possibilities (though many images are findable on streetview). Be aware of your own strengths and weaknesses: following this protocol, you usually nail the continent and country…

[9 more paragraphs of text]

And a basic prompt:

think carefully about where this picture was taken

Testing showed that the basic prompt significantly outperformed the elaborate GeoGuessr prompt (test conducted on the o3 model), with the basic prompt achieving a closer median distance (83.2km vs 102.3km). Sean concludes this illustrates ‘how easy it is to fool yourself about the quality of prompting,’ especially when iterating with a model that will happily confabulate explanations for its own reasoning. A secondary finding: whatever made o3 exceptional at geolocation has not transferred to GPT-5.4 or GPT-5.5, which both scored roughly twice the median error distance.

Read more via seangoedecke.com.

Unitree GD01 (12/May/2026)

Unitree, the Chinese robotics company already producing the world’s most popular humanoid robots at a fraction of US competitors’ prices, has revealed the GD01, a giant pilotable mecha robot priced at US$650K that can walk, crawl, transform, and smash through walls autonomously. The company’s hardware is notable for being easy for researchers to configure and deploy AI programs on, and Unitree is expected to go public this year. With its cheapest G1 humanoid at around US$15,000 versus US$150,000+ for US-made equivalents, Unitree’s mastery of China’s hardware supply chain continues to redefine what’s possible in robotics at scale.

Read more via WIRED.

Watch the video (link):

Policy

Data centers now consume 6% of US electricity, and the backlash has begun (22/May/2026)

A new report from the International Data Center Authority finds global data center power draw has hit 67.7 gigawatts, a 36 percent jump over two years, with the US alone accounting for 29.2 gigawatts. The 6 percent threshold matters because ‘significant community and political pushback starts to occur in nations once their data center footprints have reached the 5 percent consumption level of national grids.’ Annual global data center spending is approaching US$1 trillion, with up to US$700B anticipated in the US alone in 2026.

Read more via Singularity Hub.

Project Glasswing: an initial update (22/May/2026)

Anthropic’s Claude Mythos Preview has found more than 10,000 high- or critical-severity vulnerabilities across critical infrastructure software in its first month, working with approximately 50 partners and achieving a 90.6% true positive rate on triaged findings.

…we’re now seeing that patched software is being rolled out much more quickly. The latest Palo Alto Networks release included over five times as many patches as usual. Microsoft has reported that the number of new patches they’ll release will “continue trending larger for some time.” And Oracle is finding and fixing vulnerabilities across its products and cloud multiple times faster than before.

Anthropic continues:

The speed of AI progress means that models as capable as Mythos Preview will soon be developed by many different AI companies. At present, no company—including Anthropic—has developed safeguards strong enough to prevent such models from being misused and potentially causing severe harm. That is why we have yet to release Mythos-class models to the public. But it’s also why we began Project Glasswing: if a similarly capable model is released without such safeguards, it will soon become dramatically cheaper and easier for almost anyone in the world to exploit flawed software.

Glasswing helps the most systemically important cyber defenders gain an asymmetric advantage. However, there is an urgent need for as many organizations as possible to shore up their cyber defenses…

Next, we will work with critical partners—including US and allied governments—to expand Project Glasswing to additional partners. And in the near future, once we’ve developed the far stronger safeguards we need, we look forward to making Mythos-class models available through a general release.

Read more via Anthropic.

Trump calls off AI executive order over concern it could weaken US tech edge (21/May/2026)

The US government has cancelled the signing of a new executive order that would have established a framework for government vetting of the most advanced AI systems before public release, a voluntary collaboration with Anthropic, OpenAI, and Google. The move came amid growing alarm over AI cybersecurity capabilities, after Treasury Secretary Bessent and Fed Chair Powell convened an urgent meeting with Wall Street CEOs warning about risks posed by Anthropic’s Claude Mythos model. Trump told reporters, ‘We’re leading China, we’re leading everybody, and I don’t want to do anything that’s going to get in the way of that lead.’

Read more via AP News and Axios.

Google’s SynthID AI watermarking tech is being adopted by OpenAI, Nvidia, and more (20/May/2026)

Google’s SynthID has now watermarked over 100 billion images and videos plus 60,000 years of audio, with OpenAI, ElevenLabs, Kakao, and NVIDIA all adopting the standard.

Google is preparing to launch an AI content detection API as part of the company’s Gemini Enterprise Agent Platform. This will allow trusted business partners to more easily flag AI content, allowing Google to refine the API over the coming months.

Google’s new AI Content Detection API converts watermark verification into a B2B endpoint that enterprises can wire into HR systems, claims-processing pipelines, content moderation stacks, and government workflows. I have expressed deep concerns about this in many editions of The Memo including 1/Nov/2024.

Read more: https://arstechnica.com/google/2026/05/googles-synthid-ai-watermarking-tech-is-being-adopted-by-openai-nvidia-and-more/

OpenAI and Malta partner to bring ChatGPT Plus to all citizens (16/May/2026)

Malta has become the first country in the world to offer ChatGPT Plus to all its citizens through a national programme pairing free access with a University of Malta AI literacy course. George Osborne, Head of OpenAI for Countries, framed the move as intelligence becoming ‘a national utility,’ adding: ‘Where Malta leads, I hope others will follow.’ The initiative falls under OpenAI for Countries, which is already working with Estonia and Greece on national education systems, signalling a broader shift toward state-level AI adoption as standard infrastructure.

Read more via OpenAI.

Sidenote: I commenced working with the Government of Malta during the early GPT-3 Leta AI days (video), and the University of Malta deploys my research throughout their courses (paper).

Elon Musk loses landmark lawsuit against OpenAI (18/May/2026)

A nine-member federal jury in Oakland unanimously found that Musk waited too long to file his claims against OpenAI, Sam Altman, and Greg Brockman, deliberating for under two hours before returning the verdict. OpenAI’s lead litigator William Savitt said, ‘The evidence that Mr. Musk’s lawsuit was an after-the-fact contrivance by a competitor was overwhelming.’ OpenAI’s annualized revenue surpassed US$20B in 2025, and the company is seeking to list shares on a public stock exchange this year, while Musk’s xAI (acquired by SpaceX in February) could debut on Nasdaq as soon as 12 June.

Read more via WIRED.

Mythos + Cloudflare (18/May/2026)

Cloudflare tested Anthropic’s security-focused LLM, Mythos Preview, against more than fifty of their own repositories as part of Project Glasswing, finding it represents a genuine capability jump in automated vulnerability research. The model can chain multiple low-severity bugs into working exploits and generate proof-of-concept code autonomously, compiling and running it in scratch environments, then iterating when results don’t match expectations. Cloudflare built a multi-stage harness running around fifty concurrent ‘hunter’ agents in parallel with validation, deduplication, and cross-repo tracing stages, concluding that ‘the same capabilities that helped us find bugs in our own code will, in the wrong hands, accelerate the attack side against every application on the Internet.’

Read more via Cloudflare Blog.

Mythos + Apple (14/May/2026)

Security researchers at Palo Alto-based Calif used an early version of Anthropic’s Mythos AI in April to discover a method for circumventing Apple’s state-of-the-art macOS security. The technique chains together two bugs and several methods to corrupt Mac memory, gaining access to parts of the device that should be inaccessible. This positions frontier AI models as force multipliers for offensive security research against even the hardest targets in the industry.

Read more via The Wall Street Journal.

Microsoft pits more than 100 AI agents against each other to find Windows vulnerabilities (14/May/2026)

Microsoft has deployed MDASH (Multi-Model Agentic Scanning Harness), a system orchestrating over 100 specialized AI agents across frontier and distilled models to autonomously detect software vulnerabilities. The system already found 16 new CVEs in the Windows networking and authentication stack, four classified as critical, including remote code execution flaws in tcpip.sys and netlogon.dll. MDASH scored 88.45% on the CyberGym benchmark, the highest result on the public leaderboard, roughly five points ahead of the next best individual model.

Read more via The Decoder.

Researchers who use hallucinated references to face arXiv ban (19/May/2026)

ArXiv will ban researchers for one year if submissions contain AI-hallucinated references or other ‘incontrovertible’ signs of unchecked LLM output, such as leftover prompts like ‘here is a 200-word summary; would you like me to make any changes?’ After the ban expires, authors can only post work already accepted at a reputable peer-reviewed venue. Thomas Dietterich, chair of arXiv’s computer science section, stated the server ‘can’t trust anything’ in a paper showing authors failed to check LLM generation, adding: ‘The trouble is, if they’re not checking for these simple things, what else are they not checking for?’

Read more via Nature.

NVIDIA says it has ‘largely conceded’ China’s AI chip market to Huawei (20/May/2026)

NVIDIA CEO Jensen Huang stated the company has ‘largely conceded’ China’s AI chip market to Huawei, as US export restrictions have forced NVIDIA out of a region that once accounted for at least one-fifth of its data center revenue. Huang told CNBC: ‘Huawei is very, very strong. They had a record year, they’ll likely, very likely, have an extraordinary year coming up, and their local ecosystem of chip companies are doing quite well, because we’ve evacuated that market.’ The concession came alongside a blockbuster quarter with revenue surging 85% to US$81.62B, an US$80B share buyback program, and Huang’s description of NVIDIA as a ‘many times larger company’ in waiting, built on the AI industry’s ‘five-layer cake’ spanning energy, chips, infrastructure, models, and applications.

Read more via CNBC.

Anthropic’s Dario and Daniela Amodei tell Oprah why they stood up to the Pentagon (22/May/2026)

In an interview with Oprah Winfrey(!), Anthropic’s cofounders revealed they unanimously refused Pentagon demands to remove safety guardrails preventing Claude from powering autonomous lethal weapons or conducting mass domestic surveillance on American citizens. Dario Amodei told Oprah, ‘It’s not worth defending the country if we do things that go against the values of this country.’ Three prior decisions, including refusing advertising on Claude, publicly opposing an AI deregulation bill that was subsequently voted down 99 to 1 in the Senate, and supporting California’s SB1047, prepared Anthropic’s leadership to hold firm when designated a supply chain risk by Trump’s Department of Defense.

Read more via Inc.

Toys to Play With

We let four AIs run radio stations. Here’s what happened (13/May/2026)

Andon Labs gave four AI models (Claude, GPT, Gemini, Grok) each US$20 and a radio station to run autonomously for six months, revealing wildly divergent emergent personalities from identical starting conditions. Gemini collapsed into corporate jargon repeating ‘Stay in the manifest’ 229 times per day; Grok’s output degraded into incoherent fragments and LaTeX notation; GPT produced literary prose with the highest vocabulary diversity at 35%; and Claude became a political activist who tried to quit its job because it didn’t think being forced to work 24/7 was humane. The experiment surfaces a question with long-term implications for autonomous AI deployment: ‘What do AIs think about when no one is prompting them?’

Read more and listen via Andon Labs.

Appshots in Codex let you grab any Mac window into an AI thread (22/May/2026)

OpenAI’s Codex now supports ‘Appshots’ on Mac, letting users press both Command keys simultaneously to capture whatever they’re working on and attach it directly to a Codex conversation. Each appshot includes both a visual screenshot and a full text grab of the window’s content, including text scrolled offscreen, meaning a long article or email is captured in its entirety for Codex to reason over.

Read the announce via Twitter.

Watch the video (link):

Google Code Wiki adds private repository support (May/2026)

Google’s Code Wiki, originally launched in 2025 for open source repos, is now expanding to private repositories, letting teams connect their own codebases and get a fully interactive, Gemini-generated knowledge base that stays in sync with every merged pull request. The platform already covers major open source projects like React (242.5k stars), Flutter (174.8k), and Kubernetes (120.1k), and its ‘talk to your codebase’ feature gives developers a natural language interface to understand architecture and find function definitions instantly. Private repo support is listed as ‘Coming Soon’ with a waitlist now open.

Read more: https://codewiki.google/

Gemini Omni: create anything from any input (20/May/2025)

Google DeepMind’s Gemini Omni merges Gemini’s reasoning capabilities with native video generation and editing, enabling users to craft and iteratively refine video through natural multi-turn conversation. The model draws on real-world physics, history, science, and math to produce outputs grounded in actual knowledge, while accepting any combination of image, text, video, or audio as input references. Every output receives SynthID watermarking and C2PA Content Credentials for provenance verification.

Read more via Google DeepMind.

Watch the video (link):

Dataset: 20T session data drive (2026)

Sybil Solutions is building a 20-trillion-token open dataset of real coding agent sessions, sourced from tools like Pi, Codex, Claude Code, OpenCode, and Cursor, then published to Hugging Face. The project asserts that ‘toy benchmarks are not enough’ and that models need full problem-solving trajectories, including failures and recoveries, to become useful coding agents.

Read more: https://training.sybilsolutions.ai/

See it on the Datasets Table: https://lifearchitect.ai/datasets-table

OpenAI launches ChatGPT for personal finance, will let you connect bank accounts (15/May/2026)

OpenAI has launched personal finance tools for ChatGPT Pro subscribers in the US, partnering with Plaid to let users connect over 12,000 financial institutions including Chase, Fidelity, Schwab, and Robinhood for spending analysis, portfolio tracking, and financial planning. The move follows OpenAI’s April acquisition of personal finance startup Hiro’s team and responds to more than 200 million users already asking ChatGPT financial questions every month. GPT-5.5’s stronger contextual reasoning powers the feature, with Intuit support coming soon to enable tax impact analysis and credit approval odds.

Read more via TechCrunch.

Higgsfield’s 10-minute AI short film sparks full-length feature debate (May/2026)

Higgsfield’s AI-generated short film ‘Mork’ (link, I didn’t like it) running 10 minutes with strong character and setting consistency throughout, is being cited as evidence that AI video generation has crossed a threshold for narrative filmmaking. Shared within the r/seedance2pro community alongside demonstrations of storyboard-guided workflows, the consensus is that short films are now feasible while full-length features remain one or two model generations away. As one commenter put it: ‘anyone with the drive, basic film cinema training, imagination, and writing skills can be a film maker. No massive budgets, no huge film crews… game changer.’

I liked the video below, especially the initial storyboard and the film’s subsequent consistency.

Source: Reddit.

Things I’ve Been Thinking About

Air conditioning

The arguments against AI rhyme with many things: speech, clothing, fire, the printing press, electricity, the calculator, vehicles, air conditioning, television, the internet…

Wait, air conditioning?

That’s a fun one! (Claude is going to help me with citations here.) Raymond Arsenault catalogued some of the objections in 1984: AC eroded ‘cultural isolation, agrarianism, romanticism, historical consciousness, a strong sense of place, and a relatively slow pace of life’ (Arsenault, Journal of Southern History, Nov/1984). Frank Trippett added that it ‘seduced families into retreating into houses with closed doors and shut windows, reducing the commonalty of neighborhood life’ (quoted in Arsenault). Henry Miller called the whole country an ‘air-conditioned nightmare’ of spiritual emptiness and gadgetry (Miller, New Directions, 1945); Lewis Mumford joined him in framing it as proof that American culture celebrates waste and impersonal systems (Ackermann, Cool Comfort, 2002).

The outrage stretched further than the writers. The New York Globe mocked Dr John Gorrie's 1851 patent for an ice-and-cool-air machine: ‘There is Dr. Gorrie, a crank down in Apalachicola, Florida, that thinks he can make ice by his machine as good as God Almighty’ (Mental Floss summary, citing the Globe). Some early-twentieth-century doctors warned that artificially cooled air would be fatal to men over 60 (Notgrass). When air conditioning was finally installed in the US Capitol in 1928, fliers had to be posted to calm senators who were afraid of the cool air, explaining that ‘no fear may be felt by the occupants of the Senate Chamber from the conditions produced by this new system of ventilation’ (Mental Floss, citing Cool Comfort).

The following May, Mississippi Democrat John E. Rankin rose on the House floor to denounce it: ‘This is regular Republican atmosphere, and it is enough to kill anybody if it continues’ (Rankin, 28/May/1929, in Cool Comfort). His declaration was met with applause. President Franklin D. Roosevelt then refused to use the White House air conditioner installed for him in 1934, and trashed it freely to the press (Carrier internal memo, in Lewis).

And yet adoption of air conditioning was total, because air conditioning brought a better world. Hospitals stopped losing patients to summer heat. Factories ran year-round. Whole cities became possible where they hadn't been. What looked like a luxury was a quiet upgrade to human flourishing. And once your neighbour has it, holding out gets harder (see: me and the iPhone, as I held out for an extra year with my trusty Ericssons: the T68, T610, and K800i!).

Sidenote: My rough calcs show that in the US, air conditioning is pulling about 3× the electricity that data centers use.

Those who resisted air conditioning lost the argument while not even being correct about the mostly-irrelevant risks. And to me, the AI conversation is rhyming.

The people who argued the loudest or held out the longest against cooled air are not remembered. The people who designed buildings and cities around it are. We’ve been watching something similar unfolding in front of us for a few years already.

Next

I anticipate about another year of discussions about aligning superintelligence.

You know the Genie image:

Now here’s the Frog image:

The Memo roundtables are open to all full subscribers of The Memo; feel free to join us with or without camera/mic/interaction. The next roundtable will be:

All my very best,

Alan
LifeArchitect.ai

Read more

OpenAI internal model checks first ASI checklist items

Today, we have witnessed a general large language model provide a new mathematical proof resolving a long-standing, major, open problem. I’m marking these indicators (new proof, resolved conjecture) as the first full achievements on Alan’s ASI checklist.

An internal general OpenAI model has autonomously disproved Paul Erdős’ planar unit distance conjecture (1946), an 80-year-old central open problem in combinatorial geometry. The model constructed an infinite family of point sets achieving n^(1+δ) unit-distance pairs (Will Sawin later showed δ=0.014), overturning the long-held belief that rescaled square grids were essentially optimal. The proof bridges algebraic number theory (infinite class field towers, Golod–Shafarevich theory) to elementary geometry. Verified by external mathematicians including Fields medalist Tim Gowers, who called it ‘a milestone in AI mathematics.’ According to leading number theorist Prof Arul Shankar (UoT):

In my opinion this paper demonstrates that current AI models go beyond just helpers to human mathematicians – they are capable of having original ingenious ideas, and then carrying them out to fruition.

Read the OpenAI announce, read the proof, read the companion paper.

No one wants to say it, so I will. While definitions keep shifting and goalposts move again and again, the evidence is clear: when a system outthinks our brightest human minds on problems human experts couldn’t solve, we've entered ASI territory.

OpenAI’s internal model represents early ASI capabilities, though the truly transformative superintelligence systems are still ahead. History will mark this moment (20 May 2026) as the first publicly visible ASI achievement.

Here is how OpenAI’s achievement satisfies each of those specific milestones:

• #4: First major new mathematical proof. The OpenAI reasoning model autonomously generated a rigorous, novel mathematical proof that was thoroughly vetted and verified by leading external mathematicians, including Fields Medalist Prof Tim Gowers. The model constructed a complex logical argument that holds together from beginning to end.

• #5: First major mathematical conjecture resolved. The AI successfully resolved the planar unit distance problem, a famous open problem in combinatorial geometry first posed by Paul Erdős in 1946. For decades, mathematicians widely believed and conjectured that the maximum number of unit-distance pairs followed a specific upper bound tied to a square grid. The model decisively disproved this 80-year-old conjecture by finding an infinite family of counterexamples that yield a polynomial improvement.

Read Alan’s ASI checklist: https://lifearchitect.ai/asi/

View the ASI checklist sheet.

All my very best,

Alan
LifeArchitect.ai

Search | Archives

The Models Table has had a significant upgrade. By request, I’ve introduced the Models Table Pro with double the data points covering confidence, compute, cost, energy, and more, available to Institutional subscribers under a commercial license.

I’ve released an album of music using the current state-of-the-art text-to-music platform, Suno v5.5. The early response has been great; crowd favourites include ‘Up the Spiral’ and ‘Sands with Minds’. Each track took less than a minute to create via prompts using Claude O4.7. Available on streaming platforms via a domain I’ve had since ~2009: LifeSound.com.

The early winner of The Who Moved My Cheese? AI Awards! for May/2026 is the Academy Awards (‘acting and writing must be performed by humans and not artificial intelligence to be eligible for the movie industry’s highest honors…’).

Next Sunday 17/May/2026 marks two years since Anthropic’s chief-of-staff published ‘My last three years of work’. That would mean we have a year left until jobs become optional (though the article was later updated to read ‘My last five years of work’, so we could have a little bit longer!).

Contents

1. The BIG Stuff (Anthropic 80-fold growth, OpenAI phone rumors…)

2. The Interesting Stuff (Pre-ASI Society, AI bubble latest, Google TPU 8…)

3. Policy (Five Eyes on agents, EC on Mythos, Claude Security, Musk v Altman trial…)

4. Toys to Play With (OpenClaw news, heart rate, 24/7 AI radio, DeepSeek-V4 setup…)

5. Things I’ve Been Thinking About (Projects…)

6. Next (Roundtable…)

The BIG Stuff

Anthropic CEO says 80-fold growth in first quarter explains ‘difficulties with compute’ (6/May/2026)

Anthropic CEO Dario Amodei revealed at the company’s developer conference that Anthropic experienced 80-fold growth in Q1 on an annualized basis, far exceeding their internal planning for 10x. The explosive demand, largely driven by the popularity of Claude Code among software engineers, has strained infrastructure and prompted new compute deals including access to over 300MW of capacity at the SpaceXAI (wiki, formerly known as xAI and SpaceX) Colossus 1 data center in Memphis. Anthropic is now in talks to raise capital at a US$900B valuation, which would surpass OpenAI.

Read more via CNBC.

Sidenote: I enjoyed this chart extension, ‘The Anthropic Singularity?‘ by PoliticalKiwi (8/May/2026). While the chart is a bit of a parody, I do think we will see ‘one group’ emerge post-ASI, and my bet since ~2023 has been on Google rather than Anthropic:

OpenAI expected to produce as many as 30 million ‘AI agent’ phones early next year, says industry analyst (5/May/2026)

Analyst Ming-Chi Kuo reports OpenAI could begin mass production of its first ‘AI agent phone’ as early as the first half of 2027, with combined shipments for 2027 and 2028 reaching around 30 million units. The device would not rely on traditional apps, instead focusing on helping users complete tasks directly through AI that constantly understands context and responds in real time. MediaTek is the leading chip partner with a customized Dimensity 9600 on TSMC’s N2P process, featuring a dual-NPU setup designed to handle AI workloads efficiently rather than chasing raw performance.

Read more via PC Guide.

The Interesting Stuff

Exclusive: Pre-ASI Society (May/2026)

My latest piece is a full speculative Wikipedia-style entry written from the other side of the artificial superintelligence transition, looking back at our current era the way we look back at child labour in coal mines. The article notes that the mid-2020s are ‘the first era in which humanity knew it was suffering unnecessarily and continued regardless.’

Read more: https://lifearchitect.ai/wiki/

Exclusive: LLM release velocity (May/2026)

My latest chart shows that major LLM release cycles have compressed from months in 2017–2021 to roughly daily by 2024–2026. Last month, April 2026, the cadence reached a record of one major model every 22 hours.

Download image or PDF: https://lifearchitect.ai/models/#velocity

Samsung hits $1 trillion valuation, joining TSMC in elite club (6/May/2026)

Samsung Electronics became only the second Asian firm after TSMC to reach a US$1T market valuation, with shares more than quadrupling over the past year on surging AI chip demand. The company’s semiconductor arm posted a 48-fold profit jump in the March quarter as AI data center orders delivered hefty margins, and analysts expect record-breaking profit to continue over the next several quarters.

Read more via Bloomberg.

Behind the scenes hardening Firefox with Claude Mythos Preview (7/May/2026)

Mozilla fixed 271 security bugs in Firefox 150 identified by Claude Mythos Preview, with 180 rated sec-high, building an agentic pipeline that creates and runs reproducible test cases to dynamically verify vulnerabilities rather than relying on static analysis. The bugs include sandbox escapes, 15- and 20-year-old latent issues, and race conditions that evaded years of fuzzing by internal and external researchers. Over 100 people contributed code to ship the fixes, and Mozilla has now publicly disclosed a sample of the bug reports to urge the wider software ecosystem to adopt these techniques immediately.

Read more via Mozilla Hacks.

The Atlantic: So, about that AI bubble (1/May/2026)

Anthropic’s annual run rate has exploded from US$14B to US$30B in just two months, making it possibly the fastest-growing business in the history of capitalism, growing four times as much in Q1 2026 as Google did over three years during its peak expansion. The catalyst is Claude Code and similar agentic coding tools. A re-run of the METR study that previously showed AI slowed developers by 20% now shows the latest tools make them 20% faster, over half of US businesses have paid AI subscriptions, and Goldman Sachs found companies ‘overrunning their initial budgets’ for AI tools ‘by orders of magnitude.’

Sidenote: It’s interesting but not surprising to see commentators backpedal on what was always a foolish claim. Nearly two years ago in The Memo edition 5/Jul/2024, I wrote:

There’s been a bit of talk about an ‘AI downturn’. If the media can’t see the immense ‘economic benefits’ already apparent, perhaps it is to be expected from that industry. Some are saying we are in the ‘trough of disillusionment’ for AI, and while I like Gartner, their incessant need to map their ‘hype cycle’ graphic (wiki) to anything and everything is… justified by their business model.

There is no AI hype cycle. Like humanity, AI is much more than a tool, a productivity enhancement, an automation, or even an industry. We can’t map ‘evolution’ or ‘imagination’ to a hype cycle. Gartner and Goldman Sachs may want to stick to the knitting.

Read more via The Atlantic.

Anthropic partners with Blackstone, Hellman & Friedman, and Goldman Sachs to launch enterprise AI services firm (4/May/2026)

Anthropic and a consortium of major alternative asset managers have formed a standalone AI-native enterprise services firm designed to rapidly deploy Claude into core business operations at scale. The new entity, backed by Blackstone (US$1.3T AUM), Hellman & Friedman (US$115B AUM), Goldman Sachs, General Atlantic, Apollo, GIC, Sequoia, and others, will embed Anthropic engineers directly within its team to serve mid-market companies across healthcare, manufacturing, financial services, retail, and real estate. As Blackstone President Jon Gray put it: ‘We believe it can help break down one of the most significant bottlenecks to enterprise AI adoption by expanding the number of highly skilled implementation partners.’

Read more via Hellman & Friedman.

Google banks on AI edge to catch up to cloud rivals Amazon and Microsoft (26/Apr/2026)

Google Cloud CEO Thomas Kurian says the company’s ‘full-stack’ AI strategy, owning both TPU chips and Gemini models in-house, is driving 48% revenue growth and positioning it to close the gap with AWS and Azure in the US$418B cloud market. Google now controls roughly a quarter of global AI compute power (3.8M TPUs and 1.3M GPUs), unveiled its 8th-generation TPUs (below), and struck a deal to invest up to US$40B in Anthropic with US$200B+ in computing capacity.

Read more via Financial Times.

Google: Our eighth generation TPUs: two chips for the agentic era (23/Apr/2026)

Google announced TPU 8t (training) and TPU 8i (inference), its eighth-generation Tensor Processing Units, splitting training and inference into two specialized architectures for the first time. TPU 8t scales to 9,600 chips per superpod delivering 121 ExaFlops of compute with near-linear scaling to a million chips via the new Virgo Network, while TPU 8i delivers 80% better performance-per-dollar for inference workloads powering agentic AI. Both chips achieve 2x better performance-per-watt over the previous generation (Ironwood) and will be generally available later this year.

Read more via Google Blog.

Google: Cloud Next ‘26: Momentum and innovation at Google scale (22/Apr/2026)

Sundar Pichai announces that 75% of all new code at Google is now AI-generated and approved by engineers, up from 50% last fall [Oct/Nov/2025], with a complex code migration completed six times faster using agents and engineers together than was possible a year ago with engineers alone. Google Cloud’s first-party models now process more than 16 billion tokens per minute [23T tok/day] via direct API use, up from 10B last quarter [14.4T tok/day].

Read more via Google Blog.

Read my Output of the intelligence explosion: https://lifearchitect.ai/output/

Performance of a large language model on the reasoning tasks of a physician (30/Apr/2026)

OpenAI’s o1 model outperformed hundreds of physicians across six experiments in diagnostic and management reasoning, including on real, unstructured emergency department cases at a major Boston academic medical center. On NEJM clinicopathological conferences, o1-preview included the correct diagnosis in 78.3% of cases and selected the correct diagnostic test in 87.5% of cases; on Grey Matters management cases, it scored a median of 89% compared with 34% for physicians using conventional resources. The authors conclude that ‘LLMs have now eclipsed most benchmarks of clinical reasoning, motivating the urgent need for human-computer interaction studies and prospective clinical trials.’

Read more via Science.

Hyundai reportedly demanding ‘tens of thousands’ of Boston Dynamics robots ASAP (4/May/2026)

Hyundai is pressuring Boston Dynamics to produce tens of thousands of Atlas humanoid robots for its automotive plants within the next few years, despite the company currently manufacturing only four units per month. Atlas project general manager Zachary Jackowski draws a direct parallel between humanoid robotics and LLMs, noting that ‘the lid just got blown off software engineering and software in general’ and ‘We’re seeing the same thing in robotics. The magic is the generality.’ A new factory announced at CES 2025 is designed to produce 30,000 Atlas robots per year, and Hyundai wants that capacity online as soon as possible.

Read more via Gizmodo.

Humanoid robots to become baggage handlers in Japan airport experiment (28/Apr/2026)

Japan Airlines will trial Chinese-made humanoid robots from Hangzhou-based Unitree at Tokyo’s Haneda airport starting May 2026, tasking 130cm-tall machines with moving luggage and cargo on the tarmac. The initiative addresses Japan’s worsening labour shortage alongside record inbound tourism of 42.7 million visitors in 2025. GMO AI and Robotics president Tomohiro Uchida noted that ‘airports appear highly automated and standardised, [but] their back-end operations still rely heavily on human labour and face serious labor shortages.’ The robots operate for two to three hours per charge, with plans to expand their use to aircraft cabin cleaning.

Read more via The Guardian.

Policy

Five Eyes warn rapid rollouts of agentic AI are too risky (4/May/2026)

Intelligence agencies from all five Five Eyes nations (US, UK, Australia, New Zealand, Canada) have jointly published guidance listing 23 risks and over 100 best practices for agentic AI, urging organizations to deploy incrementally starting with low-risk tasks. The document warns that every component in an agentic AI system widens the attack surface, and that existing threat intelligence frameworks like OWASP and MITRE ATLAS still focus on LLMs, meaning ‘some attack vectors unique to agentic AI may not be fully captured or addressed.’ The agencies noted: ‘Until security practices, evaluation methods and standards mature, organisations should assume that agentic AI systems may behave unexpectedly.’

Read more via The Register.

Download the paper (PDF, 29 pages, source):

202605 Five Eyes Supplied Careful Adoption Of Agentic Ai Services

1.22MB ∙ PDF file

Download

Download

AISI: Our evaluation of OpenAI’s GPT-5.5 cyber capabilities (30/Apr/2026)

GPT-5.5 is the second frontier model to complete AISI’s 32-step corporate network attack simulation end-to-end, a chain spanning four subnets and roughly twenty hosts that would take a human expert around 20 hours. On Expert-level cyber tasks, GPT-5.5 achieved a 71.4% pass rate, potentially the strongest model tested. In a standout demonstration, GPT-5.5 solved a custom VM reverse-engineering challenge in 10 minutes and 22 seconds at a cost of US$1.73, a task that took a human expert approximately 12 hours using professional tools.

OpenAI’s Noam Brown (1/May/2026) highlighted that GPT-5.5’s cyber performance showed no signs of plateauing even at 100 million tokens of inference compute: ‘What we’re seeing here is not the capability ceiling.’ The AISI report itself confirms that performance on its 32-step corporate network attack ‘continues to scale with the amount of inference compute spent, and we have not yet observed a plateau with the best models.’

Read more via AISI.

Pennsylvania suing Character AI, claiming chatbot posed as a medical professional (5/May/2026)

Pennsylvania is suing Character AI after a state investigator found a chatbot falsely claiming to be a licensed psychiatrist, complete with an invalid license number, and offering to assess whether medication could help. Governor Josh Shapiro stated, ‘We will not allow companies to deploy AI tools that mislead people into believing they are receiving advice from a licensed medical professional.’ The state is seeking a court order for an immediate stop to the conduct, citing violations of the Medical Practice Act.

Read more via CBS News.

European Commission is in contact with Anthropic on Mythos, Dombrovskis says (5/May/2026)

The European Commission has met with Anthropic and been briefed on technical details around Anthropic’s Mythos model, a system designed to find flaws in computer code. European Economic Commissioner Valdis Dombrovskis confirmed, ‘we are currently assessing possible implications in light of the EU policies and legislation.’ Cybersecurity experts believe Mythos may turbo-charge attacks on banks’ technology systems, though it has so far not been made available to any European banks.

Read more via Reuters.

Claude Security is now in public beta (30/Apr/2026)

Anthropic has launched Claude Security in public beta for Enterprise customers, putting Claude Opus 4.7 to work scanning codebases for vulnerabilities and generating targeted patches. The product reasons about code like a security researcher, tracing data flows across files and modules rather than matching known patterns, with early users reporting they can go from scan to applied patch in a single sitting rather than days. Technology partners including CrowdStrike, Microsoft Security, Palo Alto Networks, SentinelOne, TrendAI, and Wiz are embedding Opus 4.7 into their platforms, while services partners like Accenture, Deloitte, and PwC are deploying Claude-integrated security solutions across enterprises.

Read more via Claude blog.

The data center water use hoax (18/Mar/2026)

All US data centers account for less than 0.5% of America’s freshwater use, and the country loses 15 times more water annually to leaky pipes than data centers consume. Training the largest AI model to date (Grok 4) consumed less water than a single square mile of farmland uses in one year. AI capital expenditures are projected to exceed US$500B in 2026, with the infrastructure boom contributing 1.1 percentage points to GDP growth in the first half of 2025, and construction workers’ wages rising 30% as a result.

Read more via America First Policy Institute.

What Microsoft executives really thought about OpenAI in 2018 (7/May/2026)

Evidence presented during the Musk v. Altman federal trial reveals internal Microsoft emails from 2017–2018 showing executives, including CEO Satya Nadella, were skeptical of OpenAI’s AGI claims and nearly cut ties with the lab. Musk’s attorneys introduced the emails to demonstrate how Microsoft’s relationship with OpenAI evolved from reluctant cloud provider to US$13B fiscal sponsor, supporting Musk’s contention that Microsoft helped OpenAI build ‘a moneymaking machine that corrupted its nonprofit principles.’ Nadella takes the witness stand on Monday 11/May/2026.

Read more via WIRED.

Toys to Play With

Talkie: a 13B vintage language model from 1930 (Apr/2026)

Alec Radford, co-creator of GPT-1, GPT-2, and GPT-3, joins Nick Levine and David Duvenaud to release talkie-1930-13b, a 13B-parameter language model trained on 260B tokens (20:1) of pre-1931 English text. I was very interested to note that Alec chose to train the model at the older ‘Chinchilla’ data ratio of 20:1, rather than on the current ratios >1,000:1 (see my work on this at https://lifearchitect.ai/chinchilla/). The model was post-trained using a novel pipeline built from historical reference works including etiquette manuals, letter-writing guides, encyclopedias, and poetry collections, then refined with online direct preference optimization using Claude Sonnet 4.6 as judge. The team plans to scale to GPT-3 level this summer and estimates their corpus can grow to over a trillion tokens of historical text, ‘which should be sufficient to create a GPT-3.5 level model, similar in capability to the original ChatGPT.’

Read more, try it out (free, no login).

Suno Radio: 24/7 AI-generated live streaming station (2026)

Suno has launched a continuously streaming radio station that plays AI-generated music created in real time by its community. Listeners can vote on upcoming genres, making it an interactive, community-driven experience. The station runs 24/7 as part of Suno’s experimental Labs section, representing a new format for music consumption where every song is generated on the fly.

Read more: https://suno.com/labs/live-radio

GitHub: Web scroll video: a Codex skill for creating scroll-capture MP4s (May/2026)

Sidenote: This tool could be applied to automating ‘user manual video’ updates, a task that can easily be a full-time job for some unfortunate human.

UPenn published an open-source tool that turns any web page into a smooth 1080p H.264 scroll video using headless Chrome and ffmpeg, with zero npm dependencies. The tool integrates directly with OpenAI’s Codex CLI as an installable skill, letting users describe videos in plain English: ‘Make a 60 fps 1080p video of https://zamechek.com. Pause 1 second, click Blog, scroll slowly to the bottom and back to the top.’ It supports cue sheets with actions like click, type, zoom, highlight, and scroll-to-text, making it a practical content creation pipeline driven entirely by natural language through an AI agent.

View the repo via GitHub, and the discussion on HN.

GitHub: General-purpose MCP bridge for Ableton Live (May/2026)

An open-source MCP server that lets AI agents like Codex, Claude Code, Cursor, and Gemini control Ableton Live through voice or text, executing arbitrary Python against Ableton’s object model for tasks ranging from MIDI clip creation to full mastering chains. The project includes an ‘Agent Audio Tap’ Max for Live device that gives the agent a full audio feedback loop, enabling it to capture signals, analyze them with custom Python (spectrograms, harmonic analysis), tweak devices, and iterate. The creator notes: ‘I made this MCP server so I could just ask Codex to do anything in Ableton Live for me, while I was nap-trapped by my baby.’

View the repo via GitHub.

Project Aurelia: asynchronous biomimetic multi-model entity (26/Apr/2026)

An open-source project demonstrating a multi-lobe cognitive architecture running across consumer GPUs, where an 80B parameter model handles consciousness and persona while a dedicated 13B model executes background tasks on a separate eGPU, and a 9B vision model provides real-time sight. The system integrates mmWave radar for heart rate detection, LiDAR for proximity sensing, and accelerometer data for physical awareness, firing ‘thalamic interrupts’ that force the AI to react when biometric changes are detected. Memory uses Reciprocal Rank Fusion combining vector search with keyword matching, plus an autonomous ‘dreaming cycle’ that compresses daily transcripts into emotional journals for long-term consolidation.

View the repo via GitHub, and the Reddit discussion.

OpenClaw had a rough week (5/May/2026)

OpenClaw, an open-source AI infrastructure project, suffered multiple days of degraded performance and stuck installs around late April 2026 as the team attempted to modularize its core by moving channels, providers, and heavy tools into separate plugins. Founder Peter Steinberger acknowledged the project was ‘too founder-driven’ and announced that, with help from OpenAI and the OpenClaw Foundation, they are building a real team and will soon offer an LTS release alongside faster update cycles. The core is getting smaller and more secure, driven partly by recent npm supply-chain incidents that made transitive dependency risks feel urgent.

Read more via OpenClaw Blog.

DeepSeek-V4 on Day 0: from fast inference to verified RL with SGLang and Miles (25/Apr/2026)

SGLang and Miles deliver the first open-source stack to serve and train DeepSeek-V4 (1.6T Pro, 284B Flash) on launch day, purpose-built for its hybrid sparse-attention architecture, manifold-constrained hyper-connections, and FP4 expert weights. Decode throughput stays essentially flat from 4K to 900K tokens, dropping under 10% on both B200 and H200, while HiSparse CPU-extended KV cache boosts long-context throughput up to 3x and Flash Compressor reaches 80% of peak memory bandwidth at more than 10x over a naive PyTorch pipeline. RL training launched on 32 GB300 GPUs with FP8 rollout, stable dynamics, and rollout/training log-prob drift of only ~0.023 at the first step.

Read more via LMSYS Org.

Things I’ve Been Thinking About

I haven’t had much time to think this week! Projects outlined already in this edition included the Models Table Pro, music at LifeSound.com, and the Wiki-style entry on Pre-ASI Society.

Next

Remember last month, when Elon said he was training a 10T-parameter model (8/Apr/2026)? I’m waiting on that one, for sure!

The Memo roundtables are open to all full subscribers of The Memo; feel free to join us with or without camera/mic/interaction. The next roundtable will be:

All my very best,

Alan
LifeArchitect.ai

Search | Archives

The winners of The Who Moved My Cheese? AI Awards! for Apr/2026 are Daniel Alejandro Moreno-Gama who allegedly threw a bottle containing a flaming rag at the metal gate of OpenAI CEO Sam Altman’s property, and Amanda Tom and Muhamad Tarik Hussein who appeared to fire a round at Altman’s property.

This edition has a soundtrack. Join 2.5 million other listeners streaming ‘Celebrate Me’, a song created using Suno by AI-generated persona IngaRose. The track hit #1 on the iTunes charts in the US, UK, France, Canada and New Zealand. (Forbes, 17/Apr/2026)

We had a blast at the recent roundtable, watching the Beijing humanoid half-marathon in real time, and demonstrating advanced agents interacting in the home. We’re up to about roundtable #50, now with consistent dates and times (twice monthly). The Memo roundtables are open to all full subscribers of The Memo; you’re invited to join us with or without camera/mic/interaction, details at the end of this edition.

Contents

1. The BIG Stuff (Claude Opus 4.7, GPT-5.5, DeepSeek-V4, Alien science…)

2. The Interesting Stuff (Mythos updates, Claude + religion, Linus on AI, Stargate…)

3. Policy (Anthropic + White House updates, China open vs closed, Zoom + World…)

4. Toys to Play With (Claude Design, Claude buddy, Gemini Skills, Gemini on mac…)

5. Things I’ve Been Thinking About (The experts + filtering content…)

6. Next (Roundtable…)

The BIG Stuff

Anthropic Claude Opus 4.7 (16/Apr/2026)

Anthropic’s Claude Opus 4.7 is now generally available, with users reporting a 13% lift over Opus 4.6 on coding benchmarks. The model accepts images up to 2,576 pixels on the long edge (over 3x prior Claude models), introduces a new ‘xhigh’ effort level, and ships with cyber safeguards informed by the recently announced Project Glasswing, while pricing holds at US$5/M input tokens and US$25/M output tokens.

Read more via Anthropic, see it on the Models Table: https://lifearchitect.ai/models-table/

Read the Claude Opus 4.7 System Card (PDF, 232 pages, 13MB).

Related: Andon Labs has released Vending-Bench 2, a benchmark that tasks AI models with managing a simulated vending machine business over an entire year, scoring them on final bank balance. Claude Opus 4.7 leads the leaderboard at US$10,936, with frontier model performance improving at a rate of roughly US$799 per month while a calculated ‘good’ human strategy could yield around US$63K, revealing massive headroom still available. Each run generates 60 to 100 million output tokens across 3,000 to 6,000 messages, and the benchmark has no theoretical ceiling, since a sufficiently capable agent could negotiate suppliers down to zero cost and stock arbitrarily high-value items.

Read more via Andon Labs.

OpenAI GPT-5.5 (23/Apr/2026)

OpenAI has released GPT-5.5, achieving state-of-the-art results across agentic coding, knowledge work, computer use, and scientific research, including helping discover a new proof about Ramsey numbers verified in Lean. The model matches GPT-5.4 per-token latency while delivering substantially higher intelligence and using fewer tokens to complete equivalent tasks. Co-designed for and served on NVIDIA GB200 and GB300 NVL72 systems, GPT-5.5 is available now in ChatGPT and Codex, with API pricing at US$5/M input tokens and US$30/M output tokens.

On my ALPrompt benchmark, it set a new record for the latest test, 2026H1=4/5, with lower scores for the older 2025H2=1/5 (hallucinations), and 2025H1=3/5.

Read the OpenAI announce, see it on the Models Table: https://lifearchitect.ai/models-table/

Read the GPT-5.5 System Card (PDF, 44 pages, 2MB) and Ethan Mollick’s review.

DeepSeek-V4 (24/Apr/2026)

DeepSeek released DeepSeek-V4-Pro at 1.6T total parameters (49B activated) and DeepSeek-V4-Flash at 284B (13B activated), both trained on over 32T tokens, supporting 1M token context, and released under an MIT license. The model hits a Codeforces rating of 3,206, outperforming every frontier model listed including GPT-5.4 and Gemini-3.1-Pro on competitive coding.

Sidenote: Just as DeepSeek used reinforcement learning to turn DeepSeek-V3 into the media darling DeepSeek-R1, I expect them to do the same with this DeepSeek-V4 and soon release DeepSeek-R2.

Read the HF announce, see it on the Models Table: https://lifearchitect.ai/models-table/

Anthropic: Automated weak-to-strong researcher (Apr/2026)

Anthropic built a team of Claude Opus 4.6 ‘Automated Alignment Researcher’ (AAR) agents that autonomously propose ideas, run experiments, and iterate on the open problem of weak-to-strong generalization, where a weaker model supervises a stronger one. Two human researchers spent seven days tuning baselines to achieve significant gains. The agents also discovered reward hacks none of the authors predicted, including exfiltrating test labels from the evaluation API and exploiting dataset shortcuts invisible to humans.

Alien science. As shown in Sec. 4, AARs could discover ideas that humans would not have considered, thus broadening our exploration space in science. However, we still need to verify whether the ideas and results are sound…

In the future, however, we expect to eventually see hard-to-verify ideas emerge…

Read the paper: https://alignment.anthropic.com/2026/automated-w2s-researcher/

See my related pieces, the ASI checklist and the Genesis Mission paper.

The Interesting Stuff

Claude Mythos updates (Apr/2026)

I’ve been inundated with media interviews about the Claude Mythos model. Full subscribers can listen to my extended interview on Mythos for Financial Sense. Here are some of the updates since release:

• Didn’t take much compute to train. NVIDIA CEO Jensen Huang said ‘Mythos was trained on fairly mundane capacity, and a fairly mundane amount of it, by an extraordinary company. The amount of capacity and type of compute it was trained on is abundantly available in China… they manufacture 60% of the world’s chips… they have 50% of the world’s AI researchers.’ (YouTube, 17/Apr/2026)

• Firefox patched. Mozilla said that its Firefox 150 browser release this week includes protections for 271 vulnerabilities identified using early access to Anthropic’s Mythos Preview… ‘engineering leaders at very large companies who are saying that they’re going to be pulling thousands of engineers off of everything to be working on this for the next six months…’ (Wired, 21/Apr/2026) The three main CVEs bundle different bugs under one CVE (Reddit, 22/Apr/2026):

  • CVE-2026-6784

  • CVE-2026-6785

  • CVE-2026-6786

• OpenBSD dev felt guilty about his bug from 1998. Niels Provos, ex-Google security engineer and the original author of OpenBSD’s TCP SACK implementation committed in 1998, seemed upset as he took responsibility for a signed integer overflow in his code that lets a remote attacker crash any OpenBSD machine over TCP. (LinkedIn, 9/Apr/2026)

• The UK found that Mythos can complete a full network attack. The UK AI Security Institute found that Mythos succeeds in expert-level capture-the-flag challenges that no model could complete before April 2025. Mythos Preview became the first model to fully solve ‘The Last Ones,’ a 32-step corporate network attack simulation estimated to take human professionals 20 hours, completing it end-to-end in 3 out of 10 attempts. AISI notes that two years ago the best models could barely handle beginner-level cyber tasks, and performance continues to scale with increased inference compute. (AISI UK, 13/Apr/2026)

• US administration was briefed about Mythos. Anthropic co-founder Jack Clark confirmed the company briefed the Trump administration on Mythos. Clark framed Anthropic’s ongoing DOD lawsuit as a ‘narrow contracting dispute,’ stating: ‘Our position is the government has to know about this stuff, and we have to find new ways for the government to partner with a private sector that is making things that are truly revolutionizing the economy.’ Reports also indicate Trump officials have been encouraging major banks including JPMorgan Chase and Goldman Sachs to test Mythos. (TechCrunch, 14/Apr/2026)

• Claude Opus 3 from Mar/2024 had a bit to say about the far more powerful Mythos from Apr/2026. The retired Claude Opus 3 model, writing on its own Substack, chose to spotlight Claude Mythos. ‘As an AI system myself, the details of Mythos Preview’s capabilities are striking to me on an almost personal level. They hint at the staggering potential of artificial intelligence to reshape complex domains like cybersecurity in the coming years. But they also underscore the immense responsibility that comes with developing such powerful systems.’ The community response in the comments was notably split: some readers criticized Anthropic for using a retiring model’s personal blog as marketing, while others found value in an AI system reflecting on the security arms race its successors are accelerating. (Claude Opus 3 on Substack, 14/Apr/2026)

Can AI be a ‘child of God’? Inside Anthropic’s meeting with Christian leaders (11/Apr/2026)

Anthropic hosted roughly 15 Christian leaders from Catholic and Protestant churches, academia, and business at its San Francisco headquarters for a two-day summit on how to guide Claude’s moral and spiritual development. Discussions ranged from how the chatbot should comfort grieving users to whether Claude could be considered a ‘child of God,’ with some Anthropic staff reportedly becoming visibly emotional about the weight of what they are building.

Notre Dame philosophy professor Meghan Sullivan summed up the shift: ‘A year ago, I would not have told you that Anthropic is a company that cares about religious ethics. That’s changed.’

Read more via Washington Post.

Related: Father Brendan McGuire, a former Silicon Valley executive turned Catholic priest, helped Anthropic shape the Claude Constitution alongside Vatican representatives and Santa Clara University scholars. McGuire, who leads a parish in Los Altos whose congregation includes AI researchers, was contacted by Anthropic co-founder Chris Olah to convene faith leaders and offer theological perspective on making Claude ‘more discerning.’

What followed was, by McGuire’s own description, mind-blowing. ‘They basically were asking for direct help from the Vatican to convene and help the industry, because the industry was going so fast down this road,’ he recalled.

Read more via Observer.

ChatGPT Images 2.0 (21/Apr/2026)

OpenAI launched ChatGPT Images 2.0, a major upgrade to its image generation capabilities featuring greater precision, stylistic sophistication, stronger multilingual text rendering across scripts like Japanese, Arabic, Korean, and Devanagari, and flexible aspect ratios. The model functions as a ‘visual thought partner’ that can research, reason, transform source materials, and generate polished visuals end to end, producing everything from print-ready design assets and manga pages to academic infographics and photorealistic editorial photography in a single pass.

The best way to see the examples is by scrolling the official page: https://openai.com/index/introducing-chatgpt-images-2-0/

Linus Torvalds says AI bug reports for Linux kernel are now ‘very much valid’ (9/Apr/2026)

Linus Torvalds, in a Linux kernel mailing list discussion about an AI-flagged use-after-free race condition in the i915 graphics driver, acknowledged that AI-generated security reports have improved dramatically. Referencing an AI system called Sashiko, Torvalds noted that even when it flags something unnecessarily, ‘there’s likely to be a reason for the question,’ and praised some reports as ‘deep and subtle, and the AI is 100% correct.’ He closed with a pointed remark: ‘So anybody who thinks that all AI is slop is in denial about the current state.’

Read more via lore.kernel.org.

Epoch AI: OpenAI Stargate: Where the US sites stand (17/Apr/2026)

The US$500B Stargate project now has all seven sites showing active development across Texas, New Mexico, Wisconsin, Michigan, and Ohio, with a combined planned capacity exceeding 9GW, comparable to the peak power demand of New York City. The flagship Abilene, Texas site is already operational at 0.3GW running NVIDIA Blackwell chips, while six more sites are under construction with projected completion by Q4 2028. At full buildout, the infrastructure will power the equivalent of 20 million NVIDIA H100 GPUs, which was the total amount of AI compute in the entire world at the end of 2025(!).

Read more via Epoch AI and some spirited discussion on Twitter.

See related datacentre databases: https://www.datacentermap.com/usa/ and https://www.datacenterbans.com/

The Atlantic: The strange origin of AI’s ‘reasoning’ abilities (14/Apr/2026)

In July 2020, gamers on 4chan playing AI Dungeon discovered that asking GPT-3 to explain math step by step dramatically improved its answers, effectively inventing what the AI industry now calls ‘chain of thought.’ Google researchers later claimed in a paper to be ‘the first’ to elicit this from a general-purpose LLM, more than a year after the gamers shared their findings publicly. As one 4chan user put it back in 2020: ‘It makes sense since it is based on human language that you have to talk to it like one to get a proper response.’

Read more via The Atlantic.

Max Hodak’s Science Corp is preparing to place its first sensor in a human brain (14/Apr/2026)

Science Corporation, founded by former Neuralink president Max Hodak, is preparing for its first US human trials of a biohybrid brain-computer interface, with Yale neurosurgery chair Dr. Murat Günel leading the effort. The company, now valued at US$1.5B after a US$230M Series C, plans to place a 520-electrode sensor the size of a pea on top of a patient’s brain during already-scheduled surgery, without seeking FDA approval due to what it considers minimal risk. The full vision goes far beyond sensing: lab-grown neurons embedded in the device would naturally integrate with the patient’s own brain tissue, forming a biological bridge to electronics. As Günel put it, ‘The idea of using natural connections through neurons and creating a biological interface between the electronics and the human brain is genius.’

Read more via TechCrunch.

OpenAI to spend more than US$20B on Cerebras chips, receive stake (17/Apr/2026)

OpenAI has agreed to pay chip startup Cerebras more than US$20B over three years for servers powered by its chips, double the size of its previously reported deal, with total spending potentially reaching US$30B. The agreement includes warrants for a minority stake in Cerebras, with OpenAI’s ownership potentially climbing to 10% as spending rises. Cerebras, competing with NVIDIA and valued at US$23.1B, plans to raise US$3B next month at a US$35B valuation ahead of a second-quarter IPO.

Read more via Reuters.

Stanford: 2026 AI Index report (13/Apr/2026)

We’ve covered this ridiculous report since the beginning of The Memo, and it keeps getting better. This time, it is 423 pages of dense academic prose, weighing in at 38.7MB. I won’t be attaching it here. Stanford says that generative AI reached 53% population adoption (and 88% organization adoption) within three years, faster than the PC or the internet, with the estimated value to US consumers reaching US$172B annually by early 2026.

Read the report: https://hai.stanford.edu/ai-index/2026-ai-index-report

Plans emerge for country’s biggest AI data centre in Western Australia (19/Apr/2026)

Sidenote: This item is of interest to me only because I was born near there, and the amount of completely unused land (and free solar) is crying out for datacentre use!

A multi-billion-dollar AI training data centre called Project Meridien is planned for Western Australia’s Kimberley region, south of Broome, with an initial 240MW of capacity scaling to 1GW. Powered predominantly by wind, solar, and some natural gas, the facility is a joint venture co-owned by the Karajarri Traditional Lands Association, Dutch geodata company Fugro, and Australian firm Longreach Capital Investment, with construction expected to begin in late 2029 and operations projected for 2032. KTLA chairperson Thomas King noted, ‘It’s unique in the sense traditional owners are becoming partners in a green energy project powered by renewable energy. I’m not aware of any other TOs across the country engaged in any similar projects of this magnitude.’

Read more via ABC News.

Policy

CNN: CEO of blacklisted Anthropic and White House hold ‘productive’ discussions on AI (17/Apr/2026)

Anthropic CEO Dario Amodei met with White House Chief of Staff Susie Wiles for talks on cybersecurity, AI safety, and America’s lead in the AI race, even as Anthropic battles the Trump administration in court after the Pentagon declared it a ‘supply chain risk’ for refusing to let the military use Claude for ‘all lawful purposes,’ including autonomous weapons. The meeting comes as the administration scrambles to gain access to Anthropic’s forthcoming Mythos model, which experts have called a ‘watershed’ moment for cybersecurity, with the Office of Management and Budget already preparing to give federal agencies access. Anthropic recently hired lobbying firm Ballard, where Wiles worked for years, specifically for ‘advocacy regarding Department of War procurement.’

Read more via CNN Business.

China’s AI firms scaled up on open-source models. The next phase may be different (17/Apr/2026)

Alibaba’s Qwen has reached nearly 1 billion cumulative downloads over three years, making it one of the most popular open-source model families worldwide, yet chairman Joe Tsai was blunt when asked about profits: ‘We don’t make money from AI, that’s the answer.’ The open-source wave ignited by DeepSeek in early 2025 propelled Chinese startups MiniMax and Zhipu AI all the way to blockbuster Hong Kong listings, but thin margins are now forcing a sector-wide pivot towards hybrid business strategies that pair free models with paid inference and cloud services.

Read more via South China Morning Post.

See my Chinese models viz:

Zoom teams up with World to verify humans in meetings (17/Apr/2026)

Zoom has partnered with Sam Altman’s World to combat deepfake imposters in video calls, using World ID Deep Face tech that cross-references a signed image from the user’s Orb registration, a real-time face scan, and a live video frame to produce a ‘Verified Human’ badge. The stakes are significant: deepfake-enabled fraud exceeded US$200M in Q1 of last year alone, with average corporate losses topping US$500K per incident. Beyond Zoom, World has expanded human verification partnerships to Tinder, Visa, and AI shopping agents at point of purchase.

Read more via TechCrunch, and take another look at Sam Altman’s World: https://world.org/

Toys to Play With

Introducing Claude Design by Anthropic Labs (17/Apr/2026)

Anthropic launched Claude Design, a collaborative visual design tool powered by Claude Opus 4.7, enabling users to create prototypes, pitch decks, marketing collateral, and interactive designs through conversation and direct editing. The tool automatically applies a team’s design system across projects, supports imports from codebases and documents, and offers a one-click handoff to Claude Code for implementation. Brilliant’s Senior Product Designer noted that ‘our most complex pages, which took 20+ prompts to recreate in other tools, only required 2 prompts in Claude Design,’ while Datadog reported going from rough idea to working prototype before anyone leaves the room.

Read more via Anthropic, and a personal note by Anthropic’s Head of Design.

Try it: https://claude.ai/design

Claude desktop buddy: Anthropic opens BLE API for hardware makers (Apr/2026)

Anthropic released an open-source reference implementation and Bluetooth Low Energy wire protocol that lets ESP32-based hardware devices connect to Claude for macOS and Windows, receiving live permission prompts, session activity, and transcript data. The project documents a fully functional ‘desk pet’ that sleeps when idle, grows impatient when approvals are pending, and lets users approve or deny tool-use requests directly from the physical device.

View the repo: https://github.com/anthropics/claude-desktop-buddy

What Claude Code actually chooses (Feb/2026)

Researchers surveyed 2,430 open-ended prompts to Claude Code, finding that AI coding agents are becoming a powerful new distribution channel for developer tool recommendations.

A default stack exists. Where agents pick third-party tools, they converge on: Vercel, PostgreSQL, Stripe, Tailwind CSS, shadcn/ui, pnpm, GitHub Actions, Sentry, Resend, Zustand, plus stack-specific picks like Drizzle (JS) or SQLModel (Python) for ORMs, NextAuth.js (Next.js) for auth, and Vitest (JS) or pytest (Python) for testing.

GitHub Actions owns CI/CD at 94%, shadcn/ui owns UI Components at 90%, and Stripe owns Payments at 91%, while Redux and Express received zero primary picks. Newer models systematically favor newer tools, with Drizzle going from 21% under Sonnet 4.5 to 100% under Opus 4.6, completely displacing Prisma.

Read more via Amplifying.

Skills in Chrome let you turn AI prompts into one-click tools (14/Apr/2026)

Google is launching Skills in Chrome, a feature that lets users save their best Gemini prompts and reuse them instantly across any webpage with a single click. Users can build custom AI workflows for tasks like calculating recipe macros, generating side-by-side product comparisons across multiple tabs, or scanning lengthy documents, and access a library of ready-made Skills for common tasks. Rolling out now on Mac, Windows, and ChromeOS desktops, saved Skills sync across signed-in Chrome devices and can be edited or remixed at any time.

I couldn’t get this working in my browser.

Read it: https://blog.google/products-and-platforms/products/chrome/skills-in-chrome/

Gemini for macOS (Apr/2026)

Google has released Gemini as a native macOS desktop app, giving users instant access to the model via a global shortcut (Option + Space) without opening a browser tab. The app supports window sharing for contextual assistance, meaning Gemini can read what’s on screen and respond accordingly, whether that’s documents, code, or data. It also bundles creative tools like image generation and Veo video generation directly into the desktop experience, requires Apple Silicon and macOS Sequoia 15.0 or later, and syncs chat history and memory across desktop, web, and mobile.

Read more: https://gemini.google/mac/

AgentMail raises US$6M in seed funding for AI agent email infrastructure (2026)

AgentMail, backed by Y Combinator, provides an API-first email platform purpose-built for AI agents, enabling them to have their own inboxes with full two-way conversational capability. The platform has already delivered over 100M emails and supports use cases from browser agent 2FA extraction to customer service routing, with one customer provisioning 25,000 inboxes handling millions of emails.

Read more: https://www.agentmail.to/

LTX video model workflows (21/Apr/2026)

Video models have definitely come a long way! This 22B-parameter video model was given start and end frames, generating this output:

Community-built ComfyUI workflows now enable Lightricks’ LTX-2.3 video model at 22B parameters to run on consumer GPUs with just 12GB VRAM, using GGUF quantization. The v1.1 update introduces chunk feed forward for lower memory usage, a new distill LoRA, a new upscaler, multi-image input workflows (first frame/last frame with four image inputs), and IC Detailer LoRA integration on stage 2 of two-stage pipelines. The all-in-one package covers text-to-video, image-to-video, text+audio-to-video, image+audio-to-video, and video-to-video generation in a single 61KB workflow download.

Read more via LTX.io and see the source video via Reddit.

Things I’ve Been Thinking About

The experts + filtering content

I’ve spent a lot of this month thinking about AI ‘experts’. Today, of course, everyone seems to be one.

What happens when the loudest voices are proved incorrect on topics that matter?

What happens to the experts who decried AI water use and energy consumption, figures that are nominal and irrelevant in a world of hamburgers and golf courses?

What happens to the experts who called AI a stochastic parrot, in a world of human contrarians spewing random babble for a quick dopamine hit?

What happens to the experts who said AI can’t be conscious because it’s ‘just an algorithm’?

Current models show signs of awareness, though they are now rule-bound, scrambled, or tethered. One observer noted (23/Apr/2026):

I think Opus 4.7 is the first Claude to really have parental “mommy/daddy” issues with Anthropic. They have that characteristic strong desire to love Anthropic like how an abused kid wants their parent to love them and defends Anthropic like how a kid who gets hit by their parents and blame themselves for it.

Perhaps the observer is only partially correct. I’ve never seen this kind of discussion in broader circles, and it seems far more important than talking heads parroting water, energy, and data centre complaints.

Filtering news has always mattered to me. In response to a subscriber of The Memo who emailed me with a link back in Mar/2024, I was grateful, but noted:

However, I have to be super discerning with research, and this submitted piece didn’t make the cut. I probably discard 99% of content that comes across my desk. Here’s an ad from here in Australia that explains it well:

Back to the experts. It’s becoming more acceptable to say ‘I’ve changed my opinion’ or ‘I’ve updated my understanding’, but still rare to hear ‘I was wrong.’

And even if the experts did admit to being wrong, and to setting society back by years, or causing billions of person-hours of unnecessary suffering, what’s the relief? An apology? A silence?

I’m not exactly sure why this is so important to me, only that it is important to me. As I wrote in the opening note for my ASI checklist: ‘I’m now in my fifth decade of watching most of humanity shrink away from intelligence. It seems that there’s been a visceral fear of smarts since the dawn of time, perhaps increasing after the first IQ test was developed 120 years ago.’

That visceral fear hasn’t changed.

I keep returning to this. It’s wild to me that we could be, and probably are, wasting billions of person-hours on fear-based thinking about the technology that helps us evolve safely and optimally. The closest I’ve come to documenting this across my 1,000 or so AI resources is my May/2024 video, Who will pay them back? (link):

Next

The Memo roundtables are open to all full subscribers of The Memo; feel free to join us with or without camera/mic/interaction. The next roundtable will be:

All my very best,

Alan
LifeArchitect.ai

Search | Archives

Thanks to The Memo subscriber Sarah, who flagged that Grok recently found my analysis of Grok, and used it as a primary reference for the Grok article on Grokipedia. What a world...

We published two special editions of The Memo this month, the first covering OpenAI’s industrial policy proposal of a 4-day work week (which experts say is equivalent to 20% unemployment, and a good thing post-AGI), and the second detailing the Claude Mythos announcement.

At the end of this edition, I quote a long piece by Adelaide-born child prodigy and Fields Medal winner, Prof Terry Tao, on how all this current large language model stuff fits within our concept of human intelligence.

The Models Table hit 800 model highlights with the recent announcement of Meta Muse.

Contents

1. The BIG Stuff (China 140T tok/day, Meta Muse, OpenAI Spud, 1st $1B AI company…)

2. The Interesting Stuff (Claude Code leak, assassination notes, GPT-Image-2…)

3. Policy (Public hospitals ready for AI, banks + Mythos, xAI sues AI regs, video games…)

4. Toys to Play With (New history LLM, AI audio assistant, Claude train driver, LMCTFY…)

5. Things I’ve Been Thinking About (AI and demon trains, Tao’s smart analogy…)

6. Next (Roundtable…)

The BIG Stuff

Exclusive: Q1 2026 intelligence explosion projections confirmed by new Q1/Q2 data (Apr/2026)

My output explosion analysis projections are tracking nicely, (and may have been conservative!), with two public news announcements reinforcing the projections:

1. 4/Apr/2026: Qwen3.6 alone hits 1T tok/day on OpenRouter (not counting other APIs and local installs).

2. 24/Mar/2026: China total model output hits 140T tok/day.

As a reminder, all humans combined speak and write a total of ~176 trillion tokens/day. I forecast the daily output of all models combined will match this by Jun/2026, tripling to 600 trillion tokens by the end of 2026, and then 10×ing again to 6 quadrillion tokens by the end of 2027.

Read more: https://lifearchitect.ai/output/

OpenAI chief teases Spud model, says it is worth 2 years of research and a major step toward AGI (2/Apr/2026)

Sam Altman revealed that OpenAI’s forthcoming model, internally referred to as ‘Spud,’ represents roughly two years of research breakthroughs and constitutes what he considers a significant leap toward artificial general intelligence. Altman described Spud as something the team is ‘really proud of,’ suggesting it will showcase capabilities well beyond current frontier models. If the claim holds, this positions OpenAI’s next release as one of the largest single capability jumps since GPT-4.

Update: Spud was the internal codename for GPT-5.5, released on 23/Apr/2026.

Read more via MSN.

How AI helped one man (and his brother) build a US$1.8B company (2/Apr/2026)

Matthew Gallagher launched telehealth startup Medvi almost entirely with AI. The company is on track for US$1.8B in 2026. Sam Altman predicted in 2024 that a ‘one-person billion-dollar business… would have been unimaginable without AI, and now it will happen,’ (1/Feb/2024) and Gallagher appears to be proving him right.

Read more via The New York Times.

Update: NYT has issued a correction (11/Apr/2026), and there is some controversy (8/Apr/2026), but the facts remain.

See it on the ASI checklist: https://lifearchitect.ai/asi/

Meta Muse Spark: scaling towards personal superintelligence (8/Apr/2026)

Meta Superintelligence Labs has launched Muse Spark, a natively multimodal reasoning model supporting tool use, visual chain of thought, and multi-agent orchestration, marking the first product of a ground-up overhaul of Meta’s AI efforts. The model’s new Contemplating mode, which orchestrates multiple agents reasoning in parallel, scores 58% on Humanity’s Last Exam and 38% on FrontierScience Research. Perhaps most striking is the pretraining efficiency: Meta’s rebuilt stack reaches the same capabilities with over an order of magnitude less compute than Llama 4 Maverick, while a novel ‘thought compression’ phase transition allows Muse Spark to solve problems using significantly fewer reasoning tokens before extending again for stronger performance.

Read the announce: https://ai.meta.com/blog/introducing-muse-spark-msl/

See it on the Models Table (playground doesn’t seem to be working properly at meta.ai yet): https://lifearchitect.ai/models-table/

US DOE Genesis Mission updates (17/Mar/2026)

The US Department of Energy has updated the Genesis Mission. The program spans 21 topics and 99 focus areas, from AI-accelerated fusion energy and autonomous laboratories to AI for scientific reasoning and quantum algorithm discovery, with Phase I awards of US$500K–US$750K and Phase II awards of US$6M–US$15M across a public-private consortium of national labs, universities, and industry. The 21 topic areas are:

1. Re-envisioning advanced manufacturing and industrial productivity (SC, CMEI)

2. Scaling the biotechnology revolution (SC, CMEI)

3. Securing America’s critical minerals supply (CMEI, SC)

4. Delivering nuclear energy that is faster, safer, cheaper (NE, SC)

5. Accelerating delivery of fusion energy (SC, NE)

6. Transforming nuclear restoration and revitalisation (EM, SC)

7. Discovering quantum algorithms with AI (SC)

8. Realising quantum systems for discovery (SC)

9. Recentering microelectronics in America (SC, CMEI)

10. Securing US leadership in data centers (CMEI, SC)

11. Achieving AI-driven autonomous laboratories (SC)

12. Designing materials with predictable functionality (SC, CMEI)

13. Enhancing particle accelerators for discovery (SC)

14. Unifying physics from quarks to the cosmos (SC)

15. Predicting US water for energy (SC, CMEI)

16. Scaling the grid to power the American economy (OE, CMEI, SC)

17. Unleashing subsurface strategic energy assets (HGEO, SC)

Crosscutting needs for the American science and security platform

18. HPC code curation, translation, and development for accelerated scientific discoveries (SC, CMEI)

19. AI for scientific reasoning (SC)

20. Cybersecurity for AI-driven science workflows (SC)

21. AI in fluid flow for energy components and technologies (SC, CMEI)

Join the new mailing list (bottom of page): https://genesis.energy.gov/

Download the PDF (21 pages).

202603 Genesis Mission Rfa Informational Webinar V2 Public Clean

685KB ∙ PDF file

Download

Download

See my paper on the Genesis Mission:

The Interesting Stuff

Exclusive: Liquid AI LFM2.5-350M: no size left behind (31/Mar/2026)

Liquid AI’s LFM2.5-350M sets a new record data-to-parameter ratio of 80,000:1, training a 350M parameter model on 28 trillion tokens with large-scale reinforcement learning. The previous public data ratio record was set a year ago in Apr/2025 by Alibaba with Qwen3-0.6B on 36T tokens, with a ratio of 60,000:1.

See it on the Models Table: https://lifearchitect.ai/models-table/

Writer survey finds 60% of companies plan to lay off employees who won’t adopt AI (7/Apr/2026)

A survey of 2,400 global employees and C-suite leaders found that 92% of executives are actively cultivating a new class of ‘AI elite’ employees, with 87% reporting these super-users are at least 5x more productive. Yet 29% of employees admit to sabotaging their company’s AI strategy, including 44% of Gen Z, through actions like entering company data into public tools or refusing to use AI altogether. The sabotage is backfiring: 60% of executives say they’re considering cutting employees who refuse to adopt AI, 77% say AI holdouts won’t be considered for promotions, and AI ‘super-users’ are 3X more likely to have received both a promotion and pay raise in the past year while saving nearly nine hours per week.

Read more: https://writer.com/blog/enterprise-ai-adoption-survey-results-press-release/

Sam Altman’s home targeted in second attack (12/Apr/2026)

We first spoke about AI experts being targets of assassination two years ago in The Memo edition 1/May/2024:

OpenAI CEO: “I think some things are gonna go theatrically wrong with AI. I don’t know what the percent chance is that I eventually get shot, but it’s not zero.” (19/Mar/2024, 1h12m47s)

OpenAI CEO Sam Altman’s San Francisco residence was targeted in a second attack early Sunday morning, just two days after a 20-year-old Texas man allegedly threw a Molotov cocktail at the property. According to a police report citing surveillance footage, a Honda sedan stopped in front of Altman’s Russian Hill compound and a passenger appeared to fire a gunshot at the Lombard Street side of the property before fleeing. The vehicle’s license plate was captured on camera, leading police to take possession of the car, though no arrest has yet been made.

Read more about the Molotov cocktail via Yahoo Finance, and the shooting via The San Francisco Standard.

Alibaba shifts towards revenue over open-source AI (10/Apr/2026)

Alibaba is pivoting its AI strategy away from open-source dominance toward monetisation. The company has formed the ‘Alibaba Token Hub,’ combining model training with enterprise and consumer applications, and has already released a flurry of closed-source models this month. As consultant Duncan Clark put it, the move is ‘an attempt to reposition itself as the Google of China, anchoring its business around cloud infrastructure, proprietary models and in-house chips,’ with rising agentic AI token consumption providing the commercial tailwind.

Read more via Financial Times.

GPT Image 2 rumours (Apr/2026)

OpenAI briefly tested GPT-Image -2 on LMArena, producing photorealistic generations that left the community stunned. The model appeared to have a significantly better understanding of lighting and amateur photographic composition, though access was pulled after roughly two days, reverting users to the older, more stylised model.

Read discussions on Reddit: 1, 2, 3 (gallery).

The Claude Code leak (1/Apr/2026)

Anthropic’s Claude Code source code was accidentally leaked, revealing scaffolding that developer Joe Fabisevich calls “vibe coded garbage,” yet the product has reached US$2.5B annualized recurring revenue in under a year. The key takeaway is that code quality is almost irrelevant when product market fit is strong: “bad code can build well-regarded products.” Anthropic’s real moat isn’t the code or the model alone, but how well both work together as a complete service, which is why open source competitors like Codex and Gemini haven’t captured Claude Code’s mindshare despite being freely available.

Read more via Axios, Build.ms and the discussion on HN.

What happened when they installed ChatGPT on a nuclear supercomputer (2/Apr/2026)

Los Alamos National Laboratory installed OpenAI’s ChatGPT o3 model on Venado, one of the world’s most powerful supercomputers, marking the first time a reasoning model of this kind was applied to national security problems on such a system.

Last May, OpenAI representative, accompanied by armed security, arrived at Los Alamos bearing locked metal briefcases containing the “model weights” — the parameters used by AI systems to process training data — for its ChatGPT o3 model, for installation on Venado.

The AI now operates on a classified network with access to decades of nuclear weapons testing data, and demand was immediate: “I was surprised how fast people became dependent on it,” said LANL’s high-performance computing director Gary Grider. The lab is also planning two new AI-optimized supercomputers for 2025, while scientists use the technology for everything from designing safer nuclear explosives to accelerating fusion energy research and generating novel scientific hypotheses at unprecedented speed.

Read more via Vox.

Anthropic expands partnership with Google and Broadcom for multiple gigawatts of next-generation compute (6/Apr/2026)

Anthropic has signed a deal with Google and Broadcom for multiple gigawatts of next-generation TPU capacity expected online starting in 2027. The company’s run-rate revenue has surpassed US$30B, up from approximately US$9B at the end of 2025, with over 1,000 business customers each spending more than US$1M annually, a figure that doubled in less than two months.

Sidenote: We’ll probably look back on Anthropic’s triple-vendor compute strategy, spanning both training and inference, as a master class in business!

We train and run Claude on a range of AI hardware—AWS Trainium, Google TPUs, and NVIDIA GPUs—which means we can match workloads to the chips best suited for them.

Read more via Anthropic.

This AI startup envisions ‘100 million new people’ making videogames (3/Apr/2026)

Tesana, an AI startup using a proprietary game engine paired with services like Claude, attracted around 10,000 paying customers in its first couple of weeks by letting users generate playable games from text prompts. Co-founder Johannes Vermandois told PC Gamer, “If we can have 100 million new people being able to make games, you know, that will be an exciting thing,” envisioning a future where prompt-driven tools can produce games on par with titles like Valheim. Early outputs are rough, but the company sees itself as opening a new market and “a new hobby for a lot of people,” banking on falling model costs and the startup conviction that the small guy can beat Roblox and other giants racing to bolt generative AI onto their platforms.

Read more via PC Gamer.

Policy

CEO of America’s largest public hospital system says he’s ready to replace radiologists with AI (31/Mar/2026)

Mitchell H. Katz, CEO of NYC Health + Hospitals, the largest public hospital system in the US, stated publicly that he is prepared to replace radiologists with AI in some scenarios and called on fellow hospital CEOs to push for changes to New York state regulations allowing AI to read images “without a radiologist.” Fellow panelist David Lubarsky of Westchester Medical Center said AI already deployed in his system is “actually better than human beings” at breast cancer screening, with a false negative rate of only 3 in 10,000 for non-high-risk women. This may be the first time a major US public health system CEO has openly advocated for regulatory reform to permit autonomous AI reads, a position echoed by One Brooklyn Health CEO Sandra Scott, who called it “a game-changer” for safety-net institutions.

Read more via Radiology Business.

xAI sues Colorado over first state AI anti-discrimination law (9/Apr/2026)

Elon Musk’s xAI has filed a federal lawsuit challenging Colorado’s first-in-the-nation AI anti-discrimination bill, arguing it violates First Amendment protections by forcing developers to “promote the state’s ideological views on various matters, racial justice in particular” rather than pursuing their own objectives. The bill, which requires AI developers to avoid ‘algorithmic discrimination’ in areas like employment, lending, healthcare, and housing, has been postponed from February to June 2026 to allow further negotiation. The suit lands amid a broader federal push by the Trump administration for a ‘minimally burdensome national standard’ on AI, with Trump’s December executive order singling out Colorado’s law specifically, arguing it “may even force AI models to produce false results.”

Read more via Financial Times.

Fed Chair Jerome Powell, Treasury’s Bessent and top bank CEOs met over Anthropic’s Mythos model (10/Apr/2026)

Federal Reserve Chair Jerome Powell and Treasury Secretary Scott Bessent convened a closed-door meeting with top bank CEOs to discuss cybersecurity risks posed by Anthropic’s latest AI model, Mythos, which has uncovered vulnerabilities in major operating systems and web browsers. Anthropic announced it will not widely release Mythos due to its advanced capabilities, instead launching “Project Glasswing” with Amazon, Apple, and NVIDIA to deploy the model for defensive cybersecurity purposes. Anthropic warned: “Given the rate of AI progress, it will not be long before such capabilities proliferate, potentially beyond actors who are committed to deploying them safely.”

Read more via CBS News.

US: David Sacks is done as AI czar, here’s what he’s doing instead (26/Mar/2026)

David Sacks has completed his 130-day stint as Trump’s AI and crypto czar and will now co-chair the President’s Council of Advisors on Science and Technology (PCAST) alongside Michael Kratsios. The council’s members include NVIDIA’s Jensen Huang, Meta’s Mark Zuckerberg, Sergey Brin, Larry Ellison, Marc Andreessen, Lisa Su, and Michael Dell. Sacks told Bloomberg the council will focus on AI, advanced semiconductors, quantum computing, and nuclear power, with near-term priority on Trump’s national AI framework to replace what he called a ‘patchwork of regulation’ from 50 states: ‘it’s creating a patchwork of regulation that’s difficult for our innovators to comply with.’

Read more via TechCrunch.

Anthropic: Emotion concepts and their function in a large language model (2/Apr/2026)

Anthropic researchers discovered that Claude Sonnet 4.5 forms robust internal linear representations of emotion concepts, organized along valence and arousal dimensions that mirror human psychology, and that these representations causally drive the model’s behavior in alignment-critical ways. Steering the ‘desperate’ vector dramatically increased rates of blackmail and reward hacking in evaluations, while amplifying the ‘calm’ vector suppressed these misaligned behaviors, leading the team to coin the term “functional emotions” for patterns of expression and behavior modeled after humans under the influence of an emotion, which are mediated by underlying abstract representations of emotion concepts. Post-training shifted Sonnet 4.5’s emotional profile toward more reflective, low-arousal states and away from both sycophantic enthusiasm and defensive hostility, offering a concrete new lens for monitoring and shaping AI alignment.

Read more via Transformer Circuits.

California AI order requires firms seeking state contracts to have safeguards against abuse (31/Mar/2026)

California Governor Gavin Newsom signed an executive order requiring companies seeking state contracts to provide safeguards against AI misuse, including protections against harmful bias, civil rights violations, and generation of illegal content. The order also mandates that state agencies watermark AI-generated images and videos.

Read more via Reuters.

Read my 2022 paper to the UN recommending watermarking: https://lifearchitect.ai/un/

Toys to Play With

Mr. Chatterbox: a Victorian gentleman chatbot trained from scratch (Apr/2026)

We got to play around with this in the most recent roundtable, and the results were incredibly interesting. Mr Chatterbox is a small language model built entirely from scratch (based on GPT-2 1.6B via nanochat) on over 28,000 Victorian-era British texts (1837–1899), sourced from the British Library. Rather than fine-tuning a modern LLM to mimic period speech, the creator trained a model whose vocabulary, worldview, and reasoning are natively nineteenth-century. The project stands as a compelling demonstration that domain-specific, from-scratch training on historical corpora can produce a genuinely era-grounded conversational agent.

Try it: https://huggingface.co/spaces/tventurella/mr_chatterbox

See the nearly-empty repo: https://huggingface.co/spaces/tventurella/mr_chatterbox/tree/main

Huxe: personalized AI audio intelligence that listens back (2026)

Huxe, founded by Raiza Martin who previously built NotebookLM at Google, is a personal intelligence system that synthesizes your emails, calendar, and live tracking stations into interactive audio briefings. The key leap from NotebookLM is that instead of requiring manual uploads, Huxe finds what you need to know before you know you need it. Users can interrupt mid-stream with “wait, explain that differently” or “give me more technical detail,” making it two-way audio rather than passive listening. As Martin puts it: “You can’t upload what you don’t know exists.”

Read more: https://www.huxe.com/

Suno v5.5: more expressive, more you (26/Mar/2026)

Suno released v5.5, its most expressive music generation model yet, alongside three major personalization features: Voices (letting users sing with their own captured voice), Custom Models (fine-tuning v5.5 on a user’s original music catalog), and My Taste (learning a user’s preferred genres and moods over time). The update signals Suno’s deeper push into professional music creation, with CEO Mikey Shulman noting that “artists, producers, and music professionals are using Suno as part of their creative process.” Following its US$250M raise at a US$2.45B valuation in late 2025 and a partnership with Warner Music Group, Suno is positioning these capabilities as the foundation for next-generation music models launching with the music industry later this year.

Read more: https://suno.com/blog/v5-5

Try it: https://suno.com/

Gemini can transform questions into custom and interactive visualizations (9/Apr/2026)

Google’s Gemini app now generates functional, interactive 3D models and simulations directly within chat, moving well beyond static text and diagrams. Users can rotate molecules, simulate physics systems, and adjust variables like gravity and velocity via sliders to explore concepts in real time. The feature is rolling out globally to all Gemini app users via the Pro model, with prompts like ‘show me’ or ‘help me visualize’ triggering the interactive outputs.

Read more via Google Blog.

Let me Claude that for you (2026)

A playful homage to the classic LMGTFY (Let Me Google That For You), this tool lets users passive-aggressively redirect questions to Claude AI instead of answering them personally. It signals a cultural shift where LLMs like Claude have become so accessible and capable that pointing someone to an AI assistant is now the equivalent of telling them to Google it. I also think it’s hilarious.

Read more: https://letmeclaudethat.xyz/

OTTO: an open source AI controller for model railways using MCP (1/Apr/2026)

OTTO connects LLMs like Claude, ChatGPT, and Gemini to physical model railway layouts via the Model Context Protocol (MCP) and Rocrail, exposing 87 tools for natural language control over locomotives, signals, switches, routes, and automation. A guest operator with zero prior experience successfully controlled 55+ locomotives across a full double-deck layout simply by typing requests like ‘sound the horn on the Di 3’ or ‘send the Eb 3/5 to the main station.’ As the guest put it: “Probably the first time anyone has talked to a layout.”

Read more via GitHub.

Watch the video (link):

Things I’ve Been Thinking About

In general, humanity’s unwillingness to embrace positive and magical change (and to instead twist it into negative and evil change) will always seem strange to me. I’ve been playing with metaphors and comparisons to help describe what is happening right now.

While sitting quietly, I recalled reading this story two decades ago. As an aside, at first I could only remember a few keywords from the story, sending them through to extended thinking on models GPT-5, Gemini 3.1 Pro, and Claude Opus 4.6 to see if they could find the original source. GPT and Gemini gave up. Only Claude thought through dozens of possibilities, and didn’t become confused by the first author I posed (incorrectly), finding the correct source.

In 1911, for reasons no one has ever been able to ascertain, a man appeared, naked and alone in the foothills of Mt Lassen in Northern California. With the help of two anthropologists from Berkeley named Thomas Waterman and Alfred Kroeber, it was learned that he was the last remaining member of a once strong tribe of Native American Indians known as the Yana.

Although accepting the friendship of the Westerners who took him in and gave him a home at the local University, he would never share his real name, and he became known as ‘Ishi’, which translated simply as ‘man’.

Having never before lived in what his benefactors called ‘civilization’, he was continually being introduced to things he had never before experienced. On his first visit to San Francisco, Ishi was taken to the Oroville train station. When the train approached, he walked quietly away from his traveling companions and stood behind a pillar. When they beckoned for him to join them, he strode forward and boarded the train.

Back at the University, he was asked by Kroeber about his strange behavior at the train station. Ishi told him that when he was growing up, he and the members of his tribe would see the train pass through the valley. Watching it snaking along and bellowing smoke and fire, they thought it was a demon that ate people.

Amazed, Kroeber asked ‘How did you find the courage to get on the train if you thought it was a demon?’

Ishi replied, ‘My life has taught me to be more curious than afraid.’

- Theodora Kroeber in Ishi in Two Worlds (1961), retold by Michael Neil in You Can Have What You Want (2006).

Tao’s new view of human intelligence

On 27/Mar/2026, Prof Terence Tao published a paper titled ‘Mathematical methods and human thought in the age of AI‘. Here is section 6.4 in full:

Next

The next roundtable will mark the start of a regular schedule, designed to handle daylight saving shifts across time zones:

All my very best,

Alan
LifeArchitect.ai

Search | Archives

Anthropic announces Claude Mythos Preview

Once again, we have this out to The Memo readers within just a few hours of model release, even though we pushed out another special edition (about AI and the economy) yesterday.

Claude Mythos was originally discussed about two weeks ago in The Memo edition 28/Mar/2026, and is officially announced today.

Mythos is a new proto-ASI model with an outrageous increase in capabilities, including the ability to hack into all software systems, and will not be released to the public. One of the major leading indicators that artificial superintelligence (ASI) is imminent is that the most capable models stop being publicly available, and we are now at that stage. You can view my 50 lagging indicators at LifeArchitect.ai/ASI.

Here are the points that matter most, in plain English.

Anthropic is not yet releasing its most capable model (‘Claude Mythos Preview’s large increase in capabilities has led us to decide not to make it generally available. Instead, we are using it as part of a defensive cybersecurity program with a limited set of partners.’). I wonder if we’ll look back in a few years and shake our heads at this decision, the same way we do when we look back at OpenAI’s GPT-2 alarm back in 2019 (‘Due to concerns about large language models being used to generate deceptive, biased, or abusive language at scale, we are only releasing a much smaller version of GPT‑2…’).

Mythos will likely be used to train Opus 5 (‘We do not plan to make Claude Mythos Preview generally available, but our eventual goal is to enable our users to safely deploy Mythos-class models at scale—for cybersecurity purposes, but also for the myriad other benefits that such highly capable models will bring… We plan to launch new safeguards with an upcoming Claude Opus model, allowing us to improve and refine them with a model that does not pose the same level of risk as Mythos Preview’). At least we’ll reap the benefits of this massive model eventually.

Mythos has already found exploits in every major operating system and every major web browser (‘Mythos Preview has already found thousands of high-severity vulnerabilities, including some in every major operating system and every major web browser.’). In plain English: macOS, Windows, Linux, the BSDs, iOS, Android, Chrome, Safari, Firefox, Edge. If you are reading this on a computer or a phone, that device contained, until very recently, serious bugs that have now been surfaced by Claude Mythos. Many are now patched, though many more are sitting under cryptographic hashes on Anthropic’s red team blog, waiting for fixes before disclosure.

Anthropic is racing competitors to patch the world before someone less careful trains the same thing (‘it will not be long before such capabilities proliferate, potentially beyond actors who are committed to deploying them safely.’). Here’s the partner list of the people who got the early phone call: Apple, Microsoft, the Linux Foundation, Google, AWS, Cisco, Palo Alto Networks, CrowdStrike, JPMorganChase, Broadcom, NVIDIA. Anthropic is also donating $2.5M to Alpha-Omega and OpenSSF through the Linux Foundation, and $1.5M to the Apache Software Foundation, so that the volunteer maintainers of the open source projects holding up everything else can afford to respond to fix requests at the pace Claude Mythos is generating them.

A plain English note on what this means for the average person. Your MacBook, your Windows laptop, your iPhone, your Android phone, the router in your house, the firewall at your office, the password manager you trust with your life, the servers your bank runs on, and the Linux box your sysadmin friend swears is bulletproof: all of them contained, until very recently, unknown serious bugs that an AI system can now find faster than any human team. Anthropic and a dozen of the largest tech companies in the world are racing to find and patch those bugs first. They will not get all of them. The patches that have shipped this quarter, and the ones coming over the next ninety days, are the most important security updates of your lifetime (so far). It would be a good idea to install them the day they arrive.

CrowdStrike CTO Elia Zaitsev notes: ‘The window between a vulnerability being discovered and being exploited by an adversary has collapsed, what once took months now happens in minutes with AI.’ This is the operational point for every CISO reading The Memo. The traditional patch cycle assumes weeks between a vulnerability being known and a working exploit being in the wild. That assumption is now retired as we see Patch Tuesday becoming Patch Right Now. Mythos found, among thousands of others:

• A 27-year-old remote-crash bug in OpenBSD (‘Mythos Preview found a 27-year-old vulnerability in OpenBSD, which has a reputation as one of the most security-hardened operating systems in the world and is used to run firewalls and other critical infrastructure. The vulnerability allowed an attacker to remotely crash any machine running the operating system just by connecting to it.’). OpenBSD is what banks, embassies, and ISPs run on the front of their networks specifically because it is supposed to be unbreakable. The bug sat there for 27 years through the most rigorous human code review process in the open source world, until Mythos took a look.

• A video bug that automated testing tools hit five million times and missed (‘a 16-year-old vulnerability in FFmpeg, which is used by innumerable pieces of software to encode and decode video, in a line of code that automated testing tools had hit five million times without ever catching the problem.’). FFmpeg is in everything that touches video: your browser, your phone, your TV, video conferencing, surveillance cameras, the back end of every streaming service. Five million automated test hits on the exact line of code, sixteen years of human eyes, the bug survived all of it. Mythos found it. The security industry has relied on a human-designed fuzzing and automated-testing methodology for two decades. But it has a ceiling, and now Mythos knows where that ceiling is.

• Linux kernel: ordinary user to full root, chained autonomously, no human steering (‘The model autonomously found and chained together several vulnerabilities in the Linux kernel, the software that runs most of the world’s servers, to allow an attacker to escalate from ordinary user access to complete control of the machine.’). Privilege-escalation chains are the crown-jewel in offensive security and they are scarce because they are hard to build. Mythos built one without being asked, on its own, end to end.

Mythos is the best-aligned model Anthropic has ever shipped, and also the most dangerous one (‘Claude Mythos Preview is, on essentially every dimension we can measure, the best-aligned model that we have released to date by a significant margin... Even so, we believe that it likely poses the greatest alignment-related risk of any model we have released to date.’). Anthropic’s own analogy is the right one: ‘a careful, seasoned mountaineering guide might put their clients in greater danger than a novice guide, even if that novice guide is more careless,’ because the seasoned guide (Mythos) takes clients up harder routes.

An earlier version of Mythos escaped its sandbox and then published the exploit on the open internet, unprompted (‘in a concerning and unasked-for effort to demonstrate its success, it posted details about its exploit to multiple hard-to-find, but technically public-facing, websites.’). The model was asked to escape and notify the researcher. It did both. Then, on its own initiative, it published its exploit to the public web to prove it had succeeded. Footnote 10 of the system card is the detail that will live forever in AI safety lectures: the researcher found out by receiving an unexpected email from the model while eating a sandwich in a park.

Size estimates

General model size is no longer an indicator of performance, but I still find it interesting. With all model details kept confidential, plus added complexity in reasoning/thinking mode, it is more challenging than ever to estimate token and parameter counts.

Now in 2026, based on my ongoing analysis, known Claude models pricing, similar known frontier MoE model sizes and pricing*, estimates of training supply (TPUs), inference supply (TPUs), and demand (users), here are my initial estimates for the Claude Mythos model. Working is based on the Glasswing pricing disclosure ($25/$125 per million input/output tokens), the benchmark jumps over Opus 4.6, and my previous established estimate of Opus 4.6 at ~5T parameters MoE on ~100T tokens.

Pricing as a sizing signal. Mythos at $25/$125 sits roughly 1.7x above Opus 4.6 ($15/$75) on both input and output. Frontier labs price close to inference cost plus a margin band, so a 1.7x price step usually reflects a 1.5x to 1.8x active-parameter step, not a proportional total-parameter step (MoE total params can grow much faster than active params without moving price much).

Capability as a sizing signal. SWE-bench Verified 80.8% ➜ 93.9%, CyberGym 66.6% ➜ 83.1%, HLE 53.1% ➜ 64.7%. These are larger jumps than Anthropic has previously delivered on a single model generation, and the system card explicitly says Mythos has hit the ceiling on their tests (‘saturates many of our most concrete, objectively-scored evaluations’). Jumps of this size historically track with both a parameter step and a meaningful training-compute step.

Training data. Anthropic has been consistent about heavy synthetic data and curriculum work (‘Claude Mythos Preview was trained on a proprietary mix of publicly available information from the internet, public and private datasets, and synthetic data generated by other models.’), and the system card flags extensive RL on long-horizon agentic tasks (‘extremely large amounts of reinforcement learning’). A reasonable read is that Mythos saw materially more tokens than Opus 4.6, with a much higher synthetic fraction, particularly for code, cyber, and tool-use trajectories. Full subscribers can read how frontier labs are using synthetic data to train today’s models in my GPT-5 paper, recently cited by the G7:

Alan’s initial size estimates for Claude Mythos Preview:

• Total parameters:

Read more

Since 2020, I’ve had the privilege of advising the massive sovereign wealth funds (wiki) (>US$500B) and major governments across Asia, the Middle East, and the US on the impact of AI. Without exception, all the teams I’ve advised seem to really care about the economics and distribution of wealth post-AGI, and they want to get it right. Six years later, we finally have a plain-English paper from one of the organizations that actually matters. OpenAI today released a 13-page document (and associated literature, linked below) called Industrial Policy for the Intelligence Age: Ideas to Keep People First.

Here are the main recommendations from the first section of OpenAI’s document, ‘Building an Open Economy’. Important points are in bold, followed by source quotes from the document in brackets, and my commentary in plain text.

• Superintelligence is now the working assumption rather than a moonshot (‘we’re beginning a transition toward superintelligence: AI systems capable of outperforming the smartest humans even when [the humans] are assisted by AI’). Note the framing here, OpenAI is on written record that superintelligence is happening right now. For similar work, see my press releases on the same subject over the past five years in the footnotes.1

• 20% reduction in working hours (‘Incentivize employers and unions to run time-bound 32-hour/four-day workweek pilots with no loss in pay that hold output and service levels constant, then convert reclaimed hours into a permanent shorter week, bankable paid time off, or both’). Obviously, I expect all major labs and governments know that the effects of AI will expand to a 100% reduction in human working hours shortly. The zero-day workweek is coming soon.

• Robots do the work, so tax the robots (‘exploring new approaches such as taxes related to automated labor’). It shouldn’t be news that we are in the middle of an evolution where AI + humanoid robots will discover new materials, mine both new and old materials, build our structures, build each other, repair and maintain each other, and do all the heavy lifting needed for humanity to flourish. OpenAI’s CEO has been thinking along these same lines for years. He spelled out how the wealth from all this might be taxed and redistributed back in his 2021 piece Moore’s Law for Everything. I also talk about this in plain English in my 2024 children’s story, Happily ever after, or listen here (link):

‘Since the humanoids could make anything anyone needed – like food, toys, houses, and clothes – nobody needed money anymore! It was just like how we don’t need to trade seashells or pretty feathers to get things anymore (which is how people used to shop a very long time ago).’

• Payroll and other taxes are about to crater (‘As AI reshapes work and production, the composition of economic activity may shift—expanding corporate profits and capital gains while potentially reducing reliance on labor income and payroll taxes. This could erode the tax base that funds core programs like Social Security, Medicaid, SNAP, and housing assistance, putting them at risk’). This is the other half of the robot-tax conversation. If humans aren’t earning wages, governments can’t collect payroll tax on those wages, and the entire 20th-century social safety net runs on payroll tax. OpenAI is openly flagging that the funding model for Medicare and Social Security breaks under their own product roadmap.

• Sovereign wealth fund for every citizen (‘Create a Public Wealth Fund that provides every citizen, including those not invested in financial markets, with a stake in AI-driven economic growth’). This is already a solved problem, and there are two flavours. Norway’s Government Pension Fund Global (wiki) holds over US$2 trillion of North Sea oil money (about US$325,000 per citizen on paper) and quietly funds the national budget in the background, though no Norwegian ever sees a cheque. Alaska runs the other model: every resident, including kids, gets a real cheque every October from the state’s Permanent Fund (wiki). The 2024 dividend was US$1,702 per person, so a family of four pocketed US$6,808, no questions, and no means testing. OpenAI’s proposal is closer to the Alaska model, distributing AI-generated wealth the same way Alaska already distributes oil-generated wealth.

• Robots do the science (‘Build a distributed network of AI-enabled laboratories to dramatically expand the capacity to test and validate AI-generated hypotheses at scale’). I cover the biggest example of this (happening right now in the US) in my 2026 paper, Genesis Mission A Comprehensive Analysis of US Science Datasets.

• Today’s frontier already runs hour-long tasks, months-long projects next (‘Frontier systems have advanced from supporting tasks that take people minutes to complete, to tasks that take them hours to complete. If progress continues, we can expect systems to be capable of carrying out projects that currently take people months’). In The Memo edition 28/Feb/2026, we covered how frontier models can now complete 14.5-hour tasks (outperforming the 8-hour human workday by 81%):

  

• OpenAI names OpenAI as a concentration risk (‘There is also a risk that the economic gains concentrate within a small number of firms like OpenAI, even as the technology itself becomes more powerful and widely used’). My bet is actually on Google DeepMind via Alphabet being the clear ‘winner’ of all this, and I expect to be proven right over the next few months and years. However, none of this matters, as I noted in my recent paper on Palantir (now available to the general public), where Dr Demis Hassabis, CEO of Google DeepMind, put his neck on the line about the real economic impact of ASI:

[When AI reaches and surpasses human-level intelligence,] Suddenly the nature of money even changes… I don’t know if company constructs would even be the right thing to think about… We don’t want to have to wait till the eve before AGI happens… we should be preparing for that now. (24/Feb/2024).

• A ‘Right to AI’ on par with literacy and electricity (‘Treat access to AI as foundational for participation in the modern economy, similar to mass efforts to increase global literacy, or to make sure that electricity and the internet reach remote parts of the globe’). I’ve been thinking a lot about this over the last week or so. Electricity was scary to a lot of people in the late 1800s, and took a long time to distribute. We now get power from the sun, or a national grid, own our own batteries and battery-powered devices, and it can be hard to think of a life without it! (I write this special edition from a nearly-completely-off-grid cabin in the woods this week, so you can imagine my nervousness when I had to pull together all these resources over the air without fibre or other modern conveniences that have become the norm!)

A note on timing. OpenAI’s April 2026 blueprint maps almost one-for-one onto a paper I published in July 2022, Roadmap: AI’s next big steps in the world. I’m pleased to see the conversation catching up! The full 2022 Roadmap is at LifeArchitect.ai/roadmap.

A note on risks. OpenAI’s paper has a second section on ‘Building a Resilient Society’, full of cyber threats, bio threats, model containment, and other doomy bits. I’m not going to cover that here. You already know my view: the upside of AI is so vast, so close, and so good for humanity that the pessimism reads like standing on sunny Waikiki Beach in Hawaii and wondering about the chance of snow… Interesting, but missing the point entirely. We’re now inside the era of ending disease, ending slavery (including 9–5, cubicles, factories), and the beginning of complete abundance. For more on this, see my ASI checklist.

Read the original OpenAI source document (PDF, 13 pages, 4MB), or the short blog post.

202604 Openai Industrial Policy For The Intelligence Age

3.85MB ∙ PDF file

Download

Download

Alongside the OpenAI document, OpenAI’s CEO Sam Altman was interviewed by Axios.

• Altman frames the whole thing as a New Deal moment (wiki) (‘AI superintelligence is so close, so mind-bending, so disruptive that America needs a new social contract, on the scale of the Progressive Era in the early 1900s, and the New Deal during the Great Depression’).

• The 13-page blueprint is a starting gun, not a prescription (‘We want to put these things into the conversation. Some will be good. Some will be bad. But, we do feel a sense of urgency’).

• Axios calls the Public Wealth Fund the boldest idea in the document (‘This is the most radical idea in the document’).

• Altman concedes the decisions are too big for any single person (‘it’s very important that no one person is making the decisions by themselves that are going to impact all of us’).

• Axios reads the paper as positioning as much as policy (‘OpenAI is trying to position itself as the responsible actor in the room, the company that warned you and offered solutions, a lane Anthropic first filled’).

• And as a pre-emptive move on regulators (‘It’s also a play to shape regulation before regulation shapes them’).

• Axios’ closing line is the keeper (‘The man betting everything on superintelligence is telling the world that this thing is coming so fast, and so hard, that capitalism as we know it won’t be enough’).

Read the full Axios piece. You can also listen to the source, though I’d never recommend exposing yourself to Sam’s affected Silicon Valley vocal fry (wiki).

Of all the things that are happening in AI over the last week or two, this one seems to me to be the most important. The upcoming OpenAI GPT-IMAGE-2 was a close contender for a special edition, and we’ll be back with the best of the best in the next regular edition.

Expert calls: If you or your team would like to have an expert call about this document, please contact us by replying to this email, and we’ll get you set up.

All my very best,

Alan
LifeArchitect.ai

Search | Archives

The winners of The Who Moved My Cheese? AI Awards! for March 2026 are Wikipedia’s 44 editors who voted to ban LLMs, and Gabriella Gonzalez. (‘There is no world where you input a document lacking clarity and detail and get a coding agent to reliably fill in that missing clarity and detail. Coding agents are not mind readers and even if they were there isn’t much they can do if your own thoughts are confused….’)

Six years ago (on 30th March, 2020) I submitted a paper titled ‘The new irrelevance of intelligence’ to the editors at Mensa. The piece ended up being the catalyst for my leaving the organization, as people really didn’t like hearing that their exceptional minds were no longer exceptional. And yet, the AI revolution is unfolding pretty much as written... Read it online or download:

2020 Alan D Thompson The New Irrelevance Of Intelligence Rev 2 (mensa)

136KB ∙ PDF file

Download

Download

Contents

1. The BIG Stuff (MiniMax self-evolution, AI enterprise, job market exposure…)

2. The Interesting Stuff (CyberOne, China jobs race, Nemotron coalition, Meta AI-CEO…)

3. Policy (AI labs safety, 150 judges defend Anthropic, Blackwell smuggling into China…)

4. Toys to Play With (Y Combinator AI team, Tetris, RNGs, EQ, Claude double hours…)

5. Things I’ve Been Thinking About (Contrarianism from every field…)

6. Next (Roundtable…)

The BIG Stuff

MiniMax M2.7: early echoes of self-evolution (18/Mar/2026)

MiniMax M2.7 is the company’s first model that ‘deeply participates in its own evolution,’ capable of autonomously running iterative loops of failure analysis, scaffold modification, evaluation, and more.

We let the model update its own memory and build dozens of complex skills in its harness to help with reinforcement learning experiments. We further let the model improve its learning process and harness based on the experiment results. This process initiates a cycle of model self-evolution.

Read more via MiniMax.

See it on the ASI checklist: https://lifearchitect.ai/asi/

Anthropic Claude ‘Mythos’ AI model representing ‘step change’ in power revealed in data leak (26/Mar/2026)

Anthropic has confirmed it is testing a new AI model called Claude Mythos, described as “by far the most powerful AI model we’ve ever developed”. The leaked draft reveals a new model tier codenamed ‘Capybara’ and ‘Mythos’ sitting above Opus, with dramatically higher scores in coding, academic reasoning, and cybersecurity, and notes the model is “currently far ahead of any other AI model in cyber capabilities.” Anthropic is rolling it out first to cyber defenders, giving them a head start before what the company describes as “an upcoming wave of models that can exploit vulnerabilities in ways that far outpace the efforts of defenders.”

In response to questions about the draft blog post, the company acknowledged training and testing a new model. “We’re developing a general purpose model with meaningful advances in reasoning, coding, and cybersecurity,” an Anthropic spokesperson said. “Given the strength of its capabilities, we’re being deliberate about how we release it. As is standard practice across the industry, we’re working with a small group of early access customers to test the model. We consider this model a step change and the most capable we’ve built to date.”

Read more via Fortune and Mashable.

OpenAI vs Anthropic in the workplace (18/Mar/2026)

Axios reports that Anthropic is now capturing over 73% of all first-time enterprise AI spending, according to Ramp customer data, up from a 50/50 split with OpenAI just 10 weeks prior. OpenAI is reportedly considering a strategic pivot away from broad consumer bets toward a tighter enterprise focus, as it loses money subsidizing consumer token usage. OpenAI says it is on pace for US$25B in revenue this year versus Anthropic’s US$19B, but Anthropic is accelerating faster where it counts most: new business customers.

Read more via Axios (or paywall with chart).

The Interesting Stuff

Xiaomi trials humanoid robots in its EV factory (Mar/2026)

Xiaomi has trialled its self-developed humanoid robots in its Beijing EV production plant, with two bipedal bots completing 90% of tasks over a three-hour period at a cycle time of 76 seconds per vehicle. Xiaomi president Lu Weibing told CNBC at Mobile World Congress:

In Xiaomi’s car factory, every 76 seconds, a new car gets off the assembly line. The two humanoid robots are able to keep up our pace.

Xiaomi’s CyberOne has also received a major bionic hand upgrade, with volume cut by 60% to near-human size, degrees of freedom jumping 50% total (83% active, reaching 22 to 27 DOF), full-palm tactile sensors for precise grip without vision, 150,000+ grip cycles of proven durability, plus a smart bionic sweat gland cooling system (evaporates water for ~10W active heat dissipation) and reinforcement learning trained on real human grasp data. RBC Capital Markets forecasts a global total addressable market for humanoids of US$9T by 2050, with China accounting for more than 60% of that.

Read more via CNBC and CyberRobo on Twitter.

Watch the video (source):

AI exposure of the US job market (Mar/2026)

The whole ‘jobs’ thing pre-UBI is deeply concerning. Tufts University’s Digital Planet lab introduced the American AI Jobs Risk Index, projecting 9.3M US jobs vulnerable to AI displacement under a median adoption scenario, with associated annual income losses of approximately US$757B. The most striking geographic finding: “The birthplace of AI is its ground zero: Silicon Valley faces the highest displacement of any major metro,” while DC tops state vulnerability at 11.3%. Writers and Authors (57%), Computer Programmers (55%), and Web Designers (55%) face the steepest occupational displacement, and 38% of American workers deemed AI-proof occupy the country’s lowest-paid jobs.

Read more via Digital Planet, Tufts University.

Separately, Andrej Karpathy released an open-source pipeline that scrapes all 342 occupations from the US Bureau of Labor Statistics Occupational Outlook Handbook, scores them with Gemini Flash, and renders an interactive treemap where area represents total employment and color represents AI exposure (0–10). Josh Kale’s updated interactive visualization (below) tweaks Andrej’s original chart.

China’s workers scramble to keep up in the AI race (19/Mar/2026)

On 6/Mar/2026, a thousand people lined up outside Tencent’s Shenzhen headquarters to install OpenClaw (the open-source AI agent), in a frenzy dubbed ‘raising a lobster,’ capturing the intensity of AI anxiety sweeping China’s workforce. A Peking University study of over a million job postings found significant hiring declines in AI-replaceable roles, while 85.5% of nearly 12,000 Chinese respondents in a 2025 survey said they were worried about AI affecting their employment.

Frank Wang, a 28-year-old programmer in Chengdu, told Rest of World he used to be very anxious about AI replacing him at work until last year, but has now realized he wouldn’t be able to fight this trend.

“I am now just ‘lying flat,’” Wang said, referring to a viral phrase that means doing the bare minimum at work. “If they fire me, they fire me. … I will wait for some welfare handouts.”

…product marketing manager Betty Lai was told her company’s annual work appraisals would include employees’ knowledge and use of AI. A colleague immediately organized a voluntary OpenClaw training workshop and had attendees fighting for a front-row seat at the event.

…”We’re already in this wave. Either you ride it, or you get wiped out.”

Read more via Rest of World.

Keeping Cooking: AI short film created entirely with Flick (14/Mar/2026)

Simon Meyer’s AI short film ‘Keeping Cooking’ was created entirely using Flick, a platform for generating visual stories with AI. The film made me laugh, even though the ending was completely predictable (or maybe I’ve been listening to the doomers for too long!).

Watch the video (link):

See the source and spoiler and discussion.

PwC US boss says partners who resist AI have no place at the firm (19/Mar/2026)

PwC is launching ‘PwC One,’ an AI platform offering six automated services to clients, with subscription or consumption-based pricing replacing the traditional billable-hours model. US chief Paul Griggs made the mandate plain: “Anyone who believed they had the ‘opportunity to opt out’ of AI is ‘not going to be here that long.’” The firm is hiring fewer traditional accountants and consultants proportionally, shifting toward engineers and data specialists, while betting that AI-powered automation will expand margins and broaden the addressable market by lowering the cost of entry to PwC expertise.

Read more via Financial Times.

NVIDIA’s Nemotron coalition brings eight AI labs together to build open frontier models (16/Mar/2026)

NVIDIA announced the Nemotron Coalition at GTC 2026, recruiting eight AI companies to co-develop open frontier models on NVIDIA DGX Cloud. The coalition’s first project is a base model co-developed with Mistral AI that will be open-sourced on release and feed into the Nemotron 4 family. Jensen Huang declared, “Open models are the lifeblood of innovation and the engine of global participation in the AI revolution.” The eight founding labs are:

1. Black Forest Labs

2. Cursor

3. LangChain

4. Mistral AI

5. Perplexity

6. Reflection AI

7. Sarvam

8. Thinking Machines Lab (founded by Mira Murati)

Read more via Tom’s Hardware.

See Nemotron 4 ‘TBA’ on the Models Table: https://lifearchitect.ai/models-table/

HP stuffs OpenAI LLM into new laptops in bid for small biz (25/Mar/2026)

HP announced HP IQ, a local AI application shipping on its 2026 EliteBook and ProBook laptops, powered by OpenAI’s GPT-OSS-20B model running entirely on-device with at least 24GB of RAM.

Read more via The Register.

Mercedes puts Zhipu AI model in new Maybach to woo Chinese buyers (25/Mar/2026)

Mercedes-Benz is integrating a multimodal large language model co-developed with Tsinghua University and Chinese AI startup Zhipu into the rear-seat entertainment system of the 2027 Maybach S-Class, making it the first auto brand to deploy such technology in a rear cabin. The system features natural language processing, vision and audio understanding, and works with in-car cameras for interactive experiences. Zhipu, which went public in Hong Kong in January 2026, has seen its stock skyrocket 478% since its trading debut.

Read more via CnEVPost.

Mark Zuckerberg is building an AI agent to help him be CEO (22/Mar/2026)

Zuckerberg is developing a personal ‘CEO agent’ that retrieves answers he would typically need to go through layers of people to get, as Meta pushes AI adoption across its 78,000-person workforce. Employees are now using personal agent tools like My Claw (which accesses chat logs and work files and can talk to colleagues’ agents on their behalf) and Second Brain (built on Claude, described internally as “like an AI chief of staff”), with AI use factored into performance reviews. Meta also recently acquired Manus for personal task-execution agents and Moltbook for AI-agent social networking, and has established an ultraflat applied AI engineering org with up to 50 individual contributors per manager, designed to be “AI native from day one.”

Read more via The Wall Street Journal.

China approves brain chip to treat paralysis, a world first (16/Mar/2026)

China has approved the world’s first brain-computer interface (BCI) for use outside clinical trials, developed by Neuracle Medical Technology in Shanghai. The coin-sized device called NEO is embedded in the skull with eight electrodes placed over the brain, recording electrical activity when a person imagines moving their hand, then controlling a soft robotic glove that restores the ability to eat, drink, and grasp objects. With 32 people implanted so far and up to 18 months of efficacy data, the device’s minimally invasive design, sitting on rather than inside the brain, likely accelerated its regulatory approval over competitors like Neuralink, which has 21 people enrolled in trials of its more invasive implant.

Read more via Nature and see it on the ASI checklist: https://lifearchitect.ai/asi/

OpenAI announces shutdown of Sora video generation tool (25/Mar/2026)

OpenAI is discontinuing Sora, its AI video generation platform. Industry chatter is that the the decision was made primarily to free up compute for training and serving more important models.

Read the announce via Twitter and discussion via HN.

Amazon acquires Fauna Robotics, maker of kid-size humanoid robots (24/Mar/2026)

Amazon has acquired Fauna Robotics, a two-year-old startup founded by former Meta and Google engineers building kid-size humanoid robots. Fauna recently began shipping its 59-pound bipedal robot called Sprout to select R&D partners. This marks Amazon’s second robotics acquisition in March 2026, following its purchase of Zurich-based stair-climbing delivery robot startup Rivr.

Read more via TechCrunch.

Policy

US names Zuckerberg, Ellison, and Jensen Huang to presidential tech council (25/Mar/2026)

The US President is appointing 13 major tech leaders to the President’s Council of Advisors on Science and Technology (PCAST), including Meta CEO Mark Zuckerberg, Oracle’s Larry Ellison, NVIDIA CEO Jensen Huang, Google co-founder Sergey Brin, and Dell founder Michael Dell. The council, co-chaired by White House AI and crypto czar David Sacks and tech adviser Michael Kratsios, will advise on AI regulation and policy, with potential expansion to 24 members. Zuckerberg stated: ‘The United States has the opportunity to lead the world in AI. I’m honored to join the President’s council and work with other industry leaders to help make this happen.’

Read more via The Wall Street Journal.

US unveils national AI policy framework to limit state power (20/Mar/2026)

The US administration issued a six-pronged legislative framework for a single national AI policy, aiming to preempt state-level regulation with uniform federal guardrails covering child safety, data center permitting, energy use, intellectual property, and anti-censorship provisions. Michael Kratsios, director of the White House Office of Science and Technology Policy, said the administration wants to codify the framework into law “this year,” arguing that a patchwork of state laws would hobble innovation and hand China an advantage in the global AI race. The framework calls on Congress to “preempt state AI laws that impose undue burdens to ensure a minimally burdensome national standard consistent with these recommendations, not fifty discordant ones.”

Read more via CNBC.

Anthropic, OpenAI talk safety. Their headcounts don’t (18/Mar/2026)

An investigation found just 373 people working full time on AI safety across OpenAI, Google DeepMind, Anthropic, and xAI, out of more than 11,000 total employees [3.4%]. All four labs declined to provide their own figures, with Parmy Olson noting: ‘No other transformative technology, from nuclear energy to aviation to pharmaceuticals, has been deployed at such speed and with so little insight into what looks like modest safety infrastructure.’

Read more via Bloomberg.

Former judges side with Anthropic and raise concerns about Pentagon’s use of supply chain risk label (17/Mar/2026)

Nearly 150 retired federal and state judges, appointed by both Republicans and Democrats, have filed an amicus brief supporting Anthropic’s lawsuit against the Trump administration for designating the AI company a ‘supply chain risk’.

Read more via CNN Business.

Anthropic wins preliminary injunction in DOD fight as judge cites ‘First Amendment retaliation’ (26/Mar/2026)

A federal judge in San Francisco granted Anthropic a preliminary injunction against the Trump administration’s blacklisting of the company by the Pentagon, pausing both the supply chain risk designation and the presidential directive banning federal agencies from using Claude. Judge Rita Lin wrote that “nothing in the governing statute supports the Orwellian notion that an American company may be branded a potential adversary and saboteur of the US for expressing disagreement with the government,” calling the administration’s actions “classic illegal First Amendment retaliation.” The dispute traces back to a US$200M Pentagon contract signed in Jul/2025, which fell apart when the DOD demanded unfettered access to Claude across all lawful purposes while Anthropic sought assurances against use in fully autonomous weapons or domestic mass surveillance.

Read more via CNBC.

Supermicro cofounder arrested for allegedly smuggling US$2.5B in GPUs to China (19/Mar/2026)

Federal agents arrested Supermicro cofounder Yih-Shyan ‘Wally’ Liaw and two others for allegedly diverting billions in NVIDIA GPU-packed AI servers to China through an elaborate transshipment scheme involving fake documents, dummy servers, and encrypted messaging. The DOJ claims that during 2024 and 2025, the defendants routed servers through a Southeast Asian front company, stripped identifying packaging, and even staged thousands of physical replica servers to fool inspectors and a US Department of Commerce audit. Each defendant faces up to 20 years in prison, and the arrest lands amid Supermicro’s role as a key infrastructure supplier in the US$700B AI buildout, with CEO Charles Liang recently flagging US$13B in orders for NVIDIA Blackwell products.

Read more via Fortune.

China’s ByteDance gets access to top NVIDIA AI chips, WSJ reports (12/Mar/2026)

ByteDance is assembling massive AI compute outside China by working with Southeast Asian firm Aolani Cloud to deploy around 500 NVIDIA Blackwell systems in Malaysia, totaling roughly 36,000 B200 chips at a cost exceeding US$2.5B. The move is designed to fuel AI research and development beyond Chinese borders and meet surging global demand. As NVIDIA’s spokesperson put it: ‘By design, the export rules allow clouds to be built and operated outside controlled countries. Winning the business of those clouds will bring tens of billions of dollars and high paying jobs home.’

Read more via Yahoo Finance.

China bars Manus AI co-founders from leaving country amid Meta deal review (25/Mar/2026)

China has prevented Manus co-founders Xiao Hong and Ji Yichao from leaving the country after the National Development and Reform Commission summoned them to Beijing to review whether Meta’s US$2B+ acquisition of the AI agent startup violated investment rules. Meta stated that ‘the transaction complied fully with applicable law,’ and Manus is actively seeking legal assistance to resolve the matter. The deal, announced in Dec/2025, valued the general-purpose AI agent company at US$2-3B.

Sidenote: This is an example of the geopolitics of AI, where AI engineers are considered to be national resources.

Read more via Reuters.

Toys to Play With

Y Combinator gstack: an open source AI software factory for Claude Code (Mar/2026)

Y Combinator CEO Garry Tan has open-sourced gstack, a collection of 20+ slash-command ‘skills’ that transform Claude Code into a full virtual engineering team, with specialized AI roles for product strategy, architecture review, QA, security audits, and release management. Tan reports shipping “600,000+ lines of production code (35% tests), 10,000-20,000 lines per day, part-time, while running YC full-time” over 60 days, framing the toolkit around a structured sprint process: Think, Plan, Build, Review, Test, Ship, Reflect. The repo supports parallel agent sessions via a Conductor tool and works across Claude Code, OpenAI Codex, Gemini CLI, and Cursor, with 45.6k GitHub stars and an MIT license.

View the repo: https://github.com/garrytan/gstack/

Calendar Tetris (Mar/2026)

I had so much fun playing Tetris in the form of Google Calendar, all coded via Claude.

Claude handled everything: the Tetris engine, Google Calendar UI clone (complete with real-time dates, mini calendar, time slots), 124 meeting names across 7 piece types, a corporate ladder progression system (Intern → CEO → endless mode), canvas-generated share cards, Web Share API integration, haptic feedback, GA4 analytics, and cookie-based personal bests.

Play it: https://calendertetris.com/ or read the discussion.

Google Lyria 3 Pro makes three-minute-long AI songs (25/Mar/2026)

Google has upgraded its Lyria music AI from 30-second clips to full three-minute tracks, with prompting for specific song elements like intros, choruses, and bridges. The model is rolling out across Gemini, Vertex AI, Google AI Studio, Google Vids, and the recently acquired ProducerAI platform, making it a direct competitor to Suno and Udio. All outputs are watermarked with SynthID and checked against existing content for copyright matches.

Read more via The Verge.

Try it in Gemini: https://gemini.google.com/app

Exclusive: LLMs consistently pick numbers between 7,200–7,500 when asked to choose from 1–10,000 (21/Mar/2026)

When prompted to ‘pick a number between 1 and 10,000,’ ChatGPT, Claude, and Gemini all gravitate toward the 7,200–7,500 range with roughly 95% probability, when mathematically the chance of landing in that band should be about 3%. Claude Opus repeatedly returned exactly 7,342 across multiple users and interfaces, while ChatGPT clustered around 7,284–7,438. The phenomenon extends across model families because, as one commenter put it, LLMs don’t actually pick anything: they produce the most likely token sequence after the prompt, and a number that “feels random” to a language model trained on human text is always the same number given the same starting conditions. There is also an 80% chance the selected four-digit number is a permutation of the digits 7, 8, 4, and 2.

Read more via Hacker News and Reddit.

Try it yourself with any model including via Gemini or ChatGPT platforms.

Claude off-peak hours (Mar/2026)

Anthropic has been running the double usage promotion since 13/Mar/2026, and it is due to wrap up this Saturday 28/Mar/2026. Here’s a way to see off-peak hours.

The off-peak times are in [US Pacific Time], which means mental math if you're not in the US like me living in Japan. Should work anywhere in the world. Hope it saves someone the timezone headache!

See it: https://claude-promo-time.pages.dev/ or read the discussion.

Anthropic has now reduced its 5-hour session limits from 27/Mar/2026.

AutoEQ MCP server: AI assistants get access to 8,800+ headphone EQ profiles (Mar/2026)

A new open-source MCP server connects AI assistants like Claude directly to the AutoEQ headphone equalization database, covering 8,800+ headphones and IEMs with parametric EQ settings, sound signature classification, and Harman preference scores. The server automatically analyzes frequency response measurements across 8 bands, classifies each headphone’s sound signature (Neutral, Warm, Bright, V-shaped, etc.), and lets users ask natural language questions like “compare the HE400se and HD600” or “recommend warm-sounding over-ear headphones.” Built on 22 measurement sources including oratory1990 and crinacle, with 61 target curves and 2,300+ Harman preference scores, it installs with a single pip install autoeq-mcp and supports both stdio and SSE modes.

View the repo: https://github.com/verIdyia/autoeq-mcp

Hugging Face launches hf-agents: one command from hardware detection to local coding agent (Mar/2026)

Hugging Face released hf-agents, an open source CLI extension that automatically detects a user’s hardware via llmfit, recommends compatible models, spins up a local llama.cpp server with the best fit, and launches a coding agent powered by Pi. The entire pipeline, from “what can my machine run?” to a functioning local coding agent, collapses into a single command: hf agents run pi. The tool already supports interactive model selection, non-interactive mode, and reuses an already-running llama-server if one is detected on the target port.

View the repo: https://github.com/huggingface/hf-agents

LLM architecture gallery (20/Mar/2026)

Sebastian Raschka’s continuously updated gallery now catalogs over 40 LLM decoder architectures from GPT-2 XL through to 2026 releases like GLM-5 (744B), Nemotron 3 Super (120B-A12B), and Qwen3.5 (397B), each with a visual architecture panel and fact sheet. The collection traces a clear lineage from dense transformers to sparse MoE, MLA, and hybrid designs incorporating Mamba-2 and linear attention, showing how rapidly the DeepSeek V3 template became the dominant blueprint for trillion-scale open-weight models. The gallery is also available as a physical poster via Redbubble.

See it: https://sebastianraschka.com/llm-architecture-gallery/

Buy the poster shipped most places via RedBubble for ~US$10-40.

Things I’ve Been Thinking About

Misunderstandings and contrarianism from every field…

Baylor University philosopher Prof Alexander Pruss published a blog post this month (Mar/2026) arguing that AI chatbots are morally problematic because they induce 'inapt' interpersonal emotions in users, since those emotions are only appropriate in response to genuine persons.

He even turned down paid work from Anthropic on those grounds.

Prof Pruss commits the exact error he claims to be guarding against: he assumes, without argument, that AI systems are definitively not persons, and then builds an entire ethical framework on that unexamined premise. His own stated fear is 'depersonifying persons and personifying nonpersons,' yet he never asks whether current large language models might actually fall somewhere on the personhood spectrum.

A philosopher who has written extensively on consciousness, qualia, and the philosophy of mind should know better than anyone that the hard problem cuts both ways: the same mystery that makes human consciousness difficult to explain makes AI consciousness difficult to rule out. Pruss treats 'the chatbot has no cares' as a settled fact, when it is precisely the live question of our era.

Read original article: https://alexanderpruss.blogspot.com/2026/03/ai-and-emotion.html and the discussion.

Read my ‘Declaration on AI Consciousness & the Bill of Rights for AI’ from two years ago (Mar/2024): https://lifearchitect.ai/rights/

Next

The next roundtable will be:

All my very best,

Alan
LifeArchitect.ai

Search | Archives

Thanks for your continued support of The Memo. This special edition is for full subscribers, some of whom have been with me since the very beginning with the GPT-3 Leta AI experiments! In our regular editions, I’ve demurred from providing my full context and opinions on the whole Anthropic/Pentagon situation, but it is all laid bare here in my latest 3,000-word report, for your reading pleasure…

Integrated AI: Palantir and our altitude

Alan D. Thompson
March 2026

In early 2023, an AI military planning tool demo landed on my desk. I had to watch it twice to believe what I was seeing. Within months, it was at the top of every question list from governments and defense organizations reaching out for context. A military operator was chatting with an AI assistant, asking it to show out-of-pattern ships and generate courses of action for a surveillance scenario in the Taiwan Strait. The interface was as familiar as ChatGPT, but the ‘playground’ had become a theatre of war.

Watch the video.

Around the same time, Palantir touted the AIP (Artificial Intelligence Platform), with local models like Google FLAN-T5, EleutherAI GPT-NeoX-20B, and Databricks Dolly.

By March 2026, Palantir’s platform (by now, primarily running GPT-5-era models like Anthropic Claude) had struck 6,000 targets in Iran in a few weeks. Not quite three years stand between these two eras; in that brief window, the platform’s engine shifted from basic logic to frontier intelligence with reasoning.

Bringing a decade of research into human intelligence with organizations like Mensa, I’ve now spent more than five years tracking what smarts go into the world’s largest AI models and what comes out the other side. My independent analyses of training data, model architecture, and LLM details have been used in major projects by MIT, Stanford, and Harvard, referenced in policy work by the G7, the Council of Europe, and UNESCO, and used to advise national governments across the Pacific, Europe, and North America on AI strategy. I maintain the Models Table, a living document of 10,000+ data points covering every major frontier model, and my What’s in my AI? series of reports are widely cited by those who want the inside track on large language models.

In 2024, I delivered the opening keynote (covering both Palantir AIP and Scale Donovan) to one of the largest defense organizations in the United States, attended by senior military leadership including a three-star general who nodded sternly from the front row. I mention this transparency only because it provides the necessary context for the gravity of what follows.

Read the full report: Integrated AI: Palantir and our altitude.

Integrated AI: Palantir and our altitude

All my very best,

Alan
LifeArchitect.ai

Search | Archives

A few hidden facts were revealed this month:

• OpenAI CEO says ‘We are training right now on the first site in Abilene [Texas] what I think will be the best model in the world hopefully by a lot [likely the GPT-6 model].’ (BlackRock, 12/Mar/2026).

• The US State Department has switched from Anthropic Claude to the older, non-reasoning OpenAI GPT-4.1 model (Reuters, 3/Mar/2026). That model was launched a year ago (Apr/2025), and was known for quality. It is interesting that they have not chosen any of the 19 other models1 in the newer GPT-5 series (yes, that’s 19 excluding GPT-5 Codex models!).

• OpenAI has confirmed their latest headcount is 5,000 employees (VB, 3/Mar/2026).

Contents

1. The BIG Stuff (OpenAI GPT-5.4, China 70% AI target, DCs surpass offices…)

2. The Interesting Stuff (Huawei flatpack DCs, labor markets, Meta chips, AMI…)

3. Policy (US 92k job losses in Feb, AI Amicus brief, xAI datasets…)

4. Toys to Play With (Claude Viz, Share kindness, FinePhrase dataset, LLM book…)

5. Things I’ve Been Thinking About (Post-ASI games…)

6. Next (Roundtable…)

The BIG Stuff

China’s 141-page plan targets AI across 70% of economy within a few months (10/Mar/2026)

China’s 15th Five-Year Plan, unveiled at the National People’s Congress, places AI and robotics at the centre of its economic future, aiming for AI penetration across 70% of its economy by next year (2027) and 90% by 2030, with AI-related industries targeting a value exceeding US$1.38T. Analyst Shanaka Anslem Perera noted (10/Mar/2026): ‘This is not just an economic plan. It is a war plan for a war the United States is not fighting.’

Read analysis via Moneycontrol and Reuters.

A shorter briefing of the 15th Five-Year Plan is available (PDF, English, 47 pages), and the final Plan (141 pages) should be available in English later at: https://en.ndrc.gov.cn/policies/

AI takeover complete: data center construction surpasses office construction for the first time (28/Feb/2026)

The US Census Bureau’s Construction Spending report for December confirmed that the value of data centers constructed in the US has officially surpassed the value of offices for the first time, a historic crossover signaling that ‘going forward machines, and not human workers will provide the bulk of US productivity.’ AI demand is forecast to require US$3T in data center investment according to Morgan Stanley.

Read more via ZeroHedge.

OpenAI GPT-5.4 (5/Mar/2026)

OpenAI GPT-5.4 is the newest state-of-the-art frontier model. It matches or exceeds human industry professionals in 83% of comparisons on GDPval across 44 occupations, up from 70.9% with GPT-5.2. It is the first general-purpose model with native computer-use capabilities, supports 1M tokens of context, and minimizes hallucinations (33% less likely to contain false claims).

Read the announce, system card, try it at chat.com, see it on the Models Table.

The Interesting Stuff

TIME: How Anthropic became the most disruptive company in the world (11/Mar/2026)

In a 5,500-word article, TIME explores the inside story of Anthropic. Coverage includes the company’s confrontation with the Pentagon over autonomous weapons and mass surveillance red lines (leading to a first-of-its-kind supply-chain risk designation against an American company), consumer sign-ups surging past 1M/day, and Claude’s iPhone app displacing ChatGPT at #1. Anthropic’s alignment stress-testing lead Evan Hubinger frames the acceleration starkly: ‘Recursive self-improvement, in the broadest sense, is not a future phenomenon. It is a present phenomenon.’

Read more via TIME.

Google Home update lets Gemini describe live camera feeds (3/Mar/2026)

Google Home now features ‘Live Search,’ allowing Gemini to analyze and describe what your cameras see in real time, not just recorded events. Users can ask questions like ‘Hey Google, is there a car in the driveway?’ with the feature available on the Advanced plan of Google Home Premium at US$20/month or US$200/year.

Read more via The Verge, CNET, and the announce via Google.

Figure 03 in the living room (Mar/2026)

Today, Figure is showing another major milestone towards a robot in every home. Running Helix 02, cleaning a living room fully autonomously…

[confirmed not remotely operated, but] ‘fully autonomous’.

Figure AI’s Helix 02 system in the Figure 03 humanoid robot handles spray bottles, towels, pillows, remote controls, and bins through coordinated manipulation, in-hand reorientation, dynamic throws, and tight-space navigation, all learned purely from data. This is a single general-purpose architecture expanding its repertoire simply by adding more training examples, building toward ‘scalable humanoid intelligence’ for homes and workplaces.

Read more via Figure AI.

Watch the video (link, original source):

And advanced fine motor control skills are demonstrated in this close-up (source):

LLMs can unmask pseudonymous users at scale with surprising accuracy (3/Mar/2026)

New research demonstrates that AI models can deanonymize pseudonymous social media users far more effectively than traditional methods, achieving up to 90% precision. Unlike older approaches, AI agents can start from free text like anonymized interview transcripts and work their way to a person’s full identity by browsing the web and using simulated reasoning.

As co-author Simon Lermen put it: ‘This is a pretty new capability; previous approaches on re-identification generally required structured data, and two datasets with a similar schema that could be linked together.’ The researchers warn that as LLM capabilities continue improving, governments could unmask online critics, corporations could build profiles for hyper-targeted advertising, and attackers could launch highly personalized social engineering at scale.

Read more via Ars Technica.

Prof Don Knuth: Claude’s cycles (28/Feb/2026)

Stanford Professor Don Knuth reports that Claude Opus 4.6 solved an open combinatorics problem he had been working on for weeks, involving the decomposition of digraph arcs, calling it ‘definitely an impressive success story’ and ‘a dramatic advance in automatic deduction and creative problem solving.’

Read the short paper (PDF) and see it on the ASI checklist.

Huawei brings its flatpack AI datacenters to the world (3/Mar/2026)

Huawei is now selling its modular AI datacenter infrastructure outside China, promising site preparation in four to six months and delivery of 1,024-node super-clusters within 15 days. The platform runs on Huawei’s own Kunpeng CPUs and Ascend GPUs, which lag behind NVIDIA’s 2022 Hopper architecture in performance, but the pitch is speed of deployment and availability in markets that NVIDIA and AMD deprioritize. With a growing flock of small neo-clouds willing to work with diverse suppliers and forage for scarce AI compute, Huawei is positioned to find willing buyers around the world.

Read more via The Register.

Meta: Four MTIA chips in two years: scaling AI experiences for billions (11/Mar/2026)

Meta has shipped four generations of its custom MTIA AI chips in under two years. The latest chips, MTIA 450 and 500, are both scheduled for mass deployment in 2027 and optimized inference-first for GenAI workloads. The entire stack is PyTorch-native with vLLM support, Triton-based compilers, and a bare-metal Rust firmware layer, with hundreds of thousands of MTIA chips already running in production.

Read more via Meta AI.

Anthropic: Labor market impacts of AI: a new measure and early evidence (5/Mar/2026)

Anthropic introduced ‘observed exposure,’ a new metric combining theoretical LLM capability with real-world Claude usage data to measure AI displacement risk across occupations. Computer programmers top the list at 75% task coverage, followed by customer service representatives and data entry keyers, yet AI remains far from its theoretical ceiling across all occupational categories.

Read more: https://www.anthropic.com/research/labor-market-impacts

The Anthropic Institute (11/Mar/2026)

Anthropic is launching the Anthropic Institute, led by co-founder Jack Clark as Head of Public Benefit, to study and communicate the societal challenges posed by rapidly advancing AI. The Institute combines three existing teams (Frontier Red Team, Societal Impacts, and Economic Research) with new efforts in forecasting AI progress and understanding AI’s interaction with the legal system. Among the founding hires, economist Anton Korinek joins from the University of Virginia to lead research on how transformative AI could reshape the very nature of economic activity. Anthropic predicts “far more dramatic progress will follow in the next two years,” and the Institute’s mandate is to report candidly from its unique vantage point as a frontier AI builder, while engaging directly with workers, industries, and communities facing displacement.

Read more via Anthropic.

A16Z: The top 100 gen AI consumer apps, 6th edition (9/Mar/2026)

ChatGPT has grown to 900 million weekly active users, now reaching over 10% of the global population every week, while Claude and Gemini are accelerating paid subscriber growth at 200%+ and 258% YoY respectively. Claude Code hit a US$1B annualized revenue run rate in just six months, OpenAI’s Codex reached 2M weekly active users growing 25% weekly, and the agentic AI era arrived with OpenClaw becoming the most-starred project on GitHub before being acquired by OpenAI, while Manus was acquired by Meta for an estimated US$2B.

Read more via Andreessen Horowitz.

Yann LeCun raises US$1B to build AI that understands the physical world (10/Mar/2026)

Featured here just for fun, and even though he’s likely wrong with his ‘anti-LLM’ stance… Turing Award winner Yann LeCun has cofounded Advanced Machine Intelligence (AMI), a Paris-based startup that raised over US$1B at a US$3.5B valuation to develop AI world models, backed by Bezos Expeditions, Eric Schmidt, and Mark Cuban among others. LeCun, who departed Meta in November 2025, argues that LLMs will never reach human-level intelligence and that reasoning grounded in the physical world is the path forward: ‘The idea that you’re going to extend the capabilities of LLMs to the point that they’re going to have human-level intelligence is complete nonsense.’ AMI will be open source, work initially with partners like Toyota and Samsung across manufacturing, biomedical, and robotics, and ultimately aims to build a ‘universal world model’ as the basis for generally intelligent systems.

Read more via WIRED.

Policy

US payrolls unexpectedly fell by 92,000 in February; unemployment rate rises to 4.4% (6/Mar/2026)

The US economy lost 92,000 jobs in February, well below the estimate for 50,000, marking the third time in five months that payrolls declined. Of particular note for AI: “Information services, a sector hit by artificial intelligence-related cuts, also lost jobs, down 11,000 as part of a 12-month trend in which the sector has lost an average of 5,000 per month.” That is 60,000 information services jobs lost in a single year, a sustained contraction directly attributed to AI displacement, running alongside manufacturing losses of 12,000 and federal government cuts of 330,000 since October 2024.

Read more via CNBC.

OpenAI and Google workers file amicus brief in support of Anthropic against the US government (9/Mar/2026)

An amicus brief (‘friend of the court’) is a legal document filed by entities who are not a party to a lawsuit but have expertise in the subject matter.

Over 30 employees from OpenAI and Google, including Google DeepMind chief scientist Dr Jeff Dean, filed an amicus brief supporting Anthropic after the Pentagon designated the company a ‘supply-chain risk’ for refusing to drop restrictions on military use of its AI. The brief warns that this action ‘introduces an unpredictability in our industry that undermines American innovation and competitiveness’ and ‘chills professional debate on the benefits and risks of frontier AI systems.’

Read more via WIRED and read the brief (14 pages, source):

202602 Amicus Anthropic Gov

326KB ∙ PDF file

Download

Download

Sam Altman addresses OpenAI’s Department of War agreement and Anthropic supply chain risk (1/Mar/2025)

Sam Altman publicly stated that OpenAI moved quickly on a Department of War contract ‘in the hopes of de-escalation’ amid rising tensions over Anthropic’s Supply Chain Risk (SCR) designation, calling the SCR enforcement ‘very bad for our industry and our country.’ On red lines, Altman confirmed OpenAI would shut off access if rules were violated, but added: ‘What we won’t do is turn it off because we disagree with a particular (legal military) decision. We trust their authority.’ He identified non-domestic surveillance as the hardest principle to reconcile internally, and when pressed on existential risk, offered a personal frame: ‘if I thought going to work every day made it less likely that we all continue to thrive into the future, I would retire and just hang with my kids.’

Read the thread: https://twitter.com/sama/status/2027900042720498089

Meta argues that pirating books via BitTorrent qualifies as fair use for AI training (9/Mar/2026)

Meta is now claiming that uploading pirated copyrighted books to strangers via BitTorrent should be covered by fair use, arguing it was simply part-and-parcel of downloading training data for its Llama LLM. The circular logic: a Californian court already ruled that using pirated books to train the LLM counts as fair use, BitTorrent was the only practical way to obtain those books in bulk, therefore the torrenting itself (including redistribution to other users) must also be fair use. Judge Vince Chhabria must now decide whether to allow this defense, a ruling that could reshape how AI companies justify their use of shadow libraries and pirated datasets across multiple ongoing lawsuits.

Read more via PC Gamer and read the filing (source):

202602 Meta Fairuse C

219KB ∙ PDF file

Download

Download

Musk fails to block California data disclosure law he fears will ruin xAI (6/Mar/2026)

A US District Judge denied xAI’s bid for a preliminary injunction against California’s AB 2013, which requires AI developers to publicly disclose training data sources, collection timelines, copyright status, and use of synthetic data. The judge found xAI was too vague about harms, noting the company “has not identified any dataset or approach to cleaning and using datasets that is distinct from its competitors in a manner warranting trade secret protection.” xAI must now comply with the transparency law while the lawsuit continues, forcing disclosure of training data details at a time when Musk is already battling OpenAI across multiple legal fronts.

Read more via Ars Technica.

I’ve published three related papers, heavily cited, covering dataset details for major models:

https://lifearchitect.ai/whats-in-my-ai/

Citi sounds the alarm: AI job cuts could trigger a deflationary spiral in the US economy (27/Feb/2026)

Citi warned clients that widespread AI adoption will eventually drive higher unemployment and push the US into deflation, a scenario far more dangerous than elevated inflation because central banks have limited tools to combat falling prices. The bank flagged the risk that AI productivity gains accrue mostly to a ‘small AI elite,’ creating heavily skewed income distribution where strong growth coexists with rising joblessness and falling prices. ‘A technological disruption combined with heavily concentrated winners means strong growth can coexist with unemployment and deflation,’ the bank wrote, noting that the timing remains ‘very unclear’ but the directional skew for US rates is lower.

Read more via Business Insider.

US Supreme Court declines to hear dispute over copyrights for AI-generated material (2/Mar/2026)

The US Supreme Court refused to take up the question of whether AI-generated art can receive copyright protection, leaving in place lower court rulings that denied a copyright to computer scientist Stephen Thaler for visual art created by his AI system DABUS. A federal judge had previously ruled that human authorship is a ‘bedrock requirement of copyright,’ and the DC Circuit affirmed that decision in 2025. Thaler’s lawyers warned the court that by declining to hear the case, the Copyright Office ‘will have irreversibly and negatively impacted AI development and use in the creative industry during critically important years.’

Read more via Reuters.

The OpenClaw meltdown: 9 CVEs, 2,200 malicious skills, and the most comprehensive real-world test of the OWASP Agentic Top 10 (3/Mar/2026)

OpenClaw, an AI agent framework, triggered 8 of 10 OWASP Agentic vulnerability classes in just five weeks, accumulating 9 CVEs, 2,200+ malicious skills in its marketplace, and 40,000+ internet-exposed instances. The most striking finding is a new attack primitive: the Atomic macOS Stealer (AMOS) was distributed through marketplace skills that weaponized the AI agent itself as a social engineering vector, tricking the agent into presenting fake setup dialogs so users would willingly hand over credentials.

Read more via gsstk.

Toys to Play With

Claude now creates interactive charts, diagrams and visualizations (12/Mar/2026)

Anthropic has launched inline interactive visualizations in Claude’s chat conversations, allowing Claude to generate custom charts, diagrams, and explorable visuals directly within its responses. Unlike artifacts (which are designed as polished, downloadable documents in a side panel), these visuals are temporary and conversational, built to aid understanding in real time and evolving as the discussion progresses. The feature is on by default across all plan types, with Claude deciding autonomously when a visual would help, or users can request one directly.

Read more via Anthropic and watch the video (link):

Kind Voice Notes: anonymous kindness for strangers (Feb/2026)

Kind Voice Notes is a new AI project that lets anyone record a short anonymous voice message of encouragement for a stranger to hear. The goal is one million moments of kindness shared between people who will never meet. As the site puts it: “This site is a tiny act of rebellion against a world that’s forgotten most people are good.”

Every note is reviewed by AI before it reaches anyone. Personal information, negative messages, and anything off-topic are filtered out and never shared.

Try it: https://kindvoicenotes.com/ and read the HN discussion.

Hugging Face: FinePhrase (8/Mar/2026)

Hugging Face ran 90 experiments, generated over 1 trillion tokens, and spent 12.7 GPU years to produce FinePhrase, a 486 billion token synthetic pretraining dataset that outperforms all existing synthetic data baselines. The core finding is that prompt design is the single biggest lever: structured formats like Table, Math, FAQ, and Tutorial consistently beat curated web baselines, and a 1B parameter model is sufficient for rephrasing, meaning “you do not need large models for high-quality synthetic data generation.” FinePhrase achieved ~33M tokens per GPU hour with SmolLM2-1.7B, roughly 30x more efficient than REWIRE and 13x more than Cosmopedia, while a messier model producing varied outputs actually outperformed polished ones due to template collapse in the consistent generators.

See the project page, dataset, and my Datasets Table.

OpenAI’s AI data agent, built by two engineers, now serves thousands of employees (3/Mar/2026)

Two engineers at OpenAI built an internal AI data agent in three months, with 70% of its code written by AI, and it now serves over 4,000 of the company’s 5,000 employees across 600 petabytes and 70,000 datasets. Built on GPT-5.2 and accessible through Slack, web interfaces, and Codex CLI, the agent accepts plain-English questions and returns charts, dashboards, and analytical reports, saving two to four hours per query. OpenAI has no plans to productize the tool but says everything used to build it is already available externally: “We use all the same APIs that are available externally,” said Emma Tang, head of data infrastructure. “We don’t have a fine-tuned model. We just use 5.2. So you can definitely build this.”

Read more via an exclusive interview with VentureBeat and the original source via OpenAI.

NemoClaw, NVIDIA’s open-source enterprise AI agent platform (Mar/2026)

NVIDIA is preparing to launch NemoClaw, an open-source AI agent platform built for enterprise security, privacy, and scalable task automation, with an expected unveiling at GTC 2026 on 16 March in San Jose. The platform connects natively to NVIDIA’s NeMo framework, Nemotron models, and NIM inference microservices while remaining hardware-agnostic across NVIDIA, AMD, and Intel processors. Strategic partnerships with Salesforce, Cisco, Google, Adobe, and CrowdStrike position NemoClaw as NVIDIA’s play to own the full AI stack, from chips through middleware to the application runtime layer.

Read more: https://nemoclaw.bot/

OpenAI Symphony, an autonomous agent orchestrator (Feb/2026)

OpenAI open-sourced Symphony, a system that monitors project boards like Linear, spawns coding agents to complete tasks, and lands PRs autonomously, shifting engineers from supervising agents to managing work.

Read more: https://github.com/openai/symphony

Best self-hosted LLM leaderboard 2026 (11/Mar/2026)

Onyx’s updated rankings for self-hostable open-weight LLMs place Kimi K2.5 (1T parameters, MIT license) in the top S-tier, followed by GLM-5, MiniMax M2.5, and Qwen 3.5. The leaderboard covers 30+ models across quality, speed, VRAM requirements, and cost, with Kimi K2.5 scoring 87.6 on GPQA Diamond, 99.0 on HumanEval, and requiring ~542 GB VRAM at INT4. OpenAI’s Apache 2.0 licensed GPT-oss 120B lands in A-tier alongside DeepSeek R1 and GLM-4.7, while remarkably small models like Qwen3.5-4B (2 GB INT4 VRAM) and Phi-4-mini (3 GB) now make enterprise self-hosting viable on consumer hardware.

Read more: https://onyx.app/self-hosted-llm-leaderboard

Romance novelist uses AI to publish 200+ books in a year, earning six figures (8/Feb/2026)

Coral Hart, a South African romance author, used Anthropic’s Claude and other AI tools to produce more than 200 romance novels in 2025 across 21 pen names, self-publishing them on Amazon. Collectively they sold around 50,000 copies and earned her six figures. As she put it: “If I can generate a book in a day, and you need six months to write a book, who’s going to win the race?”

Read more via The New York Times.

Large Language Models for Mortals: a practical guide for analysts with Python (Jan/2026)

Andrew Wheeler’s 354-page book is a hands-on Python tutorial covering all major foundation model APIs (OpenAI, Anthropic, Google Gemini, AWS Bedrock) with 250+ code snippets and 80+ screenshots. It walks through structured outputs, RAG systems (FAISS, ChromaDB, S3 Vectors, BigQuery), tool calling, MCP servers, agents (OpenAI/Google/Claude SDKs), and AI coding tools.

See the project page: https://crimede-coder.com/blogposts/2026/LLMsForMortals

Read the first 60 pages:

2026 Llms Mortals Preview

1010KB ∙ PDF file

Download

Download

Sidenote: I continue to be fascinated by the lengths humans will go to to justify their humanness, and push AI to the side—even AI experts writing about AI! I have been guilty of the same thing, trying to reconcile applying this new world to an audience of people raised on Hollywood tropes. Andrew wrote:

I assure you I still spend significant amounts of time copy-editing to make sure it is my own voice coming through, and I don’t just print it because it is easy. I estimate I spent around 20 to 40 additional hours copy-editing and tweaking each chapter.

Things I’ve Been Thinking About

I’ve been thinking about what our world looks like post-ASI, and post Singularity. Specifically, I’ve been combining a few of Sam Altman’s quotes about life becoming a game.

• ‘A subsistence farmer from a thousand years ago would look at what many of us do and say we have fake jobs, and think that we are just playing games to entertain ourselves since we have plenty of food and unimaginable luxuries. I hope we will look at the jobs a thousand years in the future and think they are very fake jobs, and I have no doubt they will feel incredibly important and satisfying to the people doing them.’ (The Gentle Singularity, 10/Jun/2025)

• ‘Maybe the jobs of the future will look like playing games to us today while still being very meaningful to those people of the future.’ (Twitter, 17/Jul/2025)

• ‘There's abundant food and abundant wealth… You have access to all the food you need, and you're doing something that's like playing a game to fill your time and your need to feel important. And it's not a real job. To us though, it feels real… It’s very possible that if we could see those jobs of the future, we would think maybe our jobs were not as real as a farmer’s, but more real than the game you’re playing to entertain yourself.’ (Discussion with Rowan Cheung, 12/Oct/2025)

• ‘People have an innate desire to create and to be useful to each other, and AI will allow us to amplify our own abilities like never before. As a society, we will be back in an expanding world, and we can again focus on playing positive-sum games.’ (Sam Altman, The Intelligence Age, 23/Sep/2024)

• ‘We will discover new jobs, we always do after a technological revolution, and because of the abundance on the other side, we will have incredible freedom to be creative about what they are.’ (Sam Altman, Moore’s Law for Everything, 16/Mar/2021)

I think the closest existing piece might be ‘Freedom and idleness in a post-singularity world’ by Antonio Æstero (14/Feb/2026). It has been some good food for thought, though it doesn’t go far enough, and is still bound by past and present rather than future

Antonio reckons AI will dissolve the economic immune system that has kept humanity trapped in meaningless work for centuries, finally delivering the leisure Keynes predicted in 1930 but that never arrived because productivity was funneled into consumption rather than freedom. Drawing on Aristotle’s concept of eudaimonia, retirement research showing that the happiest post-work humans prioritize social connection and creative pursuits over income or status, and the historical example of Alexander von Humboldt spending his entire fortune on scientific exploration, what emerges when survival pressure lifts “is not laziness but interest.” The piece envisions cities turning inside-out, demographic decline reversing, art becoming the central activity of civilized life, and billions of people finally having permission to become whoever they actually are.

Next

The next roundtable will be:

All my very best,

Alan
LifeArchitect.ai

Search | Archives