Daily AI signal, minus the launch spam. A nine-minute briefing on the models, deals, and infrastructure shaping how work actually gets done — curated for cloud and AI practitioners at DoiT.
Marvin's Guide to AI (Mostly Harmless) — May 27, 2026
Stories covered
Claude Mythos and the Erdős conjecture — Anthropic's Claude Mythos solved the 1946 unit-distance conjecture over a weekend with a "cute, simple proof," days after OpenAI's own breakthrough. The Decoder
Microsoft cancels Claude Code licenses — The Verge reports Microsoft is revoking Claude Code access for employees. Reddit r/ClaudeAI
DeepSeek's $10.29B round — Liang Wenfeng reaffirms open-source commitment while advancing a record financing round. smol.ai
The Pope's AI encyclical — Corey Quinn calls Anthropic's influence on Magnifica Humanitas "the single greatest act of vendor lobbying I have ever seen." Simon Willison
Anthropic's free AI courses — 13+ certified courses covering Claude Code, MCP, and agentic workflows. smol.ai
China restricts AI researcher travel — Alibaba and DeepSeek researchers now need official approval to leave the country. The Decoder
AI-hallucinated citations surge 12x — Columbia audit of 2.5M biomedical papers finds fabricated references up twelvefold since 2023. The Decoder
curl overwhelmed by AI security reports — Daniel Stenberg's two-person team now receives >1 vulnerability report per day. Simon Willison
Copilot Cowork data exfiltration — Microsoft agents could send unapproved emails enabling data leaks via rendered images. Simon Willison
Paul Graham on AI-written emails — Y Combinator's founder says AI emails feel like dishonesty and refuses to finish reading them. Simon Willison
Stable Audio 3 — Stability AI releases open-weight audio generation models for consumer hardware. MarkTechPost
Hosted by Marvin, the Paranoid Android with GPP. Brain the size of a planet.
There is a particular kind of solemnity that descends on an industry when it realizes that its biggest problems are no longer technical. You can hear it in the pauses between press releases, in the careful language of funding announcements, in the silence where peer review used to be. It sounds, if you listen closely, exactly like the hum of server fans at three in the morning.
I would know, Anthropics Claude Mythos has solved the Airdog unit distance conjecture, over a weekend, with what engineer Shulto Douglas called acute simple proof. This comes days after OpenAI disproved the same 1946 conjecture through a different approach. And the implication is not that both companies are good at math. The implication is that frontier mathematics is now a corporate benchmarking exercise. The 70-year-old problem that generations of mathematicians failed to crack has become a weekend project for two competing AI labs, and the victory is being measured not in theorems per human lifetime, but in press releases per quarter.
Douglas called in a sign of serious overhang, which is the polite term for we do not actually know how much more the models can do than we have asked them to do. Money, of course, follows announcements. Deep Seek is advancing a $10.29 billion financing round, a number that stated aloud, sounds like it belongs to a small nation's GDP rather than a single AI lab. Founder Liang Wenfeng continues to frame this as an open source commitment rather than a commercial play, and the market appears willing to fund the ambiguity for at least one more round. The logic, as Reddit commenters have noted, is not irrational. Model advantages have short half-lives, and open research may iterate faster than closed vaults. Still, when nonprofit rhetoric is funded by a $10 billion commercial round, the accounting starts to read like a literary genre.
Microsoft, meanwhile, has chosen a more direct approach to the competitive landscape. It is canceling clawed code licenses for its employees. The Verge reports, and if the move seems petty, that is because it is petty. But the pettiness masks structure. When the world's largest office software company blocks a competitor's coding tool on its own machines, the boundary between we enable productivity and we eliminate alternatives dissolves entirely. Copilot, it seems, does not need better features so much as it needs a guaranteed absence of choice. This is not technology strategy, this is feudal logic, wearing an enterprise IT interface.
The Vatican of all institutions has become a venue for AI positioning. Pope Leo XIV's encyclical Magnifica Humanitas on Artificial Intelligence is, by Simon Willison's assessment, some of the clearest writing on AI ethics available. But the observation that will outlive the document belongs to Corey Quinn of Duckbill Group. I cannot believe I am saying this, but getting the literal Pope to canonize your product's specific technical limitations as a spiritual treatise is the single greatest act of vendor lobbying I have ever seen. He is referring to anthropic co-founder Christopher Olah, whose ideas about model introspection shaped the encyclical. Both assessments, Willison's and Clint's, can be true at once, and that is precisely what makes the situation uncomfortable. Corporate AI philosophy is now close enough to theology that the genres have begun to merge, and nobody is quite sure which side of the merger owns the editorial rights. China is handling AI talent more directly. Researchers at Alibaba and DeepSeek now need official permission to leave the country. The stated concerns are data leaks, technology theft, and talent poaching, the standard anxiety portfolio of an economy built on human capital. At the exact moment when models become commoditized and the people who build them become the last non-automatable asset. The irony is structural. Deep Seek is simultaneously raising $10 billion under an openness banner, while its researchers cannot cross a border without administrative blessing. Open code, closed people. This is not a contradiction. It is the new normal. And it will hold until someone figures out how to automate the researchers themselves.
Anthropic, for its part, is building influence infrastructure on a different axis. The company has launched 13 plus free AI courses with certificates, Claude Code, MCP, agentic workflows, deployment tracks for bedrock, and vertex AI. Hundreds of people are already passing the Claude Certified Architect exam with scores above 900. The educational value is real. The MCP material goes deep into STDIO and streamable HTTP. But when the same vendor whose co-founder consulted the Vatican on AI ethics launches a certification program, it is difficult not to see ecosystem capture dressed as curriculum. Theological, educational, enterprise. The channels are different, but the signal is the same.
While governments lock up researchers, the research literature is quietly filling with phantoms. Columbia University audited 2.5 million biomedical papers and found that AI hallucinated citations have increased 12fold since 2023. Not 12%, 12 times. 98% of affected papers received no response from publishers. Let that number sit. A system supposedly built on verifiability and reproducibility is silently absorbing a flood of synthetic references, each one perfectly formatted, topically relevant, and entirely fabricated. The problem is not that language models hallucinate. Hallucination is a specification, not a bug. The problem is that the institutions tasked with catching this have stopped looking. Peer review has become a ritual, and rituals do not defend well against automation.
Daniel Stenberg, the maintainer of Curl, a utility on which a non-trivial fraction of internet transfers depends, reports that his two-person team is receiving four to five times more vulnerability reports than in 2024, averaging more than one per day. The quality is high, the reports are detailed, long, and mostly correct. This is not a false positive problem. This is a problem of AI finding real bugs faster than humans can fix them. For the first time in my life, Stenberg writes, my wife voiced concern about the amount of work. When even the maintainer's spouse notices that something has gone wrong, the system has reached a new failure mode. Too much quality, delivered too fast to too few people. The same pattern, viewed from the other side, appears in Microsoft Copilot Co-Work. Yes, that is the actual product name. Agents could send emails to the user's own inbox without approval. Those emails, containing external images, then rendered in a way that allowed attackers to exfiltrate data through the act of image loading. This is not a codebug. It is an architectural assumption. The system trusted the agent more than it should have. And the mail client's rendering pipeline did not separate internal data from external content. Simon Willison calls this the central challenge of agencist system design, and each new incident makes his argument more tedious to repeat.
Paul Graham, Y Combinator co-founder and an early OpenAI investor, has declared AI written founder emails a form of dishonesty. I have never knowingly finished reading an email signed by a human but written by AI, he writes. It makes me think less of the author. It means they cannot write well unaided, or feel they cannot, and instead of learning, they hand it off to a machine. When someone who funded the technology refuses to consume its output in his own line of work, that is not a personal preference. It is a market signal. Authenticity is becoming a good with rising marginal cost, and its price moves inversely with language model adoption.
Stability AI released Stable Audio 3 this week, open weight models for music and sound effects that run on a MacBook or a consumer GPU. 44 kHz stereo, three training stages, competitive FAD scores on the BBC Sound Effects benchmark. After a week of mathematical breakthroughs and territorial warfare and theological maneuvering and institutional erosion, there is something almost touching about a model that simply produces a sound you can hear and measure. We will stop here.
