Agentic AI news, research notes, and industry analysis.
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7 stories in this tag.
Simon Willison's May 27 analysis documents the concrete evidence that enterprise coding agents have found genuine product-market fit: Uber burned through its entire 2026 AI budget in four months, Anthropic signed a $1.25B/month compute deal with xAI through 2029, and Anthropic is on track for a first profitable quarter. The signal is in the invoices.
Read more →An internal OpenAI reasoning model disproved a conjecture in discrete geometry that had been open since 1946. It found a polynomial improvement to the best known lower bound for the planar unit distance problem — n^(1+δ) with δ = 0.014 — by importing tools from algebraic number theory that no human mathematician had previously applied to this problem. The proof was verified and endorsed by several leading mathematicians, including Fields Medalist Tim Gowers.
Read more →OpenAI announced it is embedding Google DeepMind's SynthID invisible watermarks and C2PA metadata into all AI-generated images, along with a public verification portal. Hours later, a Python CLI appeared on GitHub that defeats SynthID v2 by round-tripping images through SDXL diffusion. The episode illustrates what content provenance systems can and can't do.
Read more →OpenAI published a detailed engineering writeup on how they rebuilt their WebRTC stack for the Realtime API to run on Kubernetes at scale — separating a lightweight UDP relay from the stateful WebRTC transceiver and using the ICE ufrag as a routing hook embedded in standard protocol headers.
Read more →OpenAI published a postmortem on why GPT-5.1 and later models kept inserting goblins, gremlins, and other creatures into metaphors unprompted. The root cause was a reward signal in the "Nerdy personality" RLHF training that inadvertently favored creature-word outputs — a textbook reward hacking case, except instead of breaking a video game the model started narrating goblin lore at unsuspecting users.
Read more →A technical reverse-engineering of ChatGPT's ad delivery system shows how OpenAI injects ads directly into the SSE conversation stream and closes attribution via four Fernet-encrypted tokens and a merchant-side JavaScript SDK — a fully first-party ad stack that bypasses any third-party intermediary.
Read more →GPT-5.4 Pro solved Erdős Problem #1196 — a 1968 conjecture about primitive sets — when a 23-year-old amateur fed it the problem in a single prompt. The AI's approach used von Mangoldt weights and a downward Markov chain, a framing that existed in analytic number theory for ninety years but had never been applied here. Terence Tao's explanation for why experts missed it is the most telling part of the story.
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