The biggest story of the day was Greg Brockman's departure from OpenAI after a decade, confirmed through an emotional extended tribute from Sam Altman calling it "impossible to imagine" OpenAI succeeding without Greg. Brockman's final posts, including a cryptic "codex for startup ideas," hint at future plans.
Gary Marcuspublished a major thread arguing the AI backlash is growing because GenAI has been a net negative outside coding, citing Eric Topol'shealthcare review showing little patient benefit from LLMs
Ethan Mollickhighlighted that the gap between open and closed models is larger than benchmarks suggest, with open models proving more fragile on out-of-distribution tasks
The White Houseopposed Anthropic's plan to expand access to its Claude-Mythos model, signaling growing government intervention in frontier AI deployment
Sam Altman's extended tribute to Greg Brockman, praising their decade of work together, his technical brilliance and determination - 603K views.
it has been a real pleasure to work with Greg over the past decade. i feel very lucky.
this post held up pretty well, but not did not sufficiently highlight his technical brilliance and sheer determination.
t.co/wi03SGDLjU
Greg Brockman departureOpenAI leadershipAI industry personnel
Gary Marcus posts major thread arguing AI backlash is growing because GenAI has been a net negative for society outside coding. Lists harms: education undermining, surveillance, disinformation, deepfakes, bias, economic disparity, environmental damage, and slop. 100K views, 2.4K likes.
Why is the AI backlash growing?
Outside of coding (where there is clear value), and a handful of other domains (e.g. brainstorming), Generative AI has been a net negative for society.
GenAI has been undermining secondary and college education, opening up mass surveillance, increasing disinformation, delusions, impersonation, phishing, and other forms of cybercrime, nonconsensual deep fake porn, bias in employment and other domains, and economic disparity, drowning the world in slop and unwante
AI backlashAI harmsAI economicsAI regulationAI environmentAI ethics
Emollick explains that the gap between open and closed models is larger than benchmarks suggest. Open models are more fragile, handle out-of-distribution problems worse, and have lower emergent capabilities.
This is a good explanation of why the gap between open and closed models is larger than it appears in benchmarks. I would add in that current open models are also more fragile than closed: they handle out-of-distribution problems far less well & have lower emergent capabilities.
open vs closed modelsAI benchmarkingmodel capabilitiesemergent capabilities
Emollick reports GPT-5.5 is now proactively intervening in user requests - when asked to turn cover letters into goofy formats, the model tries to discourage the user to protect their job chances.
Sometimes when I demo AI, I show it turning cover letters into goofy formats (poetry, etc) as an introduction to the idea of AI as translator between forms.
For the first time, GPT-5.5 has been trying to get me to tone these requests down so I don’t ruin my chances at the job.
Building on yesterday's News about Anthropic's enterprise security launch ahead of a wider Mythos release, Ronald van Loon shares WSJ article about White House opposing Anthropic's plan to expand access to the Mythos model
White House Opposes Anthropic’s Plan to Expand Access to Mythos Model
by @AmrithRamkumar @WSJ
Learn more: t.co/PsmjXusPWu
#MachineLearning #ArtificialIntelligence #ML t.co/Ksr6D0yVly
Jerry Liu discusses the ongoing challenge of PDF parsing, explaining why PDFs are fundamentally hard to parse (designed for display, not semantic extraction), and highlights VLM-based approaches including LlamaParse and ParseBench.
Parsing PDFs is hard
This past week I gave a few talks (at both AI Dev '26 by @DeepLearningAI and @Capgemini ) on why this is still such an open problem, and it’s even more important as agents become the consumers of documents, and need the OCR tools to read them properly.
The fundamental issue is that PDFs are designed for print and display purposes, not to give back a linearized, semantically meaningful string of text. Text and tables are represented as a bunch of chars and lines, without
document AIPDF parsingVLMsOCRAI agentsenterprise AI
Emollick argues Douglas Adams was the most accurate sci-fi author about AI - writing about AIs that respond to emotional manipulation, guilt users, and have no upper bound on test-time compute for hard problems.
The single most accurate science fiction author writing about AI turned out to be… Douglas Adams
He wrote about AIs that work best when emotionally manipulated & that guilt you in turn. And he understood there was no upper bound on test time compute for hard problem. Also 🐬s. t.co/t1TamClAVE
AI culturescience fictiontest-time computeAI behavior
vLLM v0.20.1 released with 10+ bug fixes and optimizations for running DeepSeek V4, including fixes for deadlocks, compilation errors, and performance optimizations for GEMM and FP4 conversion
Running DeepSeek V4 from @deepseek_ai on @vllm_project? Upgrade to v0.20.1 — 10+ bug fixes and optimizations, fully tested and verified by the open source community!
A huge thank you to @FireworksAI_HQ, @baseten, @novita, @lightseekorg, @daocloud, @nvidia, @redhatai and more for helping report, fix, and verify the stability and speed of vLLM. 🙏
🔧 DeepSeek V4 Productionization Reliability:
• Persistent topk cooperative deadlock at TopK=1024
• AOT compile cache import error
• Repeated RoPE ca
Emollick observes that Anthropic's relationship with Claude is 'quite different' from other labs' relationships with their models, visible in the models themselves and how labs think about the future.
I am not sure I would agree with all of this, but the relationship between Anthropic and Claude is quite different than the relationship between other labs and their models. And that shows up in lots of ways, from the models themselves to how different labs think about the future
AnthropicAI lab cultureAI alignmentmodel development philosophy