❗️ A developer hid a Bitcoin key on a PHP server left unpatched against PHP2Shell, the critical flaws fixed on Oct 21, and dared anyone to steal it. 17 hours on, the wallet holds ~$2,000 and nobody has taken it. The developer says someone is crashing PHP but "still no RCE yet".

Advanced session management of your @FastAPI endpoints using @Redisinc, based on the #Starlette framework? As easy as 𝙵𝚊𝚜𝚝𝙰𝙿𝙸𝚁𝚎𝚍𝚒𝚜(𝚊𝚙𝚙).𝚕𝚒𝚏𝚎𝚜𝚙𝚊𝚗().𝚜𝚎𝚜𝚜𝚒𝚘𝚗𝚜() 🕺🏼 Voilà! 🕺🏼 🔗 tinyurl.com/7pc498r6

A note from our research leaders: Last week we parted ways with Jasmine, Mikita, and Tomek after a thorough investigation found they violated clear policies on handling sensitive information. Our internal investigation uncovered a significant breach of trust beyond what’s outlined in the letter they published and we stand by the decision to not continue their employment. We generally keep individual employment matters private and don't believe a back and forth would be productive or lead to a resolution, but we want to address the points they raised in their letter directly. - We want to be very clear that these decisions were not about raising safety concerns or speaking out. Safety and research debates happen every day at OpenAI, often spirited and highly critical. We actively encourage these discussions and consider them essential to making the right decisions. We cannot do the work in front of us without a high degree of trust. We will continue to be extremely forgiving of our team making good-faith mistakes. We have not and do not terminate any of our employees for raising concerns. - We are actively finalizing contracts with third-party safety assessors and will announce details in the coming weeks. People across the company have been working really hard on getting these partnerships up and running. We are committed to embedding external assessors and continue to make close collaboration with independent safety organizations a core part of our safety work. Many of our researchers already work with 3p safety organizations productively. - We agree with the letter that preserving the monitorability of frontier models requires an industry-wide commitment, including from OpenAI. Monitorability has long been a core piece of our research program, and something we continue to invest significant resources in (see our publications on Monitoring Monitorability and the subsequent open sourcing of monitorability evals, our system card for GPT-6 Astra, Jakub’s blog and post on X, and the numerous blog posts on our Alignment blog on the topic). We are deeply sad about this outcome. We appreciated Jasmine, Mikita, and Tomek’s contributions to AI safety at OpenAI and their willingness to speak up and challenge ideas. We championed their voices, supported their work, and placed enormous trust in them. These decisions were not about them raising safety concerns. We have always encouraged that and always will.

reading the pained responses of mathematicians, there’s a real cruelty in the way the labs have pursued this. not least because the attempted outcome in dropping so much unvalidated and poorly-written work (per the comments) is to push some of the world’s most passionate problem-solvers to be fact-checkers to a machine, as a kind of cynical cheap-as-free RL environment-by-nerdsnipe. dump a bunch of shit in public, call it solutions, get the experts to pore over it, painstakingly review and critique, scrape their efforts and use it to tweak the model, all while stoking terror about the future of the profession. it’s fucked up.

SHOCK AND AWE: AI MATHEMATICS Fields Medalist: the release seemed intended to show the systems could “massacre us in the deepest sense of the term.” Here are other striking remarks from Hugo Duminil-Copin’s 8 October 2026 seminar talk “Un grave défaut d’alignement de l’IA en mathématiques, 28 jours plus tard” (SMF MIAM series), drawn from the available auto-transcript of the YouTube recording. - On the scale of the damage to his own work: after noting that roughly 350 major problems had been resolved, he said he placed “several trucks” on the slide to illustrate the impact, because every problem he had cited in talks, papers, and both past and future funding applications had been solved—none left unresolved. He described himself as panicked and paralyzed in the middle of the night when the results appeared. - On volume: looking only at the OpenAI texts that cite him directly, he counted about 3,500 pages; he has published roughly 3,700 pages in his entire career. Specific clusters included six papers totaling over 600 pages on conformal invariance aspects of percolation (a major ongoing project of his group) and a sequence of papers on self-avoiding walks that he only gradually realized totaled more than 1,000 pages. - On process and alignment: he described the approach as systematic “farming” or “mining” of open problems, in which the program itself selects targets from the existing literature, amounting to “the complete automation of mathematical discovery.” He said the community’s request not to destroy the open conjectures that orient research was “absolutely ignored,” and that the release seemed intended to show the systems could “massacre us in the deepest sense of the term.” - On the human side: he reported that his PhD students and postdocs were in “a state of total panic,” with undergraduates and master’s students also asking whether mathematics still has a future, and stressed the immediate need for collective resilience rather than delayed discussion. He added that the community must manage both its own emotions and the surrounding media reaction, while avoiding internal polarization that would weaken arguments to funders.

👀👀 "[…] we provide several examples of AI mistranslations of natural language (NL) statements and proofs into Lean in practice, resulting in mismatches between NL proofs and their Lean 'verifications'. These include OpenAI's announced Navier-Stokes proof. In particular, we show that the formalised Lean proof does not correspond to the NL proof of blow-up of solutions to the Navier-Stokes equations." arxiv.org/abs/2610.08144

You couldn’t beat me hard enough to admit that Golang is a beautiful language 🤣 Half your codebase will become “if err != nil” Remember when things got so bad that people implemented generics using U+1438 ᐸ and U+1433 ᐳ? Okkkkkkkk

I've had agents implement and optimize the Campfire web app in Elixir, Go, and Rust. Yes, Ruby is the slowest. I didn't care about that when the pay-off was huge in terms of productivity and developer joy. But if you're no longer reading the code? github.com/basecamp/once-cam…

I've had agents implement and optimize the Campfire web app in Elixir, Go, and Rust. Yes, Ruby is the slowest. I didn't care about that when the pay-off was huge in terms of productivity and developer joy. But if you're no longer reading the code? github.com/basecamp/once-cam…