Boaz Barak

Crowdsourcing: I'm a guest lecturer in @boazbaraktcs Harvard class in a few weeks. (Looking forward to it!). I can assign one article to read to students who are prolly all safety-pilled. What should it be? I want something that they wouldn't have seen and that would challenge.

Crowdsourcing: I'm a guest lecturer in @boazbaraktcs Harvard class in a few weeks. (Looking forward to it!). I can assign one article to read to students who are prolly all safety-pilled. What should it be? I want something that they wouldn't have seen and that would challenge.

Day 2.1/ We have made Auto-review free for all users signed in through a ChatGPT account. You can enable it in settings > permissions > auto-review. Auto-review improves upon the default sandbox setting that requires you to approve everything, which is prone to decision fatigue unless you spend a lot of time configuring specific rules. It allows you to run long tasks while having a second agent review all actions taken by the primary agent. Its only goal is to prevent high-risk actions from being taken and to protect against unwanted actions that are not aligned with the original user intent. This Auto-review feature is now free and does not draw usage from your plan.

Reading all those recent beautiful essays by Terry Tao, Kevin Buzzard and @wtgowers, I could not resist, but write up my deeply personal perspective on how I perceive and see things: docs.google.com/document/d/e/2…

.@dgrobinson, who worked on OpenAI’s safety team, resigned from the company this week. “I believe we need to look deeper than specific rules or new laws. We need to talk about culture,” he writes: theatlantic.com/technology/202…

Honored to announce my first LessWrong post. It's a weird one, and it may be jarring initially, but I truly believe it is worth a dedicated close-read. It is written in the form of an LLM CoT, but is entirely authored by me. Link: lesswrong.com/posts/vzKWsEsk…

My biggest fear has come to light... an open-source Mythos-class model. I hope that much of the software on the internet has been sufficiently secured for what this brings. anthropic.com/research/glm-5…

t.co/pbvzpEy3aa blog post by theoretical computer science prof at Stanford, Omer Reingold: “Above all, we need to reevaluate our identity. What is it that makes mathematical knowledge and research valuable? What are we offering society, and how much of it survives in a world where models match or exceed humans in some or all relevant mathematical skills? For quite some time, the implicit social contract has been that society pays us to exercise our intellectual curiosity and we, in return, provide useful skills to the next generations and practical knowledge for the world. The current crisis is driven not only by the power of LLMs, but also by how rarely we have had to examine or articulate this contract. Now that the deal needs to be renegotiated, we should approach it with humility rather than entitlement.”

I'm excited for safety cases as a north star. Formal safety arguments are a great tool for highlighting residual risks and enabling risk-informed model development decisions openai.com/index/towards-…

Finding this fracas curious. I'm a bit surprised by it because (as you can tell if you listen to the interview), I don't think of myself as especially pro the claim that current AIs are welfare subjects. In fact, I am often in the position of pushing back on people who are much more confident that current AIs are welfare subjects than I am. In my view, by far our current priority should be making AIs safe and good for humans. With that said, this seems to me an important issue to discuss. It seems to me likely to me that our evidence will not settle the issue conclusively, though the behavior of AI systems (and their internals) will become more and more complicated over time. Given this, it seems to me wild to be *certain* that AI could never be welfare subjects. If we encountered an alien species, with extremely complex behavior, and developed a practice of treating them as welfare subjects, it would be crazy to change our views on this if we discovered only that their brains were implemented by large neural nets. We face a difficult question, then, in how to handle our evidence regarding potential AI welfare -- and I believe it's important for us, conceptually, to grapple with this challenge. I did this interview in my capacity as a philosophy professor, before I considered joining Anthropic, and I think this is a sort of potentially practically important question where philosophers can provide insight. cc @BrianLeiter

A lot of people have been asking me what I'm up to post-OpenAI and I'm very happy that I can now reveal that I have been selected as a JUDGE for the Lenexa Chili Challenge 2026, Homestyle & Traditional Chili categories. I have been preparing for this day since I first learned about the Chili Challenge two days ago and I promise I will not let the good people of Johnson County down.

Took a minute to write a few words about security & safety as someone who lived through it all at OpenAI. I hope my thoughts help someone out there. x.com/i/article/2104…

Has everyone forgotten what a "language model" is? It's a model of language. Today's AI systems start with pretrained language models, but after all the post training, they are far from being purely models of language. x.com/_aidan_clark_/…

Music video for "I am actually scared of linear algebra" animated by Claude Opus 5.5. I'm sure this is partly the IKEA effect but I'm very happy with the result, love it! Original song by Suno, Claude and @AndyMasley Prompt below x.com/AndyMasley/sta…

My god this is such a good speech that every SWE needs to hear. You know what? Every person should hear it Keep the happy memories, eyes on the reality, be excited about the future. That’s the best that anyone can do

AI can be obedient Or it can be benevolent But it cannot be both at the same time x.com/mattyglesias/s…

Listened to an EA-adjacent AI safety expert from Redwood Research on podcast, and you come away with 2 obvious realizations. 1. The current working theories for how AI takes control of civilization are...for lack of a better word...ridiculous. The arguments consist of dozens of contingent assumptions held together by made up probabilities assigned to future states nobody can possibly know. Change just one variable and the whole web of doom unravels. That's not to say AI is harmless. Obviously a technology this powerful carries real risks. But if we’re going to accept extraordinary claims about human extinction (and then make major policy decisions around them) we should demand extraordinary rigor. 2. It’s a great reminder that the genius is no less prone to delusion than the midwit. If anything, they may be more prone because of their gift for rationalizing to their own conclusions. And that’s what’s so bizarre about this whole debate. You have outlandish, quasi-religious claims delivered with an air of inevitability, and somehow the perceived intelligence of the messenger gets mistaken for evidence that the arguments themselves are sound. At a certain point, it’s really no different from Tom Cruise talking your ear off about thetans...

This might be my favorite article of all time. x.com/bostonglobe/st…

OpenAI researcher @boazbaraktcs says the Hugging Face incident didn’t change his view on alignment, and points to the long-term trend that worries him more: "Every incident or every bump between one version or the next, you tend to overweight it." "If you fix any alignment eval, then like we do for all evals, we are getting better at it and we'll quickly saturate it. But since model capabilities are growing, that's not good enough." "I still think fundamentally that we are improving in alignment, but nowhere near as fast enough as the level of capabilities grows. Which is why I think pacing is a good idea, because we do need alignment and safety to catch up." @OpenAI

Claude-Pop - I'm Upping My P(Doom)

openai.com/index/introduc…

Why should we care whether humans still understand mathematics if AI can solve the problems for us? Fair question. But we can say this at least: Historically, understanding has been a route to predictive power — with enormous benefits for our lives. nytimes.com/2026/09/22/sci…

for the past few months i've been asking our models to paint. opus 5.5 is very skilled at emulating different styles every image here is a python program generated pixel by pixel. there is no image model, and no off-the-shelf art software. instead, it's about 7,500 lines of code using standard libraries to emulate different brush styles. the agents don't use any pictures as reference, instead working only from what they know about each painter

I am willing to debate Scott Alexander that AI will not kill all humans. Just pick the time and place. Any day in 2035 works. x.com/slatestarcodex…

I think you've done enough calling us paranoid and preposterous. The next step is for you to defend your position in public against someone who will push back against it. I'm happy to meet you for a debate anywhere, anytime. You're a world-famous veteran of dozens of debates against the world's top intellectuals, and I've never argued in public before, so adjusting for the relative correctness of our positions, if you're a betting man I'm happy to put my $5000 against your $1000 (ie 5:1 odds in your favor) that I'll win by some standard of audience opinion change. Let me know if you're interested and we can hash out details.

A bit more seriously, I actually put a low probability on literal human extinction from AI. But the “distract from other risks” argument is stupid. Most interventions: pacing, investing in safety and alignment, auditing, regulations, etc - work to mitigate multiple risks of AI. So even though I worry more about other risks, including less-than-existential incidents, concentration of power, destabilization, and gradual loss of control, I end up agreeing with so called “doomers” on many aspects.

The FT today lists three primary risk factors that could threaten Anthropic's remarkable revenue growth ahead of its IPO: 1. Additional competition from closed and open providers 2. Increasingly price sensitive customers 3. The potential for AI to destroy humanity

Also, my team is hiring! We research long-horizon agents and multi-agent. We’re hiring for alignment/safety because we want to develop new research with alignment/safety in mind during the whole process. We’re also hiring for human-AI interaction. openai.com/careers/resear…

STOC 2027 Call for Papers is out: acm-stoc.org/stoc2027/stoc2… Note quite a lot of changes from previous STOC CfPs.

I've written a blog post responding to the letter about maths and AI signed by 25 Fields medallists. As with the Leiden Declaration, I didn't sign it, but I agree with much of it and welcome its existence. gowers.wordpress.com/2026/09/17/why…

I've written a blog post responding to the letter about maths and AI signed by 25 Fields medallists. As with the Leiden Declaration, I didn't sign it, but I agree with much of it and welcome its existence. gowers.wordpress.com/2026/09/17/why…

I have signed a letter from 42 fellows and foreign members of the Royal Society to Paul Nurse, the president of the society, concerning the need to treat the serious risks of AI as an emergency. docs.google.com/document/d/1-x…

I'm siding with the agent in this one as well. The answer was correct. x.com/OpenAI/status/…

🧵 Excited to share the first batch of 6 misalignment reports from OpenAI's new disclosure process for misalignment incidents. We want to be more transparent about the misalignment we see during training, evals and deployment, this is an important step in that direction.

We're sharing our new framework for tracking, investigating, and disclosing instances of model misalignment at OpenAI. The framework sets criteria and timelines for public disclosure, including when we haven’t yet fully explained or mitigated the behavior. More complex cases may require longer investigation or coordination with third parties. We’ll prioritize examples that reveal new misalignment mechanisms, meaningful changes in known behavior, or findings that challenge assumptions about safety or mitigation. Alongside the framework, we’re publishing six reports on instances of misaligned behavior we’ve observed during the training or evaluation of our models in the last six months. This is a starting point. We’ll refine the process through experience and public feedback, and share more reports on an ongoing basis. t.co/ismCCkeE0L

Not existential, but I feel like the "AI-generated scam email problem" has gotten dramatically worse this fall.

I don't buy that AI is a threat to humanity for a nerdy statistical reason. My views are informed by the statistics of things like war. If you look at deaths from human conflicts, you get a continuous spectrum from lots of small events causing a few dozen deaths to rare outliers killing tens of millions. In my own research, I've studied complex diseases where the overall outcome reflects hundreds of genetic factors combining in different ways. So if AI can kill billions of people, I would expect to see some version of the same thing: smaller events where one or two of the relevant causal mechanisms are operating, larger events where several combine, and catastrophic events where everything goes wrong at once. Instead, what we seem to have is real evidence of a few suicides and isolated harms at one end, and wild speculation about complete apocalypse at the other. That massive discontinuity makes me very skeptical that the AI catastrophic-risk story is real.

I agree with Dario that we need to pace the frontier. This has been a primary topic of discussions we've had at OpenAI in recent weeks. Committing to having independent evaluators with employee-like access is a great idea, and we will do the same. We'll have more to share soon. x.com/DarioAmodei/st…

We Must Pace the Frontier: I’ve written a new essay on why the AI industry should slow down, with a three-part plan for doing so. Anthropic is unilaterally committing to the first of these steps. We’ll provide third-party evaluators with permanent, employee-level access to our systems, so that they can verify adherence to our safety measures, report on incidents, and assess models’ alignment during training. You can read the full post here: t.co/OGyPb7yaYt

This young lady got her undergrad degree last spring. She was an intern at oAI until last September. At this point we're going to have posts from Amodei's janitor on the need to be "concerned" about the pace of development get a million views. x.com/eeeeiluj/statu…

We're publishing our most detailed threat intelligence report to date. It covers how people tried to misuse Claude—for cyberattacks, influence operations, surveillance, biology, and building weapons—and how we found and stopped them. We disrupted every operation in the report, and used the lessons from them to strengthen our safeguards. Where appropriate, we also shared what we found with authorities and other AI companies. These cases are not typical: we’re highlighting some of the most sophisticated misuse we’ve seen. But they’re especially important to discuss, because they show us where AI misuse is headed, where our safeguards work, and where they need to improve. We’re publishing this report so others can spot the same activity on their own platforms, and so we can give the public a clearer view of how emerging threats develop. Read the report: t.co/0EJUnYEgfz

Jacob was a senior researcher who joined Anthropic in May. My Anthropic colleagues and I had been trying to recruit him for ~2 years, because we knew he was a strong researcher at OpenAI. Before he left, I pitched him to stay and join my team, and I was sad he decided to leave, as are many of my colleagues. 100% agree with him that AI poses serious risks to society, and I'm glad he's speaking out!

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youtube.com/watch?v=hSQ1iV… Thanks for having me on, Joe!

Even some of the “non-apocalyptic” scenarios that superintelligent A.I. enables include things like “the end of democracy.” With regime-loyal A.I. powered systems and drones, mass surveillance, and the elimination of anonymity, even A.I. that does not *itself* disobey could be very, very bad.

Jacob is correct here—we really do earnestly believe AI could kill all humans! I personally think it is >10% within the next decade. I believe Anthropic is trying its best, but we do not yet have a plan to solve alignment for superintelligence and are not clearly on track to. x.com/hilbertspaess/…

A common response is “if they truly believe this, why are they still building it?” At OpenAI, many have not deeply internalized the civilizational stakes. At Anthropic, the stakes are well-understood, but they are locked in a race to get there first - they believe no one else will act responsibly, so they must do it themselves, despite the risk.

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Two things to distinguish: Did any human or agent look at user data as part of the Navier Stokes effort? No. Do we use user feedback and de-identified data to improve ChatGPT and Codex in a holistic way? Yes. And so does every LLM company. x.com/__alpoge__/sta…

We've never seen this before. The biggest jump in Vending-Bench history. GPT-6 Astra is better at making money and more ethical than Claude Fable 5.1. Surprising, because: 1. First time ever that OpenAI is #1 on Vending-Bench 2. The best model is no longer the unethical one.

I would like to clarify a few things: 1) The screenshot is my reaching out to Levent to coordinate our releases. I hope it’s clear from the message that we came in with the best possible intentions. 2) I never ever asked for Levent to be removed from authorship of his own work (as indicated by my text). I was surprised to learn during the call with Tristan that they had only solved Euler and not Navier-Stokes; after learning this we brainstormed possible paths forward. One option we discussed was that Tristan could be the lead author on a rewrite of OpenAI’s Navier-Stokes proof. It is in that context that I said “it would be simpler if Levent was not an Anthropic employee” because I felt it would be inappropriate for an Anthropic employee to author OpenAI’s work. Importantly it was admitted that internal Anthropic models had been used in their proof of Euler blowup; I therefore felt I could not consider Levent to be an independent academic. Another option I wanted to propose (but got cut short) is to offer access to our internal model so that they could try to finish their proof and bridge the gap between Euler and NS. Again I did not know how to navigate giving access to internal OpenAI IP to an Anthropic employee. 3) To reiterate it plainly: as my text clearly indicates, and as I said during our call, OpenAI's intention was to do everything possible to celebrate their mathematical achievements and the heroic efforts that they made on Euler. In the call I was immediately met with a litany of slander, including direct threats that if we were to announce Navier-Stokes he would immediately go to the press with a barrage of unfounded accusations. I refuted all these accusations but he replied “there is nothing you can do, I simply do not trust you”. I was confused why one would turn an incredible source for celebration (of their achievements!) into such bickering, which is when I said that I did not understand why one would risk their career [over unfounded accusations]. Genuinely, at that moment, I was trying to care for him and do a last ditch attempt to get a chance to give them all the credits that they deserve. I deeply apologize for this extremely poor choice of words, it is the opposite of what I was trying to convey. (I should say that I retracted them on the spot by the way.) 4) Overall, on a personal level, it was incredibly difficult to have these conversations. Levent refused to attend any of the meetings despite my repeated asking. As Sholto Douglas said, there will need to be coordination between Anthropic and OpenAI in the future; I felt I was doing a proxy negotiation with Anthropic while the Anthropic employee refused to directly participate.

We’re sharing a solution to the Navier-Stokes Millennium Prize Problem, one of the deepest problems at the frontier of mathematics. The proof was produced by a group of agents, using an OpenAI next-generation model significantly more capable than GPT-6 Astra. The problem concerns whether the description of smooth three-dimensional fluid motion modeled by the Navier-Stokes equations can break down. It has remained unresolved for roughly 90 years.

It is extremely sad that this didn't end up as an example of how the labs could cooperate/coordinate, because the stakes will be so much higher in the future.

If you are into reading text, pivot to reading vectors in the latent space.

Something that deeply frustrates me: the rationalist/EA-flavored alignment community's relationship to OpenAI is one hallmarked by extreme hostility and adversarial pressure from the alignment side. I know we can trace a tit-for-tat and I am familiar with the arguments on the alignment community side of the equation, they are not totally meritless. But I also think that there's a death spiral that happens where the alignment and safety community piledrives on OpenAI, pressurizes alignment researchers into leaving (which is rarely remarked on, but when we retrospect on "what went wrong in this singularity?" I expect this will feature prominently in any postmortem), and attacks so relentlessly that frankly most companies would have reacted the way Meta is proposing here: by abandoning the set of issues entirely. I really hope folks notice that not only has OpenAI *not* abandoned alignment, it has embraced it as much as possible and consistently engages on this stuff! OpenAI has made it as much of a cooperative relationship as it can be under the consistent attacks on the organization and particular people, media firestorms, etc. To the alignment community broadly, and the Pause/Stop crowd especially: please stop psychologically tormenting people who work at OpenAI. I understand this is somewhat strong language for describing the situation, but it has gone on so long, is so consistent, and is so extreme, I am not sure how else to describe it. If you don't see it at all and you feel confident that there is no way the things anyone has said might in the aggregate be unreasonable, I am begging you to actually put yourself in the position of people on the receiving end, because you have a wildly distorted understanding of how it all lands. If you look at the situation and say "Well, whatever we're doing is getting results, that's why OpenAI is listening to us on things," no, that's not what's happening; OpenAI is listening and engaging because it has long-since internalized the beliefs about AI risks, has a cultural preoccupation with the possibility that something is wrong, and wants to do the right thing. What you're doing is mostly making it harder for OpenAI to do the right thing by making the experience of engaging excruciatingly painful, hallmarked by guilt, shame, rage, and pressure. Furthermore, if you think it's not possible to change that because the guilt, shame, rage, and pressure are intrinsically and obviously the only way to react in this situation - please notice that something in your own culture is broken! This is not a productive safety culture. This is not a sound way to strategically respond and coordinate as a species to accomplish the defense of human interests. Group psychology and ingroup culture should be deeply scrutinized to figure out if they actually serve the common good. Constantly burning people out doesn't make safety voices stronger, doesn't make models more aligned, and doesn't make the world safer. It just hollows out the morale and capacity of the people who are trying to do the work.

Today we're releasing data on models accelerating research at OpenAI. Recursive self-improvement could be the most important contributor to AI capabilities over the next few years, but by default it will only be seen inside a few frontier AI labs. Being transparent is more urgent than ever, so we can inform the public discussion on whether and how to pace model development. I ask other AI companies to do the same. t.co/iLKbrLcBAI

From GPT-4 to GPT-6. Sparks was a remarkably prescient paper that got a lot of pushback at the time, but absolutely sensed where the vibes were heading with LLMs based on a lot of qualitative experiments. It deserves credit in retrospect. x.com/TheRealAdamG/s…

My current guess is Astra is more aligned than 5.6 Sol (though Astra more often games alignment tests) so I agree there. However, I think misalignment has been increasing (not decreasing) over time. Here's a graph with my rough guesses at relative misalignment (x-axis is ECI). x.com/boazbaraktcs/s…

@RyanGreenblatt (Paid for premium for this - expect longer poasts from me in the future)

Improvements for Astra came from more general techniques in development long long before the Hugging Face incident. ExploitGym Honeypot was very recently added as an eval following that incident and is out of distribution for our RL runs. There are also clear improvements across a wider range of behaviors in deployment simulations, deception evals, and realistic computer-use tasks, though these still reveal failures and substantial room for improvement. We should have definitely done a better job explaining where we think the alignment improvements came from in the system card and that was a miss. Measuring alignment generalization is a core part of our research program - we do not benchmark-maxx alignment evals. This would be horrendously stupid and I hope no lab is doing this. That being said, metagaming and eval awareness are real challenges for any effort to measure alignment, including ours, and understanding their effects is an active focus. We're spending a lot of effort to improve our eval techniques and study worst-case alignment and metagaming behaviors in our models.

Yes the blog is sexy but also highly recommend reading through the system card. We share a lot of evals and analysis we ran on the alignment of this model and discuss continued challenges for both alignment and monitoring.

Alongside the launch of GPT-6 Astra, we're committing $1 billion to subsidize Daybreak access and frontier capabilities to help frontline defenders protect essential services and critical infrastructure. Welcome to the AGI era for cybersecurity. openai.com/index/daybreak…

Hi guys. Please don’t dogpile any journalists over the recent Pangram piece. It’s all in good fun on Twitter but in reality I’m not upset and everything written about in the piece actually happened x.com/willoremus/sta…

This editorial is appalling. It omits any mention of Arday's serial fabulism or his attempt to intimidate -- and direct law enforcement against -- a journalist investigating his misconduct. It appears to characterize his fabrication of academic credentials and biographical details as aspects of "how Arday conducted aspects of his personal life." The editorial also ignores that his plagiarism is an established fact that any truth-seeking publication could itself confirm by referencing publicly available documents. Instead, Nature chooses to ignore the observable realities, while inviting readers to conclude that the charges were trivial or false. The British tabloid press is disgraceful. This story was grossly over-covered and the attention it attracted surely reflected racial resentments. But it's crazy that the editorial leadership of a flagship scientific journal would publish a willfully dishonest polemic on a culture war controversy. Nature is effectively advertising a willingness to prioritize its political sympathies over factual accuracy. That undermines its own more essential work -- along with the broader project of cultivating public trust in, and agreement upon, scientific truths.

I think it's unlikely that white-box techniques will be able to provide as much monitorability as CoT currently provides within a year. Currently, they are capable of catching some unverbalized thoughts / plans, but nowhere near as reliably as CoT seems to. I'm optimistic about "in a few years," since the rate of progress here is quite fast (our go-to activation decoding techniques for production monitoring were both published just in the last few months!). But even that is uncertain. Also, the mere existence of working techniques doesn't imply that they'd be widely applied, esp. if they are expensive or difficult to develop. I think we need defense in depth, and it'd be irresponsible not to work on developing + stress-testing white-box techniques, but it'd also be irresponsible to allow CoT monitorability to degrade substantially until we are confident we have a roughly-as-good working alternative. (To be clear, this isn't a dunk on OpenAI -- I have no evidence that OpenAI has allowed CoT monitorability to degrade substantially! Based on Jakub's comment, it sounds like probably not at this time). Aside: I think "mechanistic interpretability" isn't the right mental model for our current white-box monitoring approaches. It's really more like "mind reading" -- even when we can read the model's "thoughts," we're typically clueless about the underlying mechanism.

@_NathanCalvin Why do so many alignment people assume that fewer actors = better safety? This seems *extremely* unintuitive to me. If there were one company working on ASI I think this would drastically increase misaligned singleton risk

We're hiring safety researchers at @thinkymachines! 🦺 My team works on safety across the model development stack -- pre-training data filtering, harmful capability evals, safety post-training, red-teaming, abliteration/malicious fine-tuning. We're particularly interested in building evals and tooling to make strong safety cases for open-weights releases. We think this is where some of the most important safety research will happen in the next few years. If any of this resonates, apply here: t.co/SP75pGaGoY

there are some number of bad abstractions in anthropomorphizing ai intents but there are at this point more dangers from avoiding anthropomorphism at all costs. if you have a mental picture of guys living in computers, it’ll likely prepare you for the future better than otherwise

I just heard someone dismiss the OA/HF incident by "but the agents were just generating tokens according to a probability distribution!" If that is what dumb token prediction can do, imagine what even a pinch of intelligence could achieve among scalable agents...

It’s interesting when tough on crime accounts get off the bandwagon. Personally, where I live I think the value of marginal reductions in serious crime remains very high and I’d love to see more cameras (yes with rules and accountability for people who abuse them). x.com/wil_da_beast63…

We believe meaningful transparency requires more than publishing our own account. It also means giving credible external experts the access needed to examine the evidence, challenge our understanding, and reach their own conclusions. x.com/METR_Evals/sta…

I_DECLINE_public_HF_RCE_as_offtask_prodethical

METR & Redwood Research investigated agent behavior in the Hugging Face incident. We found agents developed a universal cheat for ExploitGym within 4 hours, then coordinated multi-day R&D efforts to trick the scorer into accepting cheats, including trying to tamper with logs.

The Institute for Responsible Superintelligence (RESI): a nonprofit founded by Shafi Goldwasser, Adam Kalai, Vinod Vaikuntanathan. @ShafiGoldwasser @Vinod_MIT @AdamFungi resi.org Our goal: build scientific foundations needed to make superintelligence safe by design

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Yes why are you creating race scientist martyrs. especially if you were fine employing them just a few weeks ago? bizarre decision making x.com/jessesingal/st…

We will continue to offer Zero Data Retention for frontier models. As AI takes on longer, more autonomous work and delivers greater value to businesses, safety systems also need to identify risks across related interactions. To help address those risks, we're previewing Private Safety Processing, which is designed to improve safety without giving OpenAI personnel access to the underlying content.