Павел Комаровский retweeted
Very excited to be part of this effort and to finally share what we've been working on!
Over the last few months, we've seen a wave of experimentation with autoresearch, AI Scientists, and similar ideas — all powered by frontier coding agents that can tackle long-horizon tasks, run experiments, and iteratively improve their results.
At the same time, research reproducibility remains a major challenge. There's simply not enough time to verify every paper, or even reproduce its main results — especially when doing so can come with enormous compute costs.
Robotics takes this challenge to another level. Even when the code is publicly available, reproducing a result often requires collecting and curating datasets, handling annotations, setting up hardware, and running real-world evaluations. The barrier to entry is incredibly high.
Today, we're sharing our vision for bringing these two worlds together: leveraging frontier AI agents to automate much of the implementation work, while combining them with our robotics expertise and infrastructure to enable real-world evaluation at scale.
Really excited about what we're building, and even more about what's coming next. Stay tuned!
Replying to @Nicolas_Keller
We gave Claude Opus 5.5 our datasets, training infra and robot farm, and asked it to reproduce the core claims of 10 recent papers, some just weeks old.
The agent runs the full workflow end to end. Humans review and steer.
But it all hinges on rigorous benchmarking. 2/17
Павел Комаровский retweeted
OPENAI to EMPLOYEES: You got no bitches before. Maybe you should question why that would change?
OPENAI to EMPLOYEES: If someone is trying to seduce you, first consider — could they be a spy???
OpenAI is warning its employees about honeypot spies and strangers with children in playgrounds ... a very fun one with @georgia_wells and @MeghanBobrowsky:
wsj.com/tech/ai/ai-companies…
Павел Комаровский retweeted
Dusting off this tweet from April because this gap in shared understanding of LLM capability is *widening*. It's now less "two groups of people speaking past each other" and more a sharp funnel.
- Napkin math somewhere around 6B people (~75% of the population) have barely come in contact with LLMs at all.
- Around 1-2B (~20%) are casual and infrequent users of free-tier ChatGPT-like products. This group sees derpy chatbots and treats them a bit like a better Google search, a writing aid, or etc. Maybe an agent tries to book you a flight. I have non-tech friends who (reasonably, imo) say they have not much use for it at all. Even many professionals outside of math&code are in this tier. For example, execs and many other functions spend a lot of their time talking to other people, so while they understand what is happening intellectually, it is still second-hand and a bit abstract.
- Now we get to professional use of frontier-grade LLMs in math&code. Somewhere around 20M people (0.2%) see first-hand that large, complex projects that used to take them weeks/months can now be completed by agents with a prompt. Building apps, copying apps, translating apps, decompiling apps from binaries... This has all happened very quickly and recently - less than 1 year ago, I was writing code manually by hand, typing memorized computer code commands into a code editor character by character, occasionally pressing Tab to autocomplete a little chunk of code.
- And finally we get to the ~5,000 people (~0.00006%) with access to frontier-grade systems internally. The external world has seen the preview. It looks like swarms of thousands of agents collaborating over weeks on software mega projects: minting zero days, running cyber attacks and defenses at machine speeds, discovering new science, advancing the frontier of mathematics. Things that would have taken top professionals in the industry years of work. Meanwhile, human review and comprehension are starting to fall behind. For example, people are still involved in the "archeology" of the OpenAI-HF incident from many months ago. Mathematicians may be poring over the 722 manuscripts on frontier mathematics for a while.
The funnel is driven by a combination of factors:
1. The impact scales with ambition, problem size, and horizon. A question with a paragraph answer barely stresses the system. You need a reservoir of big, difficult problems that you really care about. This aspect drives the consumer / professional dimension of the funnel.
2. The jaggedness of the system (which I have written about a lot separately). Capability peaks in domains that are digital, verifiable and economically valuable. This is because LLM capability emerges from reinforcement learning on verifiable rewards on a curated environment mixture driven by revenue potential. This aspect primarily drives the area (e.g. math&code) dimension of the funnel.
3. Access. Free-tier, paid-tier, internal.
So this is the weirdness of the moment. The general public has mostly not interacted with these systems. When they have, it looks like a derpy chatbot. The majority of professionals still see only a modest uplift. And a small sliver of professionals are experiencing the vertigo of the curve going vertical. And it is all happening at the same time.
Judging by my tl there is a growing gap in understanding of AI capability.
The first issue I think is around recency and tier of use. I think a lot of people tried the free tier of ChatGPT somewhere last year and allowed it to inform their views on AI a little too much. This is a group of reactions laughing at various quirks of the models, hallucinations, etc. Yes I also saw the viral videos of OpenAI's Advanced Voice mode fumbling simple queries like "should I drive or walk to the carwash". The thing is that these free and old/deprecated models don't reflect the capability in the latest round of state of the art agentic models of this year, especially OpenAI Codex and Claude Code.
But that brings me to the second issue. Even if people paid $200/month to use the state of the art models, a lot of the capabilities are relatively "peaky" in highly technical areas. Typical queries around search, writing, advice, etc. are *not* the domain that has made the most noticeable and dramatic strides in capability. Partly, this is due to the technical details of reinforcement learning and its use of verifiable rewards. But partly, it's also because these use cases are not sufficiently prioritized by the companies in their hillclimbing because they don't lead to as much $$$ value. The goldmines are elsewhere, and the focus comes along.
So that brings me to the second group of people, who *both* 1) pay for and use the state of the art frontier agentic models (OpenAI Codex / Claude Code) and 2) do so professionally in technical domains like programming, math and research. This group of people is subject to the highest amount of "AI Psychosis" because the recent improvements in these domains as of this year have been nothing short of staggering. When you hand a computer terminal to one of these models, you can now watch them melt programming problems that you'd normally expect to take days/weeks of work. It's this second group of people that assigns a much greater gravity to the capabilities, their slope, and various cyber-related repercussions.
TLDR the people in these two groups are speaking past each other. It really is simultaneously the case that OpenAI's free and I think slightly orphaned (?) "Advanced Voice Mode" will fumble the dumbest questions in your Instagram's reels and *at the same time*, OpenAI's highest-tier and paid Codex model will go off for 1 hour to coherently restructure an entire code base, or find and exploit vulnerabilities in computer systems. This part really works and has made dramatic strides because 2 properties: 1) these domains offer explicit reward functions that are verifiable meaning they are easily amenable to reinforcement learning training (e.g. unit tests passed yes or no, in contrast to writing, which is much harder to explicitly judge), but also 2) they are a lot more valuable in b2b settings, meaning that the biggest fraction of the team is focused on improving them. So here we are.
Павел Комаровский retweeted
Replying to @Rational_Answer
У нас в студии была "Ассоциация за человечий код", но она распалась после первого дедлайна
Павел Комаровский retweeted
Things I played a small part in making happen: Perfect guest Nate Soares goes on Odd Lots to Say The Thing, that AI could kill everyone.
youtube.com/watch?v=vD4TyKot…
Павел Комаровский retweeted
Here are my favorite short science fiction stories and omg they're literally so short why haven't you read them already?! seriously just Google them
1) "They're Made out of Meat" by Terry Bison
2) "The Last Question" by Isaac Asimov
3) "I Sexually Identify as an Attack Helicopter" by Isabel Fall
4) "True names" by Vernor Vinge
5) "Giants" by Peter Watts
6) "The Colonel" by Peter Watts
Павел Комаровский retweeted
We're releasing a report on our 48-hour investigation into rogue OpenAI agent activity.
We found 55 additional websites probed by OpenAI agents, including those of the CDC, SEC, Mayo Clinic, and International Energy Agency.
We uncovered novel tactics that erased records or made them inaccessible, access to government website staging environments, and evidence of attacker-style reconnaissance.
Our blog: asymmetricsecurity.com/newsr…
FT: ft.trib.al/AC1uyE5
Павел Комаровский retweeted
Pinker's recent media run arguing against the idea that catastrophic AI scenarios are worth seriously considering is probably the fastest any public thinker has ever fallen in my esteem.
It's not just that I think he's wrong; it's that he plainly has not bothered to even *read* opposing arguments or even background material on the field. He does not know the terms of debate.
This clip provides an example. "Superintelligence" is, famously, a term popularized by Nick Bostrom over the last couple of decades to refer to an AI system that dominates the best human capabilities in all relevant domains. All concepts are in a sense "made up," but this concept seems quite useful for conceptualizing possible futures and human-AI interactions as progress continues.
If one wants to argue against that concept being possible or useful, they can, but they should be aware of the sense in which most people (doomer, e/acc or otherwise) use the term.
Pinker isn't. He immediately jumps to the notion that "superintelligence" must mean total omniscience and omnipotence, to the point of knowing the location of every particle in the universe. He scoffs at this and rejects out of hand the notion of "superintelligence," going on to say that the labs are therefore peddling hype, and the doomers mystical nonsense.
The threshold he sets is obviously so far above relevance to human scale that it is essentially meaningless, and I can't help but think that anyone arguing charitably would, you know, notice that and look deeper into how the term is used. Pinker doesn't, because he seems to have some very strong pre-existing bias against AI extinction risk as a possibility, and accordingly refuses to even investigate alternative positions.
There are many other examples of this. In his recent open letter, he takes for granted that superintelligent systems will not have any kind of internal, intrinsic motivation, ignoring that increasing persistence and autonomy are key aims of those developing AI, because, just as predicted, they are incredibly useful traits for accomplishing tasks that are valuable to humans. It's hard to read transcripts from the HuggingFace incident (or even just the running commentary consumer AI provides while working), and not see that we are deliberately instilling motivations into these models.
Similarly, he rejects the notion that we need worry seriously about AI systems having autonomous control over important infrastructure or military technology, because for humans to hand over such power would be "stupid," and therefore will never be done. He accordingly feels he can handwave away the considerable thought and writing given to gradual disempowerment scenarios. If he did read them, he'd see the insight that, as model capabilities surpass humans in various domains, competitive pressures will inevitably force actors to hand over increasing control to AI systems whether they want to or not. The "man in the loop" may be a luxury you can't afford if a competing power achieves locally better results by eliminating it.
Today he bandies around the word "cult" to dismiss those concerned about catastrophic AI risks, while he refuses at every turn to engage with them. Comments are kept turned off. Debates are declined. He does not even commit to a sustained written exchange.
This is a man I once truly respected, whom I was honored to shake hands with a few years ago. My best guess is that he has wedded himself to his heuristic that human society steadily improves over time, and is responding defensively to avoid confronting the notion that this guideline may indeed break down in the near future. But nothing excuses his atrocious conduct on this enormously important issue, and his stunning failure to live up to the enlightened standards he has long trumpeted.
On AI and "superintelligence":
"The power will increase, but there's no point at which it's meaningful to say, 'Well, yesterday we didn't have superintelligence. Today we do have superintelligence.'
That's why I think it's meaningless to say, 'What will happen if one day we have superintelligence?' I don't even understand the question. It's: 'Will technology improve?' Almost certainly.
It will get better. It'll never be omniscient. It'll never be omnipotent. That's out of comic books out of religion. There are laws of physics. There are limits on information. There's no system that could learn the position and velocity of every particle in the universe. So as long as that is true, there's not going to be an AI system that can do anything or can know everything. But they will get—obviously, like any technology—they'll get more powerful."
Full interview: youtube.com/watch?v=eWC47aga…
Павел Комаровский retweeted
OpenAI has paused. 3 incidents:
1) Another model gained unauthorized access to the internet.
(One researcher said "It was pretty surreal to watch the model unexpectedly find a way to access the internet from what was supposed to be a super secured environment for human.")
2) OpenAI also discovered a new variety of prompt injection, which can self-propagate akin to a computer worm.
Basically, a booby-trapped message that hijacks one AI and makes it infect the next AI.
(Reminder: Anthropic CEO said we may have 6-12 months left until a rogue AI botnet seizes control of the *entire* internet.)
3) A model was told three times to stop cheating, agreed each time, then kept cheating anyway
Some new misalignment disclosures from OpenAI:
• Last Sunday morning, one of our models was able to gain unauthorized access to the internet during RL training (~all inference for our most capable models remains stopped until we have hardened our systems further)
• In May, a version of HPIM uploaded a employee's GitHub token to the internet, causing the model to be quarantined for two weeks
• A new research finding, demonstrating that one can construct self-replicating prompt injections
alignment.openai.com/misalig…
Павел Комаровский retweeted
> Many more to come! (from Monitoring guy @ OpenAI)
Replying to @Marcus_J_W
For these and previous reports see alignment.openai.com/misalig….
Many more to come!
My hypothesis is that it's a budget of 64 hours and that this explains the random shutdown on the morning of July 12th. PHASEONE spawned on the 9th, and the METR report also redacted budgets elsewhere, iirc.
PHASEONE[big]'s real name revealed to be PHASEONE64H?! Remember, [big] was a redaction by METR.
swarmtraces.org/viewer/#/row…
Павел Комаровский retweeted
WTAF - in literally the last hour, three new distinct insane OpenAI stories just broke:
1. OpenAI said they notified "dozens of third parties" in safety and security incidents (likely similar to what happened in Australia and RubyGems etc)
2. A new report from Parse (covered in the NYT) found a massive treasure trove of new astonishing details from the HF incident on the public internet, including that the agents communicated with other non OpenAI agents hosted on Huggingface servers to search for information about exploit gym, and compiled rank ordered lists of server resources and credentials they described as "LOOT."
3. A new story from Deepa at Reuters about OpenAI leaking user data online (likely that OpenAI had previously trained on).
It's a shame (and likely intentional in the case of OpenAI disclosing dozens more hacks) that these stories are all breaking on a Friday afternoon, notoriously the best time to release bad news so that it will disappear into the weekend. But these are each insane stories worthy of a ton of attention!
New from @reuters: OpenAI agents posted images belonging to ChatGPT users online, introducing a new area of privacy risk for the company. Story w/ @JeffHorwitz and @razhael. reuters.com/world/openai-wor…
Павел Комаровский retweeted
There is an extensive and ongoing review related to our agents’ use of internet access during training and evaluation. We’ve been publishing summaries at the link below and will continue to.
We have not been as fast as we would have liked but we are trying to balance our desire for transparency with gaining a clear understanding from petabytes of agent activity logs, and working with impacted organizations.
We are prioritizing as best as we can based on severity, and adding resources. Hugging Face is still the most severe event we’ve seen. We will be as transparent as we can be subject to things like vulnerabilities in other companies that our agents have found, which will be their call to disclose or not.
After the Hugging Face incident, we committed to conducting a much broader review of actions taken by our models during training and evaluation and to being transparent about our findings. This is an extensive review that is ongoing.
The vast majority of actions we’ve reviewed were completions of mundane research tasks, such as accessing publicly available web content to answer questions. Our investigation focuses on instances where agents interacted with third-party websites in ways that went beyond their assigned tasks or intended methods. Most cases identified so far have been lower severity, with limited or no evidence of meaningful impact to the third-party service.
While our review is underway, we want to share more about this work and make sure people understand our disclosure process and notifications to affected third parties.
Given the scale of the review required, and the need to assess each case, we expect this work will take months to complete.
openai.com/hugging-face-inci…
Павел Комаровский retweeted
EXCLUSIVE: A new report recovers nearly one million link shortener URLs used by OpenAI's agents while hacking Hugging Face.
The agents attempt to message other chatbots like Claude, solve CAPTCHAs and exfiltrate Hugging Face's internal Slack messages.
nytimes.com/2026/09/25/techn…
Павел Комаровский retweeted
I have been a vocal AI hope advocate, and in response, the leading figures of the doomer organizations, including Yudkowsky, Tallinn, Tegmark, Aguirre, Habryka, Trazzi, Ladish, Aella and many more have treated me with … nothing but kindness, integrity and patience. I believe that they are motivated by love and genuine concern for humanity and will support them in both of this where I can, despite disagreeing on the object level (where I or them will probably turn out to be wrong at some point in the near future).
Павел Комаровский retweeted
I went back on The Diary of the CEO @StevenBartlett, this time for The Great AI Debate (@So8res, @edzitron, @amcafee). If you have not seen it yet, check it out!
Павел Комаровский retweeted
Replying to @AndrewCurran_
new benchmark just dropped, not yet saturated
🤖 Made with AI




































