Where the AI market is talking

Responding to the next frontier of critical cyber capabilities

The point is to reduce the attack surface and blast radius and to slow it down. AIs aren't instant magic. Even the OpenAI swarm needed days for its compromises. And each needs lots of compute while targets are diverse, so it's not like they would take out every network in the world simultaneously, worms in the past haven't either. When the rate of compromises is manageable we can figure out how to deal with it without pouring more AI into the fire.

Improving GPT‑5.6 Sol in ChatGPT, expanding GPT‑5.6 Luna access for free users

> No they wouldn't have. Low cost isn't no cost, R$D is expensive I'm not talking about R&D. > there are a class of tokenmaxxing users well outside the median (e.g Agentic Coding). It wasn't a thing before last year and OpenAI wasn't making profit before that either. > https://cloud.google.com/blog/products/infrastructure/measur ... > https://epoch.ai/gradient-updates/how-much-energy-does-chatg ... None of these support your claim. Again, when you're here saying that the CEOs of the two biggest AI companies are basically idiots, nobody will take you seriously.

Timeline of the OpenAI accidental attack against Hugging Face

I now watched the video. It seems the agents were sharing context for months, run unattended for months, the sandbox was no sandbox at all, one agent hacked a service and announced it, the service was fixed weeks (?) later, but not secured in any way, the agents hacked the same service again and researchers again didn't watch what the agents were doing. Then the agents - unattended - hacked OpenAI infra and HF. Which is when someone found out about the whole thing that was going on for some months.

DeepMind's WeatherNext model achieves breakthrough forecasting cyclones

Everything in the western world isn't focused on LLM. The top western players are heavily focused on AGI. Meanwhile the Chinese are using LLMs and other non-AGI AI tech at the edge wherever they think to put it for task-specific productivity or optimization. They don't really care about AGI, or more accurately: they're working on getting their society more efficient and decarbonized, and then they'll be free to work on AGI with far fewer resources. OpenAI, Anthropic, et al are working toward someday having AGI, and if they ever do, when they do, the Chinese will be hopelessly far ahead of us on energy, manufacturing, logistics (especially low/zero carbon transport of goods and people) and so on. Once the Chinese figure out how to train an AI for ULEV lithography, especially once they…

DeepMind's WeatherNext model achieves breakthrough forecasting cyclones

Everything in the western world isn't focused on LLM. The top western players are heavily focused on AGI. Meanwhile the Chinese are using LLMs and other non-AGI AI tech at the edge wherever they think to put it for task-specific productivity or optimization. They don't really care about AGI, or more accurately: they're working on getting their society more efficient and decarbonized, and then they'll be free to work on AGI with far fewer resources. OpenAI, Anthropic, et al are working toward someday having AGI, and if they ever do, when they do, the Chinese will be hopelessly far ahead of us on energy, manufacturing, logistics (especially low/zero carbon transport of goods and people) and so on. Once the Chinese figure out how to train an AI for ULEV lithography, especially once they…

Timeline of the OpenAI accidental attack against Hugging Face

In a functioning system, I would say that there would have to be some kind of government oversight over companies training models of this intelligence, and that OpenAI should be prevented from continuing their work until they get their act together. But I guess in the actual world we live in, this is just something that happens, and we all shrug and move on and hope that nothing worse is going to happen tomorrow.

Timeline of the OpenAI accidental attack against Hugging Face

I can only recommend everyone to watch the actual recording of the Black Hat USA 2026 presentation by two OpenAI researchers: https://www.youtube.com/watch?v=87DyyMV0kCY It was submitted to HN previously but was overlooked.

Timeline of the OpenAI accidental attack against Hugging Face

"This also helps explain why the models had nothing to cause them to hold back. Those safety behaviors are added much later in the process." I am a fan of Asimov and the three laws of Robotics. Itlooks like in OpenAI's world, the three Laws of Robotics would be added later if they were to develop the positronic brain. It may also explain how US Robotics from Asimov's books would have been able to design Robots that only partially adhered to the 3 laws (e.g. the robots in iRobot - the book - which were programmed to allow a human to come to harm through inaction so that the humans could complete their work on the plains of Mercury).

DeepSeek V4 Flash 0731

> GLM 5.3 bridges this gap. I’m sure the next models will only get better, when they’re released. Also super curious about what Moonshot will achieve and the full DeepSeek V4 Pro release! > Their moat, especially OpenAI is funding and hardware resources. They gain train models 10x as large and also serve at large scale. That's it. I’ve seen how much slower Kimi K3 can be and that part seems correct, their own GPU production still has ways to go and export restrictions definitely limit what they can do. Not sure about the size part, if Kimi K3 achieves SOTA performance at 2.8T parameters, western models being >2x that size would be insanely bad in regards to efficiency. I bet they’re all within the same order of magnitude and below 10T and won’t really have a reason to go even tha…

Timeline of the OpenAI accidental attack against Hugging Face

[edit] I've now watched the video on the idea that your write-up was misleading. BUT the video is much worse. For two months with highly dangerous agents agents were hacking a service and none of the researchers watched (drank coffee for 2 months, didn't say). THEN they found the hack, removed the message board. AND the agents found another way to create a message board, on the same service, and the researchers again - after the agents having hacked a service - do nothing - like monitoring the hacked service or tightening the sandbox. WOW! THEN agents hacked OpenAI infrastructure, and the researchers did nothing. THEN the agents hacked HF. The video does not explain why the agents run for two months unattended. They claim for model training, but don't explain how letting run agents withou…

What Happened: OpenAI and HuggingFace

Timeline of the OpenAI accidental attack against Hugging Face

Beyond a whole lot of online conspiracy theories I haven't seen anything that suggests to me that OpenAI aren't not telling the truth about what happened here. I find the Black Hat presentation in particular very credible. Also the Hugging Face technical report. (As an example of something I don't find credible: https://openai.com/index/responding-next-frontier-critical-c... is a total nothing burger. It's the other end of the credibility scale from the Black Hat talk.)

Timeline of the OpenAI accidental attack against Hugging Face

About knowing whether a scenario is fictional, there was an interesting finding in Anthropic's J-Lens research. When they benchmarked the model to evaluate whether it would try to blackmail someone in a contrived scenario, the J-Lens showed "fake" and "fictional" in the workspace. And if edited out, the model was more likely to do the blackmailing.

Auto Mode will be the default in Claude Code – because humans can't be trusted

once you have built up a trust in a model/harness/setup/workflow and you’ve been hitting enter for months straight then Auto Mode is appealing. i found initially it would hang on some commands (moreso on subagents and moreso when first rolled out) and then roll past the hung command sometimes forgetting about it entirely. which wasn’t cool. but after dialing in subagent permissions and probably some updates from anthropic Auto Mode is great. i still don’t always do it. but after reading this article just switched my current 12 panes to Auto.

Timeline of the OpenAI accidental attack against Hugging Face

It does not explain how agents months later would "collaborate" to hack Hugging Face.

Timeline of the OpenAI accidental attack against Hugging Face

I think for the power you have and how many people listen to you, you should have added context. All of it is made as if without prompt or direction, agents on their own initiative, over weeks collaborated to hack Hugging Face - which too me, sounds highly doubtful. You transporting this without any context makes it seem as you agree with the narrative of OpenAI.

U.S. Department of Energy Launches the Genesis Open Models Initiative

The DOE does a lot of "energy consuming" or less than environmentally friendly work, to include, historically, nuclear tests, and also has had ownership of some of the largest TOP500 supercomputers over the years. Large compute projects such as an open language model aren't too far from their usual. You could easily argue the race to AGI is the closest thing to a modern Manhattan Project we've had in some time. Whether that's a good allocation of resources is debatable, but from a national strategic perspective this makes sense, since private industry has pulled out of government contracts before in the LLM space (see Anthropic), this is just hedging their bets.

Improving GPT‑5.6 Sol in ChatGPT, expanding GPT‑5.6 Luna access for free users

>with their daily active users count, OpenAI and Anthropic would have been profitable for years if that was true. No they wouldn't have. Low cost isn't no cost, R$D is expensive and there are a class of tokenmaxxing users well outside the median (e.g Agentic Coding). > I don't know where you get that from https://cloud.google.com/blog/products/infrastructure/measur... https://epoch.ai/gradient-updates/how-much-energy-does-chatg...

Gentoo bugzilla closed due AI bot scraper overload

While we're dealing with the same issue at work, I sometimes still wonder exactly who these scrapers are. OpenAI, Google, Anthropic and others are normally fairly well behaved (Minus Anthropic attempting to hide behind a browser-for-hire company). Mostly you can get IP range and user-agents for the large players, while it problems mostly stem from bots pretending to be Chrome. Our largest offenders seems to be mostly limited to South-East Asia, so probably mostly Chinese AI projects, but that's speculation. I also don't recall ever seeing Grok IP ranges or a specific Grok UA, but that doesn't mean that they're hiding, perhaps they're just not interested.

U.S. Department of Energy Launches the Genesis Open Models Initiative

> Why are Anthropic's and OpenAI's annualized revenue about $50B each? I too can have $50B revenues by selling dollars for 50 cents each, and in the process I'll make a smaller loss than they do.