self-training is possible when using something external to validate the results

I don’t think the cost of hosting the repositories itself is the issue, more the legal problems and the fact that real projects get drowned out by the noise

It seems like the marketing cooperated on writing the incident report, but I felt it was still interesting to share considering the importance on public perception and what it tells about OpenAI’s PR strategy

Huggingface actually had to use an open model to analyze the attack because the guardrails of commerical API’s caused issues.

When we started the log analysis, we first used frontier models behind commercial APIs. This did not work: the analysis requires submitting large volumes of real attack commands, exploit payloads, and C2 artifacts, and these requests were blocked by the providers’ safety guardrails, which cannot distinguish an incident responder from an attacker. We ran the forensic analysis instead on GLM 5.2, an open-weight model, on our own infrastructure. This had a second benefit: no attacker data, and none of the credentials it referenced, left our environment.

Security incident disclosure — July 2026

And Chinese AI like Deepseek and GLM

It could also be a way to encourage more regulation to push out competition with compliance cost

From my personal experience, most companies don’t look at the benchmarks and simply buy “AI” from a company based on their perception of that company.

All the Chinese models are scary and “dangerous”, Grok too (but for slightly more legitimate reasons), Meta that’s Facebook and everyone knows they’re bad at privacy (even your boss), so they end up choosing Microsoft’s AI, OpenAI, or Anthropic.

Windows is still good enough for Microsoft to sell licenses, sell services, and other large contracts.

It does not need to be faster, safer, or generally “better” since there is no competition in the traditional sense. Almost everyone is trained to work with Windows and almost all software works on Windows, so it’s just (seen as) a more sensible option for most businesses.

Great excuse to show off that beautiful view

I do wonder if this is similar to Mythos, where the company deliberately stokes fears to get people talking about it and spread the assumption that it will actually happen and is a big deal (and to avoid people’s first question about whether it will actually work).

Luckily it probably won’t get made and the company will just rugpull their investors

Would DDR4 or DDR3 be easier to produce?

It’s interesting how certain companies and organizations have such large ranges, 16m IP’s each for both that old printer company and a farmaceutical company is a lot. It really shows the history of the internet and how seemingly certain companies that adopted it first ended up with huge chunks of the available IPv4 space.

Better than that

Mitosis, if cells classify as mechanical

And even if they publish the model it’s almost always just open weights

According to artificialanalysis.ai’s latest benchmarks, it scores better than Opus 4.8 set to max, despite costing half as much per task.

It also beats the top models of some of the largest US tech companies such as xAi, Meta, Google, and Nvidia.

I wonder what the US tech investors will think of this, and what this will mean for the financial AI bubble.

You can use it through openrouter

AFAIK, their open models are distributed as weights, not executables and are therefore not able to start network connections / run code. There is of course tool-calling functionality but that just works by having the model output a special pattern and having something external run predetermined commands based on that.

Nuclear landmines?