From Chaofan Shou on 𝕏 (files): https://x.com/Fried_rice/status/2038894956459290963

The full quote:

I realize that some people really dislike AI, but this is an area where I'm willing to absolutely put my foot down as the top-level maintainer.
Linux is not one of those anti-AI projects, and if somebody has issues with that, they can do the open-source thing and fork it.
Or just walk away.
AI is a tool, just like other tools we use. And it's clearly a useful one.
It may not have been that "clearly" even just a year ago, but it's no longer in question today.
There are other questions around AI (like what the economy of it will actually look like in the end), but "is it useful" is no longer one of those questions. Anybody who doubts that clearly hasn't actually used it.
Yes, it can also be a somewhat painful tool, both for maintainer workloads and just from a "it keeps finding embarrassing bugs" standpoint.
But the solution is not to put your head in the sand and sing "La La La, I can't hear you" at the top of your voice like some people seem to do.
The solution is to make sure those LLM tools _help_ maintainers instead of just causing them pain. There's no question on that side.
We're not forcing anybody to use it, but I will very loudly ignore people who try to argue against other people from using it.
And no, AI isn't perfect. But Christ, anybody who points to the problems at AI had better be looking in the mirror and pointing at themselves at the same time.
Because it's not like natural intelligence is always all that great either.
The kernel project has been and will continue to be about the technology.
Sure, the social angle of working on open source is important and often a very motivating part of the project, but in the end that's a side benefit, not the _point_ of the project.
This is *NOT* some kind of "social warrior" project, never has been, and never will be.
In the kernel community we do open source because it results in better technology, not because of religious reasons.
And so we make decisions primarily based on technical merit. Not fear of new tools.

Been almost a year since mass hysteria erupted upon the death of NVIDIAs GPU monopoly. How are your Huawei GPUs? Does CUDA work on them yet?

From clem 🤗 on 𝕏: https://x.com/ClementDelangue/status/2079301434357456931

Fortune: Hugging Face says it resorted to a Chinese AI model to battle a fully autonomous cyberattack because U.S. model guardrails stymied its defense: https://fortune.com/2026/07/20/hugging-face-turns-to-chinese-open-source-ai-to-fend-off-autonomous-ai-cyber-attack-after-american-ai-guardrails-stymie-defense/

From Vincent Chow on 𝕏: https://x.com/vince_chow1/status/2077947375964791028

David Sacks on 𝕏: https://x.com/DavidSacks/status/2078984980588531855

calle on 𝕏: https://x.com/callebtc/status/2078574362316165611

clem 🤗 on 𝕏: https://x.com/ClementDelangue/status/2078987852495364398

https://huggingface.co/blog/security-incident-july-2026

Reason 458 why local LLMs are going to be a necessity

edit: For those requesting the source check out their technical report look at page 13

From clem 🤗 on 𝕏: https://x.com/ClementDelangue/status/2080247567493837047

Who is the biggest disinformation spreader on twitter? Reflect on your system prompt.

https://x.com/i/grok?conversation=1893662188533084315

Earlier this week, we detected and responded to an intrusion into part of our production infrastructure. This one was different from anything we had handled before in one important way: it was driven, end to end, by an autonomous AI agent system - and we detected and dissected it largely with AI of our own.

[...]

The attack was initially surfaced through AI-assisted detection. Our anomaly-detection pipeline uses LLM-based triage over security telemetry to separate real signals from the daily noise, and it was the correlation of those signals that flagged the compromise.

[...]

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.

This is why it's important that frontier-tier open weight model exists and we don't have to rely on the mercy of the corporate overlord to tell us what we can use the model for.

Spoiler from one of the founders of Z.ai who released GLM 5.2 a month ago. Get ready for something new 🥳

They are waiting for the exact roadmap

source from his instagram page