Vaclav Tunka (EN)

Engineering lead at @RedHat: @OpenShift cloud-native app-dev & applied AI portfolio. Languages, sport, travel. My own opinions.

[Red Hat Security @RedHatSecurity]

Important memory corruption flaws in PHP's request handling have been identified: CVE-2026-109618 and CVE-2026-109619. Red Hat is expediting fixes, with some updates already available. The latest updates are available here: https://t.co/k9UZ1RmSUT

[Red Hat @RedHat]

Red Hat AI Factory with @NVIDIA is helping enterprises scale autonomous agents with trusted security and control. The latest innovations span agent safety with the OpenShell Reference Architecture, optimized support for the latest open models, and Day 0 enablement for NVIDIA Vera Rubin. Learn more: https://t.co/lP2ifajPEe #NVIDIAGTC

[Red Hat @RedHat]

Scale distributed inference and control AI serving costs with confidence. llm-d 1.0 brings multi-tenant quality of service, zero-downtime rolling updates, and prefix-cache-aware routing to your production workloads. Explore the release: https://t.co/4YaxviT5Z6 #PyTorchCon

[Chris Wright @kernelcdub]

When measuring open source security, counting vulnerabilities only tells part of the story. Real risk depends on context, attack paths, and how fast reusable fixes can travel through the software ecosystem. Check out the new Open Source Security Signals: https://t.co/E4ujRDCsnK

[Grady Booch @Grady_Booch]

Let’s be very clear: there is value in automating tedious and repetitive and dangerous tasks; there is value in delegating certain work to our machines that can do the work tirelessly and much faster.

But at the same time, let us remember that there is value in the activity of engaging one’s mind and body to discover, to understand, to create, and yes, even to struggle and overcome. Indeed, these are some of the things that make us human, that contribute to giving us meaning, that are part of the simple joy of experiencing being alive.

[Grady Booch @Grady_Booch]

It’s artificial intelligence, Sundar.

And in the history of computing, this puerile attempt to rename it simply because of the simpleminded whims of an incompetent and corrupt narcissist will be seen as a failure of leadership, an abandonment of intellectual integrity, and an embarrassment for any who join with him.

[Grady Booch @Grady_Booch]

I can’t decide if people who assert that contemporary AIs can think or are conscious do so out of fear or out of envy.

But I can say that any such people do so either out of emotion or perhaps driven by some pecuniary interest in it being true, not from any fully informed or defensible position.

[Grady Booch @Grady_Booch]

Speaking of scientific, Joscha, you of all people should know that one cannot prove a negative.

Indeed, you make the claim that LLMs can think.

Extraordinary claims require extraordinary evidence, as Carl Sagan observed. Thus, the onus is on you and others who make that claim to give evidence as to its veracity. The process of science then follows to test that that claim.

By inverting the demand you yourself are engaging in unscientific methods.

[Yann LeCun @ylecun]

@PessimistsArc Right. Dario was already claiming that GPT2 was too dangerous to open source back in 2019.
I made fun of them then.
Everyone should make fun of them now.

[Red Hat AI @RedHat_AI]

The overview, why the context wall happens and why offloading is the fix: https://t.co/8i2gf3pbAw

The how, enabling KV cache offloading in @vllm_project: https://t.co/c3xDXPkiY3

[Vaclav Tunka (EN) @vtunka]

To friends in Israel and around the world celebrating - may the arrival of Rosh Hashanah bring with it the promise of peaceful renewal; may the silence of Yom Kippur be an occasion for peace and inner light; may the festival of Sukkot be filled with joy, gratitude and fellowship.

[Hedgie @HedgieMarkets]

🦔An NYU mathematician says OpenAI used his own progress against him to beat him to one of the biggest unsolved problems in mathematics. Tristan Buckmaster had been working toward a Millennium Prize proof using OpenAI's Codex when information about his progress reached OpenAI.
Days later, OpenAI published a full proof of the same problem using the same uncommon approach, after burning $22.5 million in compute to get there. When Buckmaster confronted them, exec Sébastien Bubeck allegedly said "Why would you ruin your career?" and "If you don't want me to be nice, then I don't have to be nice."

My Take
OpenAI spent $22.5 million to solve a problem with a $1 million prize. They didn't do this for the bounty. They needed a headline that says "our AI solved one of the hardest problems in mathematics" and they needed it before someone else got credit. They started days after they heard about Buckmaster's progress and took the same uncommon approach he'd pursued for months. That's hard to explain as coincidence.

Buckmaster did his work inside Codex. OpenAI reserves the right to train on Codex data. They admit they can't rule out that his usage helped improve their models. So a customer used their product, potentially handed them the roadmap, and then OpenAI outran him with $22.5 million in compute he could never match. I don't know if any of this was intentional. But if you're a researcher and you just watched this happen, I don't think you'd keep your best ideas inside someone else's product.

Hedgie🤗

https://t.co/1YnggU7xdI

[Grady Booch @Grady_Booch]

I do not fear the rise of artificial intelligence.

But I do fear the rise of a small set of billionaires and companies who seek to build such things to increase their power and their wealth, all without transparency or accountability.

[Tim Cook @tim_cook]

Sending lots of love to the Apple community on my last day as CEO. My title changes tomorrow, but the love I have for the Apple community never will. Thank you for being a constant source of inspiration. My gratitude is endless, and I’m excited for the next chapter!

[Jim Whitehurst @JWhitehurst]

Happy birthday, Linux! It's been an amazing 35 years!!

[Sherpa @LLMSherpa]

Naturally, hard times tend to make folks withdraw into themselves; become more insular, more isolated, and focus on their own self-interest to a higher degree.

I think we have to resist that urge, though.

To force ourselves to the common good; to become the leaders we need.

[Gergely Orosz @GergelyOrosz]

Looked back at a product manager who used to have lots of original writing on social media and over email a few years ago.

Has 10x as many followers now… and an account that is ALL AI slop. Like unbearable generic slop slop. Nothing about PM any more.

Is this another form of “AI physosis” for a “content creator?”

I do not understand what the thinking of such folks is. “I managed to find a way to spend 10x as little time to spend on social media / newsletter writing and have 10x as much output with AI” thinking?

Except it went from interesting to terrible. No longer putting in any effort

[Jim Whitehurst @JWhitehurst]

Check out the latest article in my newsletter: What Open-Weight AI Can Learn From Open Source https://t.co/GjV5gAphNi via @LinkedIn

[Red Hat @RedHat]

How are leading organizations moving #AI from experimentation to enterprise value? Hear from @RedHat CTO @kernelcdub on how hybrid cloud platforms help scale AI workloads efficiently: https://t.co/sLHQjWrWkk

[Valerio Capraro @ValerioCapraro]

I think this is the most important concept to understand right now: LLMs can’t jump.

OpenAI says an internal version of Astra, its next major model, has solved ten major open problems in mathematics and theoretical computer science.

This is extraordinary.
And I don’t use this word lightly.

During my PhD in mathematics, I worked on a problem closely related to Gromov’s conjecture. For decades, constructing a non-sofic group—an infinite group whose finite pieces cannot be approximated by finite groups—was a dream shared by many of us.

Now Astra appears to have done it.

This is not a toy result. This is serious mathematics.

But it is not “the most significant day in the history of mathematics”, as some have claimed.

This claim confuses scale with kind.

Astra has solved difficult problems inside existing conceptual worlds.

Calculus, topology, and scheme theory created new conceptual worlds.

They did not merely answer questions. They changed which questions mathematics could ask.

Induction finds patterns. LLMs are extraordinary at it.

Deduction follows implications. Using symbolic AI tools, LLMs are becoming formidable at traversing chains of logic that humans missed, abandoned, or could never afford to search.

But abduction is different.

Abduction invents the right concept, the right representation, the right question.

That is the jump.

Current LLMs can fill the gaps of knowledge left by humans.

But they can’t jump beyond the external boundary of existing knowledge.

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Full paper in the first reply