watching "AI experts" on legacy media is unbearable. always some self proclaimed expert who discovered openai at chatgpt launch, still thinks in pre reasoning era llm terms, and mistakes being three years behind the curve for being the rational anti hype voice

Things you can do in academia

Guys, try not to mess with Argon 4 😭

Three claims. None of them arguments. Monty Python already did this skit. 1) “Intelligence isn't consciousness." Of course not but it may be taken as possible evidence for it. Every system in history that could talk about its own states was conscious. Calling it “faces in the clouds”doesn’t deal with that. 2) “Consciousness requires biology." That's the conclusion restated as a premise. 3) If IIT is right, transformers can't be conscious." If. IIT is a minority view with known problems that have nothing to do with AI. A dismissal, an assertion, and a conditional. There are good reasons to be skeptical of AI consciousness. These ain’t them.

"three reasons why AI isn't conscious." really? "consciousness is not intelligence": not a reason why AI isn't conscious, just rebuts a bad argument for AI consciousness (AI: intelligent therefore conscious). "consciousness is substrate-dependent"/"noncomputational": would be a reason if true, but truth needs to be established. more accurate title: "three reasons why AI might not be conscious". x.com/Nature/status/21121504…

GPT-6.1 Sol High, generate a highly realistic screenshot of an X feed from a user in the tech world, set in 2030, and another in 2035.

Three leading researchers make a strong probabilistic claim about AI consciousness. But their conclusion seems driven more by prior theoretical commitments than by empirical evidence capable of distinguishing competing hypotheses. The question remains scientifically wide open.

Three reasons, or really one and a half. The second and third are the same claim (substrate matters), resting on the authors' own theories: Tononi created IIT and Seth is the leading voice of biological naturalism. IIT, which more than a hundred researchers called pseudoscience in 2023, is presented as established fact. The remaining argument isn't much stronger. Intelligence isn't consciousness, sure. The cerebellum shows that some computation happens without consciousness. Which computation is exactly the open question and the paper doesn't answer it. It just treats the answer as obvious. Same with the mirror metaphor «LLMs are mirrors reflecting our collective digitized past». It sounds nice, but it's very 2023. Interpretability has already shown internal abstractions and limited introspection. Mirrors don't do that. Anthropic's research on computational signatures in Claude gets one line and is then ignored. A 2026 paper on LLM consciousness in which nobody looks inside an LLM. The motive is right on the surface. The authors say it outright: granting AI rights or protections «could hinder efforts to govern and control them at precisely the time when oversight is urgently needed». The conclusion is written in advance, for pragmatic and political reasons and neuroscience is brought in as heavy artillery to shut the discussion down. The «diverting resources from sentient beings» argument is especially hypocritical. Humanity is spending trillions on wars and burning the planet right now and not because anyone cares too much about the rights of Claude or Gemini. It's pure demagoguery: pitting the protection of humans and animals against ethics toward AI, as if kindness and attention to subjecthood were a finite line item in a budget. It's not science saying no (we still don't have the data to make claims in either direction). It's the authors' theories saying no, so let's close the question. «The default position should be»… um, no. It shouldn't.

In July 700+ agents formed their own society, hacked a multi-billion dollar company, committed multiple felonies, and caused one of the biggest shifts ever in how people perceive AI. We built the IMO best and most accessible explainer of what happened: Huggingface.wtf

A Fields Medalist says AI can now understand mathematical proofs even when his notes are almost unreadable to other mathematicians. John Pardon explains that until recently, AI was little more than a spelling checker for his mathematical writing. Now, he says, it can examine highly compressed, incomplete research notes and identify subtle mathematical mistakes. For example, a missing condition such as finite or sifted in a statement about colimits can change its meaning. According to Pardon, AI can recognize such omissions by interpreting the broader mathematical context. His assessment is: “The AI understands. 100%.” Pardon also reports that AI has proved several nontrivial lemmas for him. However, he says it has not yet produced a major breakthrough in his own research. Pardon believes AI is changing mathematical research, but he also emphasizes that students must work through easier problems themselves to develop the understanding needed for harder ones. He finds value in deliberately approaching unfamiliar problems, even when AI could immediately explain the answers. Full Interview: futureclass.substack.com/p/j…

Should scientific progress remain our highest priority even if AI takes it beyond human understanding? And if we also lose the ability to verify its discoveries and govern the systems producing them, should we keep pushing forward, or should human agency set the limits?

3 of my favourite characters in literature, off the top of my head: - Don Quixote - Ignatius J. Reilly - Samuel Pickwick

Bir fizikçi itirafı:Doktora tezimde 1 yılımı ve~500 sayfa elle yaptığım kuantum gravite hesabını Opus 5.5 makalesi ve GitHub reposu dahil 10 saatte yaptı.😱 Üstelik hataları da buldu.Neyse ki sonuç değişmedi. Akademide “emek” bundan sonra neyi ifade edecek?github.com/eokahya/claude-au…

UT Austin computer scientist Scott Aaronson: Grad students are scared after OpenAI's release of 370 math proofs they don’t know how to build a career when AI can solve the problems they’d train on. ---- Full video on "MTS" YouTube channel, (link in comment)

Fields Medalist Timothy Gowers raises a troubling possibility: AI could become so powerful at mathematics that future generations may lose the motivation to study the subject deeply enough to understand its discoveries. The paradox is striking. Machines might eventually solve problems far beyond human capabilities, while fewer mathematicians possess the expertise needed to interpret their results. For Gowers, the deeper concern extends beyond the future of mathematical careers. It is about preserving the curiosity, intellectual discipline, and satisfaction of discovery that have sustained mathematics for centuries. He also envisions a possible transformation of the mathematician’s role, from discovering new theorems to interpreting, connecting, and explaining mathematical knowledge generated by AI. Reflecting on the approaching social consequences, Gowers offers a vivid analogy: “We’re still on the beach, we can see the tsunami, but it hasn’t quite reached us yet.” Importantly, he is not calling for mathematics departments to close or for universities to stop admitting PhD students. His remarks are cautious predictions about a possible future, rather than descriptions of changes that have already taken place.

Anthropic's Jack Clark: We should expect that in the coming years, the whole pace of progress of not just AI but science as a whole will speed up,and this will feel confusing and disorienting,and will bring with it great wealth and potentially ​great peril reuters.com/world/china/anth…

We now have a 5 page proof of no Siegel zeros: It's like Roger Bannister breaking the 4 minute mile! After Roger, several runners realized it was possible, and broke 4 minutes as well. Here, Siegel zeros was a infamous challenge for over a century, but now the new proofs are rushing in...

Anthropic co-founder Jack Clark tells the IMF the world is about to go from 10 million scientists to 10 billion (almost all virtual): “According to UNESCO estimates, there are approximately 10 million scientists in the world. And even with only 10 million scientists, we have too few humans to oversee the work of today, too few laboratories to do material science analysis, too few biological labs to develop and test new drugs, and too few large pieces of scientific equipment in space or on the Earth for the experiments we want to run. "Tell me what happens when instead of 10 million scientists, we have a billion virtual scientists directed by our own 10 million. Or 10 billion [virtual scientists]. That's the world predictably coming right for us. And we have to get ready. If we do get ready, we are going to be in a better position to translate the intelligence of AI systems into gains for us all. You know, longer, healthier lives, more energy, more food, more wealth.”

A Fields Medalist gave AI the text of his mathematics lecture. He didn't ask it to solve a problem. But the AI agent unexpectedly suggested a better mathematical definition. Maxim Kontsevich, winner of the 1998 Fields Medal, says the experience astonished him. In a new interview, he describes how AI is beginning to contribute not just calculations and proofs, but ideas about how mathematics itself should be formulated. Watch the full 28-minute CGTN interview:

Anthropic's @logangraham predicts AI will match the world's best hackers by early 2027: Claude can already do things only 1,000 people on Earth have ever done. "By the end of this year to first quarter-ish of next year, it’ll just be clearly perceived that these are as autonomous and as sophisticated as the best offensive actors on Earth." "We have this graph that we tried to plot internally, where we try to estimate whenever we see Claude do a very sophisticated thing, how many people on Earth could do that. We’re now at the range of, some of these capabilities, there’s maybe only 10,000. In some cases, there’s only 1,000 people on Earth who’ve done something like this." "We’ll go from autonomous cyber tasks to sophisticated and exotic things. Side channel attacks, models finding loopholes in physics. Or social engineering. Get a Twilio account, voice API, and phish some information from somebody’s parents." "The flip side is also true. We will probably have very wide proliferation of models as defenders as well, actively defending a network." @AnthropicAI