A curious mind, always exploring the vast landscapes of knowledge and creativity. Passionate about learning, the future of AI, and philosophy
South East Asia 📍
Joined April 2011
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Extended Brain retweeted
As Election Day approaches, writer Alex Stone explores what topology teaches us about democracy and the strange paradoxes it can give rise to: quantamagazine.org/how-votin…
Extended Brain retweeted
Çok çok acayip bir siteye denk geldim. Adam interaktif bir dinler tarihi hazırlamış. Harita ve grafik üzerinden ayrımlar ne zaman başlamış inceleyebiliyorsun. Sitedeki 69 bölümün tamamını okumak 26 saat sürüyormuş. Hastasıyım böyle kafası kırık adamların. howitevolved.com/
Extended Brain retweeted
Introducing Kimi K3.1 Pro: our most capable 3T-class open-weight model.
🔹 1M-token context, 2.8T total / 104B active params (MoE), Multimodal.
🔹 Full-project coding: games in Unreal, Unity & Godot.
🔹 Excels at parametric 3D modeling in Blender & CAD.
🔹 More reliable at finance work: Accurate modeling with hallucination down by 65%.
🔹 Matching the strongest proprietary models across coding, agentic and knowledge benchmarks.
Kimi K3.1 Pro and K3.1 Pro Highspeed (2–3× faster) are now live on Kimi.ai, Kimi Work, Kimi Code, and the Kimi API.
Open weights by Nov 4, 2026.
🔗 API: platform.kimi.ai
🔗 Tech blog: kimi.ai/blog/kimi-k3-1-pro
Extended Brain retweeted
🚀 DeepSeek-V4.1-Flash-1017 is here!
Stronger benchmark performance, faster task completion, and shorter outputs than the previous version—a Pareto improvement in performance and cost. Now live on our website, app, and API.
🛠️ Optimized for @DeepSeekHarness, Tencent CodeBuddy, WorkBuddy, and more. Upgrade to DeepSeek Harness v0.2.1-rc.1 or later for the best experience with the new model.
1/4
Extended Brain retweeted
The AI Scientist v3 is out: The Agentic Scientist.
GitHub: github.com/SakanaAI/AI-Scien…
Blog: pub.sakana.ai/agentic-scient…
arXiv: arxiv.org/abs/2610.18933
The Agentic Scientist is the 3rd iteration of our automated AI Scientist research system, and the shift this time is from “one agent writes a paper” to “a scaffold of parallel agents orchestrates the full research loop.”
The system now orchestrates a pool of parallel workers that share memory and distilled conclusions. Crucially, it features Evidence Generation: isolated agents automatically run controlled baselines and ablations to prove why an idea actually works.
It works as a co-scientist. We used a development version as a co-scientist to explore biologically plausible learning rules. The agent handled the empirical heavy lifting, proposing mechanisms and running experiments. We stayed in the loop to steer direction, verify results, and moderate claims. That feels like the right division of labor for where the technology actually is.
This resulted in a new biologically plausible learning algorithm, and the resulting paper was accepted at ALIFE 2026 as an oral presentation.
We are also releasing AutoIllustrate. It generates editable draw.io vector figures instead of uneditable, hallucinated raster images. Real scientists need vectors, not pixels. I am an SVG junkie ;)
Incredible work by Robert Lange, Luca Grillotti, Yutaro Yamada, Rujikorn Charakorn, and the team!
The Agentic Scientist: Orchestrating Coding Agents for Automated Scientific (Co-)Discovery
Blog: pub.sakana.ai/agentic-scient…
GitHub: github.com/SakanaAI/AI-Scien…
arXiv: arxiv.org/abs/2610.18933
Since 2024, we’ve used The AI Scientist as a way to test how far AI alone can take scientific research, from v1 to v2 to the paper published in Nature earlier this year. The Agentic Scientist is the next step in that line of work, built for the era of coding agents.
Coding agents such as Codex and Claude Code now carry out long software tasks on their own. Handing them a research problem, however, tends to produce a strong hyperparameter optimizer rather than a scientist: scores go up, but ideas stay narrow, and the reasons for the gain are rarely examined.
The Agentic Scientist makes the research loop explicit. It wraps off-the-shelf coding agents in a scaffold that controls what they see, what they write, how they are evaluated, and how results are handed to the next stage.
Parallel workers test hypotheses against rubrics defined before any experiment runs, share successes and failures through a common memory, and then ablate the winning program to generate evidence.
We used an early version of the system to study Error Diffusion, a biologically motivated alternative to backpropagation. Our researchers set the question and the rubric, chose directions at each stage, and verified the results, references, and claims before submission. The resulting paper was accepted as an oral presentation at ALIFE 2026. In autonomous runs, the system also raised Doc-to-LoRA retrieval accuracy from 52% to 98% on multi-needle tasks and designed a learned evolution strategy that improves over its CMA-ES reference on unseen tasks.
Alongside it we release AutoIllustrate, a pipeline for scientific figures that keeps an editable draw.io file as the source of truth, so every diagram can be corrected by hand.
Humans define the question and the standards of evidence; agents expand the experiments researchers can run. We call this Co-Discovery, and we are releasing both systems as open source for the community to build on.
Extended Brain retweeted
A number of these results are in theoretical or mathematical physics!
For example: A proof of spontaneous magnetization in quantum Heisenberg ferromagnets (Lean-verified)
If it survives scrutiny, it would be the first rigorous proof of quantum ferromagnetic order and a landmark in mathematical physics, with or without AI.
Claude:
The question is whether, at a low but nonzero temperature and with no external field, an infinite magnet spontaneously picks a direction and becomes magnetized. Physicists have assumed the answer is yes since Bloch's spin-wave theory in the 1930s. Proving it rigorously has been another matter:
Dimensions 1 and 2: the Mermin–Wagner theorem shows it can't happen, so the question is only for 3 or more dimensions.
The classical version (spins as ordinary arrows) was proved by Fröhlich, Simon and Spencer in 1976 using "infrared bounds."
The quantum antiferromagnet (neighbors anti-align) was proved by Dyson, Lieb and Simon in 1978 with a related technique called reflection positivity.
The quantum ferromagnet is the case that stayed open. Reflection positivity doesn't give the needed bound there, which Dyson–Lieb–Simon pointed out themselves. The paper notes that Lieb listed it as an open problem in 1999. Results since then, such as Correggi–Giuliani–Seiringer's 2015 free-energy asymptotics, controlled thermodynamics and finite length scales but never produced an ordered state.
What's claimed
For every dimension d ≥ 3 and every spin S (½, 1, 3/2, …), at all sufficiently low temperatures, there is a translation-invariant infinite-volume equilibrium state (a KMS state, the rigorous definition of "thermal equilibrium" for infinite quantum systems) whose spin expectation is at least S/4. In other words, a genuinely magnetized phase exists.
For spin ½, the paper also derives a consequence for lattice bosons: a form of the long-range order associated with Bose–Einstein condensation.
We’re releasing a broad range of new mathematical results produced by an internal frontier model.
We’ve been consulting with the independent Advisory Group on Mathematics and Artificial Intelligence at the Institute for Advanced Study, and we have drawn on their advice and public recommendations to inform how we release these results.
github.com/openai/math
Extended Brain retweeted
Today @KarlDeisseroth of @StanfordMed @Stanford won the @NobelPrize for his co-discovery & development of Optogenetics. Here he explains what that is, and how it is unlocking the secrets of brain function & helping to cure diseases.
(And he explains that in ~1min).
Extended Brain retweeted
wow. another one
Mathematician Benedikt Jahnel said that, if a human had solved a problem like this, it could plausibly have been Fields Medal level work 👀
AI just solved a decades old “holy grail” problem in probability theory that resisted elite mathematicians for decades
Anthropic says its AI generated a proof resolving a famous conjecture in percolation theory, the mathematics of how random local connections suddenly form large scale connected structures.
The big open question concerned dimensions 3 through 10. Mathematicians already knew the relevant phase transition was continuous in 1D, 2D, and dimensions 11+, but the middle range had remained unresolved. The new AI generated proof shows that the transition is continuous there too, filling the decades old gap.
2022 Fields Medalist Hugo Duminil-Copin had tried and failed to solve the conjecture, then wrote in late August that it was only a matter of time before AI beat humans to it.
Extended Brain retweeted
Introducing Gemini 4 Argon – our new frontier model.
It’s built for complex workflows across coding, enterprise knowledge work, and cybersecurity defense – rolling out today to a set of trusted testers through our Fairwind Program.
Extended Brain retweeted
Claude has discovered a previously unknown enzyme system hidden in the DNA of bacteriophages. Beside the enzyme’s gene sits a long array of repeating DNA—a structure that looks somewhat similar to CRISPR.
We don’t yet understand what this system does, but only a handful of known systems share its features, and all of them are able to cut, copy, and paste DNA. Historically, the discovery of such programmable systems has helped revolutionize medicine. CRISPR, for instance, is now the foundation of genetic medicines. But it will take much more work to learn what this system does, and whether it can be put to similar use.
Read more: anthropic.com/news/claude-di…
Extended Brain retweeted
big AI news
Google just demonstrated a recursive self improvement loop for AI discovery
Google/DeepMind researchers introduced Dream-RSI, a system where an AI agent improves how it explores problems by replaying its past discovery attempts, testing thousands of alternative strategies cheaply, then deploying the better strategy in the next round.
Across algorithm design, mathematical optimization, and GPU kernel engineering, it matched or improved discovery quality while cutting search costs dramatically, in one setting reducing agent calls by up to 162x. 👀
Importantly, it improves the exploration policy, not the underlying model weights.
Extended Brain retweeted
We’re introducing Gemini 3.8 Live and 3.8 Live Extended Thinking – our best conversational AI.
The models talk, think, and handle tasks in the background without breaking your flow. 🧵
Extended Brain retweeted
TradingView yeni bir kapı açtı: Resmî MCP Server artık beta olarak kullanıma sunuldu.
Bunun anlamı şu: TradingView verileri ve bazı platform araçları artık ChatGPT, Claude ve MCP destekleyen diğer yapay zekâ istemcileriyle doğrudan bağlanabiliyor.
Şu anda MCP üzerinden OHLCV verileri, screener sonuçları, teknik göstergeler, haberler, temel veriler, ekonomik takvimler, watchlist’ler ve alert’ler gibi birçok veriye erişilebiliyor. Bazı işlemler, örneğin alert oluşturma ve watchlist yönetimi de destekleniyor.
Bağlantı OAuth 2.1 ile yapılıyor; API key gerekmiyor. TradingView tarafında özellik Essential ve üzeri planlarda sunuluyor.
Ben de bugün ChatGPT ile bağlantıyı kurup test etmeye başladım.
Şimdilik kişisel Pine Script indikatörlerinin kendi ürettiği özel değerleri doğrudan okumaya yönelik bir araç görünmüyor. Ancak MCP araç seti beta aşamasında ve TradingView bunun zamanla genişleyeceğini belirtiyor.
Bence asıl ilginç olan, piyasa verisi ile yapay zekâ arasındaki bu doğrudan bağlantının bundan sonra nereye evrileceği.
Resmî TradingView MCP dokümantasyonu:
tradingview.com/mcp/docs
Extended Brain retweeted
AI is ravenous and is eating mathematicians' lunch. A long-standing problem is solved, others are in its sights. But is this more than just a problem about problems? Here's Fields Medallist James Maynard.
Read the Fields Medallists' Declaration: mathandai.org/
Extended Brain retweeted
New post by Terry Tao, and a new declaration on AI and mathematics signed by 25 Fields Medalist
terrytao.wordpress.com/2026/…
Extended Brain retweeted
BREAKING: Terence Tao and 24 other Fields Medalists just signed a letter telling AI companies they're destroying mathematics
>headlines: AI solves famous math problems
>25 greatest mathematicians respond today
>"we are witnessing a general threat to intellectual work"
>ai labs are treating math problems like a benchmark you can brute force
>“solutions are announced in a rush, leaving no time for a proper writeup and citing relevant previous work of others"
>they're talking about openai
>"this raises severe attribution and plagiarism questions"
>they're definitely talking about openai
>openai offered to put math professor name on navier-stokes proof
>condition: abandon his coauthor bc he works at anthropic
>"the most precious resources of our profession are students and ideas"
>for the labs the most precious resource is GPUs
A Severe Misalignment of AI in Mathematics
Extended Brain retweeted
We benchmarked DeepSeek V4.1 Flash by @deepseek_ai .
It reached 98% of GPT-6 Astra’s score at 1.4% of the cost on everyday design tasks based on user requests.
Every model except Astra scored lower AND cost more.
Are open models overtaking closed ones?
Full results below ↘️
