Armando Vieira retweeted
Cuántas HORAS de trabajo cuesta llenar un depósito de gasolina de 50 litros.
🥉 Razonable:
🇨🇭 Suiza — 3 horas
🇺🇸 EEUU — 3 horas
🇩🇰 Dinamarca — 4 horas
🇦🇺 Australia — 4 horas
🥈 Aquí empieza a doler:
🇩🇪 Alemania — 5 horas
🇪🇸 España — 7 horas
🇮🇹 Italia — 8 horas
🇵🇹 Portugal — 11 horas
🥇 Misión Imposible ↓↓↓
The irony of AI is that this Mafia effect is greatly amplified
There’s a dark side to science. If you’re outside the inner circle, you probably know this all too well.
Emmy Noether didn't write Hilbert's equations. She formulated much of what his theory was based on; invariance, symmetry, conservation. Yet was denied habilitation taught under Hilbert’s name and worked without pay.
So many examples of this that there's a term for it: the Matthew effect.
But it isn’t only race or sex that determines the way recognition compounds around the already recognized. It's whether you’re in the club.
Physics runs through elite networks that shape who gets funded, published, cited, and heard. Nobel included. Nominations and evaluations stay secret for 50 years. The physics prize is decided by the Royal Swedish Academy of Sciences through its Nobel Committee.
JASON is a real, closed scientific advisory group for the U.S. government. Much of its defense work is classified. Scientific influence can sit inside networks most people never see.
You don’t need to name the cabal running physics to understand the mechanism.
If you’re outside the club, your work can be ignored for years. Then suddenly echoed back to you through the "proper" channel, penned by the "right" person.
Armando Vieira retweeted
Sony built an AI that discovers scientific facts on its own.
And it reportedly discovered actual previously unknown facts about "aging"
It's called "Hakken"
Hakken analyzes millions of research papers, maps how scientific facts evolve over time, and predicts exact, undocumented relationships that humans haven't found yet.
It generates a mathematical confidence score for scientific facts that do not currently exist in any literature.
Researchers pointed it at the biology of aging. The AI generated 1.5 million brand-new hypotheses.
But they didn't stop at the computer screen.
They took the AI's best predictions and physically tested them in a real-world wet-lab.
And the results are historic.
Physical lab confirmed two previously undocumented biological interactions in the human body (involving TP53, BAMBI, RAF1, and TNF).
the AI successfully saw the invisible mechanics of biology that human scientists had missed. And the lab proved it was right.
We are crossing a massive threshold.
We used to build AI to read scientific papers faster. Now, AI is writing the next chapter of human knowledge before we even run the experiments.
The bottleneck for scientific progress is no longer human intelligence.
It is how fast the physical labs can keep up with the machine.
Armando Vieira retweeted
Scorpions kill more than 3,250 people a year, mostly kids, and the cure is still made by milking venom from thousands of scorpions and injecting it into horses. Anthropic just let a team of investment researchers with zero biology background try to cut the horse out.
The horse method is over a century old. You immunize the animal for months, draw its blood, and purify out the antibodies its immune system made. Given early, it works against a narrow set of toxins, and because you're putting horse protein into a child, it can trigger anaphylaxis.
Barely anyone makes it, because the people getting stung can't pay enough to cover the factory. Mexico has about a quarter of the world's scorpion stings and relies on a single lab. Last year in Sonora, a 5-year-old was stung at preschool and rushed to a public hospital that had already burned through a shipment delivered days earlier. Staff found more 45 minutes later. She'd already gone into cardiac arrest twice.
So Citrini Research walked into Anthropic with a question. Could motivated amateurs with Claude make real progress on a disease the drug industry ignores?
An internal Claude model ran for 64 hours off one prompt and four follow-ups. It drove 12 protein design tools, generated 318,484 candidate molecules, ran 553,052 simulated matchups against five scorpion toxins, and picked 180 to build. Then it emailed the order to the lab itself.
Two labs made 211 of them. 17 latched onto their target toxin, covering scorpions from Mexico, North Africa and the Middle East. Brazil's yellow scorpion beat every single design. The best two grab a Mexican scorpion toxin at the same spot as an antibody already shown to protect mice.
The computer finished in under three days. The lab work stretched past a month, held up by contracts, shipping, and the hassle of sourcing the toxins themselves. One of the outside experts who reviewed the results said binding is no longer the main bottleneck.
There's no antivenom yet. None of these molecules has touched a living cell or a mouse.
Anascorp, the only scorpion antivenom the FDA has approved, took 35 years to go from a Mexican lab to US approval. The first candidate molecules for a horse-free successor took 64 hours, for a team whose day job is writing investment research.
New on our Science Blog: designing protein binders against scorpion neurotoxins.
Scorpions sting about 1.2m people every year, and antivenoms are often costly or in short supply. Claude has made an early step toward finding new treatments.
anthropic.com/research/claud…
Three reasons why AI is not conscious and perhaps never will be | Nature share.google/7WXzQYathdf7xdZ…
Something I cover on my book. The AI doom scenario you've never heard of may be the hardest to stop - CBS News share.google/gDnNj7CQYVEi9Gp…
Exciting news: DeepSeek-V4.1-Flash-20261017 (Max) by @deepseek_ai is now the #1 open model in Code Arena: WebDev, surpassing Kimi K3 (Max) at 10x lower cost!
Highlights:
- #1 open model, ahead of Kimi K3 (Max)
- #12 overall with 1670 pts, ahead of Claude Opus 5 (High) and within ~10 pts of GPT-6 Sol (Max)
- Shifts the Pareto frontier at $0.3/$1.2 per million input/output tokens
- +52 pts vs. the previous DeepSeek-V4.1-Flash-20260910
Congrats to the @deepseek_ai team on another strong contribution to the open source ecosystem!
🤖 Made with AI
🚀 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
I asked myself this question all the time. The point is progress in science. Humans have to find meaning in other stuff. Academia business model is done
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…
Armando Vieira retweeted
Our NeurIPS’26 paper is public now. Learning the partner’s mental-state is essential for multi-agent systems. That’s what show in our NeurIPS’26 paper and provide an amortised method to learn it. Checkout our paper and code: hananshafi.github.io/Mental-…
Armando Vieira retweeted
🚨 DeepSeek Just Dropped The Best And Cheapest Open Source Model In The World
- scores on top of the open-source leaderboard
- beats Muse Wonder, Haiku, and Luna
- cheapest in terms of cost per task
Argon is still ahead at the moment
LLM for materials research
news.mit.edu/2026/giving-ai-…
Singularity check: AI writes the code, reviews the code, writes the papers, reviews the papers, and recommends what to read about it all. We're mostly here to press Accept. 🌀
Great Idea
New paper! Science is constrained by physical and economic bottlenecks such as hypothesis testing, especially as many discoveries involve long chains of smaller steps and hypotheses, each requiring validation. As the marginal cost of hypothesis generation goes down, the physical validation cost is likely to remain inelastic in the absence of major investments in scientific infrastructure.
Autonomous science is therefore not merely a question of raw capabilities - the allocation of limited validation capacity matters just as much. We argue that this will require deliberately designed markets and institutions, both to allocate scarce validation capacity to the most valuable work and to ensure public good research isn’t crowded out.
With @weballergy , @FranklinMatija , @Dr_Atoosa , @vivnat , @alan_karthi , @sindero and I.
arxiv.org/abs/2609.31562
Armando Vieira retweeted
That didn’t take long: the model swallows the harness.
arxiv.org/abs/2609.35738
Great idea
China is officially issuing government ID cards to AI-generated “digital humans,” so virtual influencers can open bank accounts and conduct business. These state-issued IDs, which include a name, birthday, address, and facial features, give virtual personas the legal ability to open digital-currency wallets, sign contracts, and form commercial partnerships.
Among the first to receive this recognition is Yuri, a popular AI-generated virtual idol and artist, who is now officially recognized as a “digital resident” in Beijing. The step comes as China’s digital-human market expands, with more than 1.3 million active firms and a sector value past $10 billion.
Supporters describe the IDs as a way to protect intellectual property and hold creator companies legally accountable for virtual actions. Critics warn that placing synthetic entities in official state systems could expand government surveillance in the digital space. Some companies are offering everyday citizens up to $20,000 to license their physical likenesses for virtual replicas, which narrows the line around personal identity.
China’s move sets a precedent that other countries will have to meet when they decide how far AI should be given a legal status that resembles a human one.




























