ML Engineer and AI enthusiast. Based out of 🇸🇪

Malmo, Sweden
Joined October 2024
Chamalka Muwangala retweeted
this mathematician won the 2026 Fields Medal, then stepped away from academia to join OpenAI’s safety team. what’s fascinating is how balanced his view is on AI. his story is WILD: >be Jacob Tsimerman >spend 13 years on a math problem >win the 2026 Fields Medal >an LLM finds a mistake in one of your proofs >you fix it, but the LLM couldn't >“I think my part is going to be very small” >realize where things are going >imagine AI solving decade-long math problems in weeks or even days >say mathematics will advance too fast for humans to keep up >AI will generate conjectures, prove theorems, and invent new definitions on its own >people argue humans will still be needed to develop new mathematical theories >“Why won't AIs be able to do this as well?” >point out that even your own theorems rely on accepted proofs you DON’T fully understand >say mathematics already relies on black boxes, and this will become much more common >“I'm definitely grieving” >stop taking traditional math PhD students >can't confidently recommend a career when you don't know what the field will look like in two years >say AI will become superhuman at doing mathematics >but worry about humans losing control >say society needs a Manhattan Project for AI safety >decide the most important problem isn't proving more theorems anymore >temporarily leave academia >join OpenAI's AI safety team he won the highest prize in math and is now making sure AI is on a leash.
Jacob Tsimerman, who won the Fields Medal this year, thinks mathematics will soon rest on proofs no one understands. He says it’s already true of many of his own theorems, which build on accepted results whose proofs he doesn’t know. Full episode: youtu.be/6uIJdXmB4vE
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Chamalka Muwangala retweeted
i visualized the top 500 unsolved math problems by who solved them. no bingo yet! how many can humans solve before AI takes over?
A quick check shows that this list claims to fully solve 90 of the top 500 open problems in math (proofatlas.ai/open-problems/). The highest ranked would be:
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Chamalka Muwangala retweeted
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
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Chamalka Muwangala retweeted
Small bird, fast wings, Kolibri is here. 78B parameters. 3.46B active. Up to 1M tokens of context. Built in Europe. Now the weights are yours. Run it on your own hardware, under Apache 2.0.
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Time for a new eval @skalskip92
Today we’re introducing Gemini 4 Argon. It delivers frontier performance in complex workflows across real-world software engineering, knowledge work, and cybersecurity defense with an industry-leading 1M token output limit.
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Chamalka Muwangala retweeted
Today we’re introducing Gemini 4 Argon. It delivers frontier performance in complex workflows across real-world software engineering, knowledge work, and cybersecurity defense with an industry-leading 1M token output limit.
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Chamalka Muwangala retweeted
Gemini 4 Argon is our next era of frontier intelligence. It shows significant improvements across benchmarks, setting a new state of the art for real-world long-horizon software engineering tasks.
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Chamalka Muwangala retweeted
i want someone to do an ablation of reasoning in every language... surely there's a language out there that is objectively the most token-efficient to reason in, and i'm willing to bet it's not english/mandarin
Reasoning models think in English, even on German prompts. We asked what it costs to make one think in German. Answer: a valley. Small doses of German reasoning data hurt, large doses mostly recover.
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Chamalka Muwangala retweeted
What can Astra do when given a humanoid embodiment? We built HomeBody to find out. Controlled by GPT Astra, it carries out long-horizon tasks in a previously unseen kitchen—from tidying up across the room to retrieving remembered objects from ambiguous requests—without environment-specific training data or additional policy learning. Here's how we did it 👀: tml.stanford.edu/homebody/
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We need silicon biologists more than ever
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Chamalka Muwangala retweeted
Life tips > stay in perpetual motion > never lie > don’t worry > you can do anything > travel as much as you can > prioritize relationships > money is there to be spent > look at good art > listen to positive music > don’t watch content > don’t watch porn > it’s never personal
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Chamalka Muwangala retweeted
Replying to @OpenRouter
Jev by @typesafeai is now on OpenRouter, in beta. Jev is a System One model. Instead of generating text, it takes your app's state plus a typed question and returns a typed decision with a probability attached. There is no JSON prompting, parsing layer, and nothing to validate against.
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Chamalka Muwangala retweeted
After co-inventing ChatGPT, I kept asking myself: why have superhuman chat models not led to AGI? I’ve spent the last 2 years in stealth building a new way to train models (RLCD), and a new type of frontier AI model that we are releasing today: Jev • 20-200x faster • 40-400x cheaper (w/ output tokens free) • Frontier composable intelligence optimized for decisions AFAICT the shortest path to AI-based economic revolution
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Chamalka Muwangala retweeted
new independent AI strategy for EU suggests: - 15% of global AI compute by 2030 - 25x EU capacity under its scenario - €1.3tn in mostly private investment - faster permits and grid connections - compute sites traded for model access - chipmaking equipment as bargaining power - EU models as a fallback (interesting) - better funding for startups (yes please) - defences against AI driven crises - an optional €800b frontier AI project quite ambitious, maybe enough to make Europe indispensable enough to secure its AI future but again, this is just a proposal, power, capital and execution still have to follow
nice initiative, it's all about compute. i wish it was a bit more about financing model building but that's understandable for comparison mistral's target for compute in 2023 is 1GW while this initiative targets 45GW
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Optimism always triumphs
After AlphaGo, the skill of human Go players noticeably improved. I suspect we will see a similar pattern in math.
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Chamalka Muwangala retweeted
After AlphaGo, the skill of human Go players noticeably improved. I suspect we will see a similar pattern in math.
Another major problem, this time in additive combinatorics, has fallen, this time to humans rather than AI, but using methods related to the AI solution to the unit distance conjecture.
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Chamalka Muwangala retweeted
Can’t make this up…the MacBook is using its webcam to look at its screen in a mirror to improve AMD Radeon chip support in Omarchy.
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Chamalka Muwangala retweeted
Proving P ≠ NP might be difficult for AI. But if P = NP, proving *that* would be exactly the thing AI is good at. Just send a gazillion agents out looking for polynomial solutions to NP complete problems. I hope this tweet doesn't destroy all cryptography as we know it.
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Chamalka Muwangala retweeted
Last week we published a factorization of RSA-260. Today, we’re sharing the methodology of how Devin and a Cognition researcher built the world’s fastest GPU optimized lattice siever, to make factoring numbers 10x cheaper than the previous state of the art: cognition.com/blog/factoring…
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Chamalka Muwangala retweeted
It is clear that as of today we are no longer the smartest things on the planet.
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