Krithik Ramesh ✈️ NeurIPS
@KrithikTweets
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AI + Math @MIT, compbio stuff @broadinstitute, prev: research @togethercompute
Joined February 2017
🧬 Meet Lyra, a new paradigm for accessible, powerful modeling of biological sequences. Lyra is a lightweight SSM achieving SOTA performance across DNA, RNA, and protein tasks—yet up to 120,000x smaller than foundation models (ESM, Evo). Bonus: you can train it on your Mac. read
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Incredibly deserving and one of the hardest working, diligent people I know!
Nice surprise this AM @ForbesUnder30! Grateful to be recognized for my work in clinical AI and genomics, and always happy to chat about either! Thankful for family, friends, and mentors, both scientific (@PardisSabeti and @snbhatia), clinical (@MarcSucciMD), and more :)
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I’ll be around at NeurIPS from the second to the 4th! Super excited to chat with people interested in efficient architectures, Bio ML, and ML systems! DMs are open, and always a pleasure to meet new people :)
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AI has been built on one vendor’s stack for too long. AMD’s GPUs now offer state-of-the-art peak compute and memory bandwidth — but the lack of mature software / the “CUDA moat” keeps that power locked away. Time to break it and ride into our multi-silicon future. 🌊 It's been a
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Very honored to have been selected as an #AI2050 Fellow. Many thanks to @schmidtsciences for supporting our work on Geometric Machine Learning and applications in the Sciences.
We're excited to welcome 28 new AI2050 Fellows! This 4th cohort of researchers are pursuing projects that include building AI scientists, designing trustworthy models, and improving biological and medical research, among other areas. https://t.co/8oY7xdhxvF
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Thank you @schmidtsciences for the 2025 #AI2050 Early Career Fellowship supporting my work on self-improving AI systems: as AI gets better, it should help human experts design better model architectures and faster training & inference systems
We're excited to welcome 28 new AI2050 Fellows! This 4th cohort of researchers are pursuing projects that include building AI scientists, designing trustworthy models, and improving biological and medical research, among other areas. https://t.co/8oY7xdhxvF
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Connectome suggests brain’s synaptic weights follow heavy-tailed distributions, yet most analyses of RNNs assume Gaussian connectivity. 🧵⬇️ Our @AllenInstitute #NeurIPS2025 paper shows heavy-tailed weights can strongly affect dynamics, trade off robustness + attractor
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Together, we can all work to build a kinder, more wholesome, more positive chess world - the world that Danya wanted. https://t.co/7RnVzCd47d
chess.com
Daniel Naroditsky was an incredible prodigy, coach, player, friend, author, and team member. He was the kindest and most wholesome voice in the chess world.
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S4 is almost single handedly what inspired the research I do today. Sashimi was incredibly refreshing paper and to see that vision industrialized at this level is inspiring. @krandiash, @_albertgu, and team have done an exceptional job!
We've raised $100M from Kleiner Perkins, Index Ventures, Lightspeed, and NVIDIA. Today we're introducing Sonic-3 - the state-of-the-art model for realtime conversation. What makes Sonic-3 great: - Breakthrough naturalness - laughter and full emotional range - Lightning fast -
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immensely proud of the team for our best model yet. grateful to be able to work with such a strong team of researchers who are always curious and willing to explore the untrodden path https://t.co/Grkgy4vaqf
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Valthos is doing incredible work in biodefense. I got a sneak peak of some of their work and it’s principled and promising!
Valthos builds next-generation biodefense. Of all AI applications, biotechnology has the highest upside and most catastrophic downside. Heroes at the frontlines of biodefense are working every day to protect the world against the worst case. But the pace of biotech is against
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I really like this research direction! For a long time, I've been talking about the "brain vs. database" analogy of SSMs vs Transformers. An extension of this that I've mentioned offhand a few times is that I think that the tradeoffs change when we start thinking about building
SSMs promised efficient language modeling for long context, but so far seem to underperform compared to Transformers in many settings. Our new work suggests that this is not a problem with SSMs, but with how we are currently using them. Arxiv: https://t.co/bCzxawF452 🧵
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Could not be prouder, absolutely exceptional work by these two :) Their product just works, and if you have messy, unstructured documents, try reducto!
Big milestone for Reducto: we’ve raised a $75M Series B led by a16z, bringing our total funding to $108M. Since our launch, we’ve been obsessed with pushing the limits of what’s possible when AI meets the real-world messiness of documents. We’ve now processed 1B+ pages, nearly
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I remember when Nathan told me about this project. Above all else, it was evident he had immense, genuine passion for robotics. Could not be more proud of what he’s accomplished :)
In March, my cofounder and I raised $1M from @southparkcommons without an idea. Next thing, I left Stanford for SF to work on giving operators’ telepresence in humanoid robots. I’m stepping away due to internal disagreements, but I wanted to share what I worked on so it doesn’t
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Caltech is so lucky to have her!
Very excited to share that I've finished my phd @stanford and will be joining @caltech’s cms department as an assistant professor. Looking forward to working with students and colleagues on ml systems! Grateful to my amazing advisor and labmates @hazyresearch for the best time
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How bad can my code be dawg that it can’t fix it 😭😭
1/n I’m really excited to share that our @OpenAI reasoning system got a perfect score of 12/12 during the 2025 ICPC World Finals, the premier collegiate programming competition where top university teams from around the world solve complex algorithmic problems. This would have
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The most important skill for a researcher is not technical ability. It's taste. The ability to identify interesting and tractable problems, and recognize important ideas when they show up. This can't be taught directly. It's cultivated through curiosity and broad reading.
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Nothing makes you want to frisbee your computer like a quantized claude response.
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compute feels less expensive when you start thinking about it in terms of caniac combos. a node of h100s for an hr ≈ 1 caniac combo
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you don’t really appreciate SLURM until you have to run torch run by hand on all your nodes 💔
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