Researcher, educator, entrepreneur, and administrator in computer science, artificial intelligence, and healthcare.

San Francisco, CA
How big is this model? At @ICML in July we previewed K2-Horizon-3.7B and 7B and asked attendees to guess their size from watching them conduct real-work and coding tasks. Average answers, 89.9B and 62.6B. Both off by an order of magnitude. Density of intelligence matters more than parameter count now. The need for capable models at smaller sizes, lower cost and higher speed was overlooked. K2 Horizon is built around it. Try them: huggingface.co/IFM/K2-Horizo…; huggingface.co/IFM/K2-Horizo…
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Michigan builders: K2 Horizon is coming to the University of Michigan this Saturday. ⛰️ Build with IFM’s open 375B-A23B flagship in the “Best Use of K2 Horizon” challenge. 🏆 100M tokens for every winning team member 📅 Sept. 19 | 9 AM–9 PM 📍 East Hall 1324 #K2Horizon #OpenSource
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Glad to be quoted here (thank you @CNN and @TM_Brown!) of my standing on AI dystopia -- an idea, a software (which AI is), a blueprint on a file (which AI generates), is NOT a physical actuation. Closing this gap takes a long way and can/should be guardrailed. I'd quote (approximately) words of wisdom I remembered from X: "regulate the world of atoms, not algorithms; penalize the effects from misalignment, not misalignment; and monitor supply-chains/factories/infrastructures in real world, not blueprints on files"
A lot of people are saying AI is going to kill everyone. But how exactly? For @CNN I talked to some influential doomers about how the world will end—and some leading experts in existential risk about why they think that prospect is pure science fiction. cnn.com/2026/09/17/tech/how-… feat. @HeidyKhlaaf @So8res @HerbLinCyber @ericxing @thlarsen
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Eric Xing retweeted
Out today in @cellpressnews: "A world model of the virtual cell," from our co-founders @ericxing and @dasongle. Their definition of a virtual cell is a stateful, multi-modal, multi-scale simulator, judged on whether it stays coherent across a sequence of interventions. Open access: cell.com/cell/fulltext/S0092…
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We discussed fundamental issues in the definition, model architecture, computational algorithm, and meaningful evaluation/qualification of a fully steerable virtual cell that is multi-modal, multi-scale, dynamic, and stateful. @dasongle , @genbioai , @mbzuai , @CarnegieMellon cell.com/cell/fulltext/S0092…
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Glad to be quoted here of my standing on AI dystopia -- an idea, a software (which AI is), a blueprint on a file (which AI generates), is NOT a physical actuation. Closing this gap takes a long way and can/should be guardrailed. I'd quote (approximately) words of wisdom I remembered from X: "regulate the world of atoms, not algorithms; penalize the effects from misalignment, not misalignment; and monitor supply-chains/factories/infrastructures in real world, not blueprints on files" edition.cnn.com/2026/09/17/t…
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second @gneubig! Cold outreachers, you can only expect to be reciprocated by the effort/seriousness you put in your outreach.
Two pieces of advice for students doing cold outreach: 1. Read the professor's page and follow directions about their preferred outreach method. 90% of students who email me do not follow the directions on my page. 2. Hand-write your messages from your heart. We can tell.
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Diffusion can multiply LLM, not just add to it to work in parallel, the outcome is a lossless acceleration of any existing LLMs. Try it out!
Today’s LLMs still write like typewriters: one token at a time. This sequential process creates a hard inference bottleneck. We're introducing Uno, a diffusion-augmented LLM that delivers autoregressive quality at diffusion speed. It’s a lossless speedup method that accelerates generation without degrading response quality. With Uno, K2-Horizon-7B outperforms state-of-the-art diffusion methods in both quality and throughput, delivering up to a 2.2× speedup with no loss in quality. Paper: arxiv.org/abs/2609.04010 Model available at: huggingface.co/IFM/K2-Horizo…
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K2-Horizon-7B scores 21 on Artificial Analysis Intelligence Index, punching above its weights. It scores 50% above the next best model under 10B, beating Qwen3.6-35B-A3B and closely matching Qwen3.6-27B. • Try it: huggingface.co/IFM/K2-Horizo… • 8-bit quantization: huggingface.co/IFM/K2-Horizo… • Uno, the speed-up diffusion-augmented version: huggingface.co/IFM/K2-Horizo…
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Glad to share my perspective on the recent AI-pacing and humanity risk narratives on @CNBC. AI, however powerful, is a piece of software residing inside a chip; to do harm in physical world and on nature, in addition to be intelligent enough to know how (e.g., to design a potent enough virus that is biologically viable not just in theory), it needs to further command supply chain, facilities, people, and additional experimentation to overcome the idea-to-physical gap, which can be and already are subject to intensive guardrail. I am less worried an immediate or even a remote risk from that direction just because of all the missing scientific and engineering links are hard to bypass; I am more worried what the AI frontier labs are making and talking about are not subject to academic investigation, 3rd party audit, and objective and quantitative forensic analysis because of their close-source or mere “open”-weight nature, which is not helpful for trust, safety, and transparency. At @IFM_AI we open source the full house (data, weight, code, checkpoints…) of our models in our recent K2-horizon release. I say NO to slow down AI, I say YES to a more open, faster stronger, and more cost effective AI, which means even faster research and development, because there are too many important problems for AI to solve, such as cure cancer.
Replying to @ericxing
@ericxing, Founder of the Institute of Foundation Models, and @ReflexivityAi Co-Founder and CEO Jan Szilagyi discuss AI development, safety, open source models and Wall Street adoption. $NVDA $MSFT $GOOGL $META $AMZN. cnbc.com/video/2026/09/16/ai…
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Powerful voice from the sanity! We should speak about science with evidence, grounding, and statistics, rather than emotion and fiction. Thank you!
I completely agree with this take related to the “AI will create viruses that will kill us all” BS. But let me add my few cents, because I am really really angry! I worked with one of the deadliest viruses in history, HIV, for two decades. I was one of the early scientists to engineer it, and engineered versions of HIV are now helping cancer patients. I understand the immune system that defends us against viruses extremely deeply. I have worked in high security biohazard labs. I don’t have a PhD in AI, but I have been involved with AI since the early 90s and have been all in on AI for years. People claiming that you can just make a virus in your garage, use AI to engineer it, and somehow build a virus that will kill everyone don’t know what the hell they are talking about! Of course bioweapons are extremely dangerous. In fact, viruses and bacteria have killed more humans throughout history than almost anything else. HIV alone killed tens of millions of people, yet today, if you have access to effective medicines and take them properly, HIV is generally no longer a death sentence. COVID-19 killed millions. Why doesn’t it kill at anything close to the same scale anymore? Not because the virus disappeared. It is still here. We developed collective defenses against it through our immune systems, prior exposure, vaccines, treatments, and better medical care. And this is exactly the point. The best way to fight biological threats, whether natural or synthetic, is to use AI to develop vaccines, treatments, antibodies, antivirals, and eventually engineer our immune system to create much stronger defenses against them. By the way, it is already possible to make synthetic viruses. You don’t need some hypothetical superintelligent AI model to do that. We have had sophisticated molecular biology and genetic engineering for decades. So how many people have actually died from synthetic viruses compared with natural viruses killing millions every year? And if someday there really is an AI capable of making some unbelievable “supervirus,” then why the hell wouldn’t that same AI make it even easier to develop defenses against it? Or cure diseases, for that matter? Where is this damn superintelligence that has cured a single major disease?! These AI companies and AI doomers keep talking like, “OMG, AI is going to become so unbelievably powerful that it could kill all of humanity!” Then why is nobody asking the obvious question? If your AI is already becoming this godlike, unbelievably powerful intelligence, why hasn’t it cured anything? I mean ANYTHING. Where is the cure for cancer? Where is the cure for Alzheimer’s? Where is the cure for aging? Forget those. Where is the vaccine that prevents the common cold? You are telling me this intelligence will soon be smart enough to engineer some magical virus capable of wiping out 8 billion people, defeating every immune system, every vaccine, every antiviral, every laboratory, every government, and the entire global biomedical community… …but somehow it still can’t cure one disease? I call that greatest intellectual dishonesty ever! At least WE actually know how to cure things and save millions of lives with our supposedly stupid human intelligence compared with this future “superintelligence.” Humans eradicated smallpox, which killed hundreds of millions of people throughout history. We turned HIV from a almost certain death sentence into a manageable disease. We developed vaccines in record time against COVID. If we had the same AI back then, would have saved millions more! We engineer immune cells to kill cancer. We developed antibiotics, antivirals, monoclonal antibodies, gene therapies, organ transplantation, and thousands of medicines. We aren't fast enough but we did all of that with our ordinary human intelligence. So imagine what actual superintelligence could do for medicine! And here is the part that really makes me angry. If you actually have, or are close to having, an AI capable of curing diseases and saving millions of lives, and you are deliberately slowing it down or refusing to make those capabilities available, then we also need to talk about the human cost of THAT decision, which you fearmongering people are going to be responsible for! More than 150,000 people die every single day around the world. Every. Single. Day. More than 90% from Cancer, heart disease, infections, aging. How many die because of AI? ZERO! Talk about the people dying TODAY. Talk about curing cancer. Talk about stopping the next pandemic before it starts. Talk about developing universal vaccines. Talk about engineering our immune system so viruses become almost irrelevant. Talk about curing genetic diseases. Talk about reversing aging. Talk about saving millions and eventually billions of lives. Instead, we constantly hear this “AI WILL KILL US ALL!” crap, delivered with absolute certainty and with this smug smile on your faces in front of cameras, as though imagining a science fiction extinction scenarios. I am actually angry about this. Each one of you causing a delay in AI advance every single day will be personally responsible for those 100 thousands deaths that could have been prevented! Because if you truly believe intelligence is about to become this powerful, then the greatest question humanity should be asking is NOT: “How could this intelligence hurt us?” It should also be: “WHY THE HELL AREN’T WE USING IT TO SAVE EVERYONE WE CAN?” And if superintelligence really is coming, then make sure one of the first things we do with it is make humanity biologically damn near impossible to kill.
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Well, I’d add one more with myself, as one with a PhD in biology and another PhD in AI and now working in both, to make n=2. Generating a hypothetical genome blueprint of a virus from LLM versus generating a true virus are completely different things. It is either an intentional attention-harnessing lie or true ignorance. The material, the manufacturing, and actual biological viability of paper-to-physical transformation is the gap you need to close. Like drawing a design of a chip or A-bomb, versus actually make one. You have, and can add more checkpoints and guardrails all over this long chain of paper to physical transformation. Fear mongering is not well founded, and mostly emotional manipulation.
I must be among an extremely small group of people (n=1?) that have both 1) trained a frontier LLM and 2) designed and synthesized custom viruses in a lab with my own two hands. And I think that the takes on AI killing us all by creating dangerous viruses is total bogus.
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Eric Xing retweeted
Dario has written that we need to “pace the frontier,” and Sam has agreed. People may be surprised by my response: go ahead. You guys are the frontier. By any reasonable metric — market share, revenue growth, model capability — the two of you have a duopoly on frontier intelligence. You’ve also claimed the lead is widening because of recursive self-improvement. I don’t see what you see in the lab. If the unreleased models are scary enough that you think you should slow down, I support your decision to be responsible. But stop pretending you need anyone else’s permission. Stop pretending antitrust law has to be suspended so you can form a cartel. Stop pretending you need a regulatory approval process that supersedes product liability. Stop pretending METR is independent when it is intertwined with Anthropic’s investors and staff. Stop pretending you need those same evaluators to police competitors who aren’t even at the frontier. Most of all, stop pretending the motivation to slow down is purely altruistic. You face massive product-liability exposure if your products enable a truly damaging cyberattack. The market already punishes models that behave in unpredictable or unauthorized ways. After the Hugging Face episode, it is simply good business for OpenAI and Anthropic to trade some raw power for reliability and predictability. Call it alignment if you want. It is also just giving customers what they want. Pacing the frontier would also create breathing room for a more intelligent conversation about regulation than Bernie Sanders’ “shut it all down.” China is very unlikely to join a global agreement, as you know, and that has to be taken into account as well. So go ahead and pace the frontier. You are the ones setting it. The easiest way not to build superintelligence is for you to agree not to build it. Demanding your preferred regulatory framework as the price of that will look like blackmail of the public and the political system. So just do it. If you do, you’ll buy goodwill for the next conversation. If you don’t, we’ll know this was just another bid for regulatory capture — or an election-season psyop.
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People on TV or social media trying to tell others that AI is/does/will be this and that should watch this video where Feynman (declined to) explain why two magnets repel each other. Be honest and respectful to the complexity of science, and context of different people. Don’t appear as an expert when you are not. And to the general public, you don’t have to listen to or believe such persons when you hear them trying to lecture you.
In 1983, a BBC interviewer asked Richard Feynman why two magnets push each other apart and he refused to answer it. What he did instead is the best seven minutes on thinking ever filmed. Bookmark & watch today, no matter what.
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