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Igor Babuschkin
@ibab
CEO & Co-Founder @river_ai_inc. Previously @xAI, Research & Engineering
893 Following    111.2K Followers
Congrats to @Cisco_Invests on joining the River AI funding round!
We're thrilled to announce that @Cisco_Invests is joining River AI's $1.1B round as a strategic investor. Personal, user-owned AI needs the best of product and infrastructure behind it. @jpatel41 understands both deeply and we're excited to work with him and the @Cisco team.
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The River API was tested in this blog post and outperformed Tinker on reinforcement learning runs with identical training code. We spent a lot of effort to get details like routing replay right so you get the best possible results with the API.
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We can now RL large MoEs with 0 train-infer mismatch! And doing so can improve performance (pictured task: teach Qwen3.6-35B-A3B to play Wordle). Everything is open-source and we did a bunch of ablations. 🧵
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I sat down with Hemant in his garden to discuss River AI's vision and our bets for how to democratize control of the AI systems we use every day.
We've raised $1.1B to build AI that is owned and shaped by each of us. Check out the article published by the The New York Times that explains River AI's mission and where we're going next. Our first product is the River API which allows anyone to build custom agents and LLMs based on open weight models: Congrats to the team and thank you to all of our supporters. Stay tuned for more updates soon.
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What are the major blockers to build powerful personal AI today and how can we solve them? I gave a talk about River AI's research roadmap at UC Berkeley.
How do we create amazing personal AI? Here's a recent talk from River CEO Igor Babuschkin (@ibab) sharing our vision for personal AI and continual learning.
I went on the Unsupervised Learning podcast to talk about my experience working at the frontier of AI for the last 10 years and the future of AI, which I believe will become more and more open. Thank you Jacob for the great conversation!
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"As a proprietary model builder, you're kind of starting to get squeezed in.” That's @ibab’s take on where the biggest AI labs stand today. He explains how you need the models to get way better to keep margin, but at some level they may be too sensitive to release. This week, I sat down with Igor on Unsupervised Learning. It was a fascinating conversation with someone who has real perspective on the questions everyone in AI is asking right now. From DeepMind's StarCraft project to early reasoning work at OpenAI to co-founding xAI, Igor has had a front-row seat to nearly every major AI breakthrough. He's now the co-founder of River AI, building individualized, locally-run AI models. We discuss: ▪️Why proprietary model labs might be in trouble ▪️What it's like working with Elon ▪️Building Colossus in 120 days ▪️Should enterprises train their own models ▪️What’s left for humans as models get better ▪️Why he left xAI to bet on personal local AI instead ▪️The three bets River is taking ▪️What's stopping AI from moving beyond coding ▪️Reflections on the rapid pace of the past years 0:00 Intro 1:17 Writing Fiction on Where AI Is Headed 4:46 Cracking Agents Beyond Coding 10:29 Why Igor Left to Start River 12:22 River's Three Big Bets 18:06 Weights vs. Memory: The Personalization Debate 22:04 Should Enterprises Train Their Own Models? 25:10 Are Proprietary Labs Losing Their Edge? 32:16 The China Open-Source Problem 44:19 The Elon Call That Started xAI 50:18 Thoughts on Cursor Acquisition 52:16 What's Actually Bottlenecking AI 56:55 Humans, Machines, and Staying Relevant 1:01:29 Igor's Odds This All Goes Well YouTube: Spotify: Apple:
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We've opened up the River API to everyone. Check it out!
River API is now available to everyone. Fine-tune and run RL on frontier open models. Fast, cheap, and scalable. Go to to try it out!
We need to build a future where the benefits of AI are broadly distributed among all of humanity and open models are the best tool we have to get there. I’m immensely grateful that Jensen is speaking out in support of open models.
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For my first post, I’m sharing a letter @NVIDIA signed on why open models matter. AI will transform every industry, power every company, and be built by every country. Open models strengthen safety and cybersecurity, accelerate innovation and diffusion, and enable sovereignty. The world needs both frontier closed models and frontier open models.
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At humans&, we train models from the long-term impacts of their interactions with people. This requires prioritizing long-horizon multi-agent RL. We've developed and are excited to share an open-source, hardware-native 4-bit RL recipe, significantly accelerating training
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Sign up for the River API if you want to try it out. We’re open ing up access incrementally.
We've received plenty of applications for the API waitlist and have opened up access to a number of enterprises and researchers already. We're improving the API based on your feedback, and we expect to open up to the public in the next few weeks.
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We are looking for exceptional people to join the team. If our mission resonates with you - please apply.
River AI is building personal AI owned & shaped by you. We are hiring exceptional talent across the stack: * Research * Software Engineering * Product Development * Data * Hardware, RTL Design Engineer * Hardware, Design Verification Engineer * Hardware, Physical Design Engineer * Hardware, Performance Engineer * Hardware, Compiler Engineer * Open Application, Exceptional Talent We are a small, elite team of researchers, builders, and pioneers from the world's leading AI labs. If you want to do the most ambitious work of your career alongside, apply today!
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Congrats to @elonmusk and $SPCX! “Any man who can hitch the length and breadth of the galaxy, rough it, slum it, struggle against terrible odds, win through, and still knows where his towel is is clearly a man to be reckoned with” - Douglas Adams
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We are releasing River API, our first product, in early access. The API gives you access to the same battle-tested tools that we’re using internally at River for post-training, reinforcement learning and continual learning. Check it out and let us know what you think!
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Introducing River API. Fine-tune and RL train leading open-source models at scale, ranging from 35B to 1T params. We’ve been using it internally to power our research and we love it. Today, we are opening up our public waitlist. Own your intelligence!
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We’re launching River AI, a new AI company with the mission to build AI systems that are owned and shaped by you. I’m extremely excited about what we’re going to ship soon. Check it out!
We are incredibly excited to announce River AI. Our mission is to create personal AI that is owned and shaped by you. Today’s best AIs are controlled by a few large corporations. We are building the alternative: a new, personal stack for AI that works entirely for you, shares your values, and operates on your terms.
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We raised $250M in Series C funding at a $2.2B valuation, led by a16z. Exa is a search lab organizing the web's data for agents.
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sglang is the best inference framework out there. RadixArk was formed to make it even better and to democratize more of the frontier AI stack. Very happy to support the team in their seed round.
Today, we are thrilled to officially launch RadixArk with $100M in Seed funding at a $400M valuation. The round was led by @Accel and co-led by @sparkcapital. RadixArk exists to make frontier AI infrastructure open and accessible to everyone. Today, the systems behind the most capable AI models are concentrated in a small number of companies. As a result, most AI teams are forced to rebuild training and inference stacks from scratch, duplicating the same infrastructure work instead of focusing on new models, products, and ideas. RadixArk was founded to change that. We are building an AI platform that makes it easier for teams to train and serve the best models at scale. RadixArk comes from the open-source community. We started with SGLang, where many of us are core developers and maintainers, and expanded our work to Miles for large-scale RL and post-training. We will continue contributing to both projects and working with the community to make them the strongest open-source infrastructure foundations for frontier AI. We would like to thank our long-term partners, contributors, and the broader SGLang community for believing in this mission. We're also grateful to @Accel and @sparkcapital, NVentures (Venture capital arm of @nvidia), Salience Capital, A&E Investment, @HOFCapital, @walden_catalyst, @AMD, LDVP, WTT Fubon Family, @MediaTek, Vocal Ventures, @Sky9Capital and our angel investors @ibab, @LipBuTan1, Hock Tan, @johnschulman2, @soumithchintala, @lilianweng, @oliveur, @Thom_Wolf, @LiamFedus, @robertnishihara, @ericzelikman, @OfficialLoganK, and @multiply_matrix among others. Thanks for the exclusive interview with @MeghanBobrowsky at @WSJ about our vision.
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DeepSeek V4 by @deepseek_ai just dropped! SGLang is ready on Day 0 with a full stack of optimizations from architectures to low-level kernels. We also deliver a verified RL training pipeline in Miles (by @radixark) for V4 at launch: 1️⃣ Native "ShadowRadix" Design: DeepSeek V4's hybrid attention is complex. Our new ShadowRadix engine is the first to provide native prefix caching for SWA and compressed KV pools, making 1M+ context retrieval seamless and memory-efficient. 2️⃣ High-Performance Kernels: - Flash Compressor: IO-aware fused kernels, 10x faster than naive implementations. - Lightning TopK: High-speed indexing for 1M context in just 15µs. - Integrate FlashInfer trtllm-gen MoE, FlashMLA, and MegaMoE kernels 3️⃣ Rich Features: Speculative decoding, HiSparse, Attention DP/TP/CP and MoE TP/EP, and multi-platform support 4️⃣ Verified RL: The open-source RL pipeline: full parallelism (DP/TP/EP/PP/CP), tilelang kernels, tensor-level checked precision, verified with growing reward. Get started immediately with our out-of-the-box Cookbook 👇 Enjoy! #DeepSeekV4# #SGLang# #LLM#
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Today was my last day at xAI, the company that I helped start with Elon Musk in 2023. I still remember the day I first met Elon, we talked for hours about AI and what the future might hold. We both felt that a new AI company with a different kind of mission was needed. Building AI that advances humanity has been my lifelong dream. My parents left the Russian Federation after the collapse of the USSR in search of a better life for their kids. Life wasn’t always easy as immigrants. Despite the hardships, my parents believed that human values were priceless: values like courage, compassion, curiosity for understanding the world. As a child, I admired scientists like Richard Feynman and Max Planck, who relentlessly pushed the frontiers of physics in order to understand the universe. As a particle physics PhD student at CERN I was excited to contribute to that mission. But the search for new physics was getting harder and harder, requiring bigger and bigger colliders, while new discoveries kept getting fewer. So I began to wonder if superintelligence, not larger colliders, could be the key to unlocking the mysteries of the universe. Could AI develop a consistent theory of quantum gravity? Could AI prove the Riemann hypothesis? In early 2023 I became convinced that we were getting close to a recipe for superintelligence. I saw the writing on the wall: very soon AI could reason beyond the level of humans. How could we ensure that this technology is used for good? Elon had warned of the dangers of powerful AI for years. Elon and I realized that we had a shared vision of AI used to benefit humanity, thus we recruited more like minded engineers and set off to build xAI. The early days of xAI were not easy. Naysayers told us that we arrived too late to the game, so starting a top AI company from scratch would be impossible. But we believed we could do the impossible. Starting a company from zero required lots of hands-on work. In the beginning I built many of the foundational tools used at the company to launch and manage training jobs. I later oversaw much of the engineering at the company, including Infrastructure, Product and Applied AI projects. xAI’s people are deeply dedicated. Through blood sweat and tears, our team’s blistering velocity built the Memphis supercluster, and shipped frontier models faster than any company in history. I learned 2 priceless lessons from Elon: #1# be fearless in rolling up your sleeves to personally dig into technical problems, #2# have a maniacal sense of urgency. xAI executes at ludicrous speed. Industry veterans told us that building the Memphis supercluster in 120 days would be impossible. But we believed we could do the impossible. Our goal was to get our training setup running at scale on the Memphis cluster ASAP. Towards the end of our 120 day deadline, we were riddled with mysterious issues with communicating over RDMA between the machines. Elon decided to fly to the datacenter, and we followed. Our infra team landed in Memphis in the middle of the night and got straight to work. After pouring through tens of thousands of lines of lspci output we finally identified a wrong BIOS setting, the root of the problem. Elon was there with us until late into the night. When the training run finally worked, Elon posted our triumph at “4:20am” causing us to laugh out loud. I will never forget the rush of adrenaline that night, and the emotional bonds that we were all in this together. We went to bed feeling like we were living through the most exhilarating time of our lives. I have enormous love for the whole family at xAI. Our team is truly special - you’re the most dedicated people I’ve ever worked with. Catching up to the frontier this quickly hasn’t been easy. It was made possible by everyone’s diehard grit and team spirit. Thank you to every single person who joined me on this adventure. I want to honor your contributions, your time, your sacrifices, which are never easy. I will always remember working together far into the nights and burning the midnight oil. I will never forget the sacrifices and contributions you’ve made. As I drive away today, I feel like a proud parent, driving away after sending their kid away to college. My heart is brimming with tears of joy, rooting for the company as it grows and matures. As I'm heading towards my next chapter, I’m inspired by how my parents immigrated to seek a better world for their children. Recently I had dinner with Max Tegmark, founder of the Future of Life Institute. He showed me a photo of his young sons, and asked me “how can we build AI safely to ensure that our children can flourish?” I was deeply moved by his question. Earlier in my career, I was a technical lead for DeepMind's Alphastar StarCraft agent, and I got to see how powerful reinforcement learning is when scaled up. As frontier models become more agentic over longer horizons and a wider range of tasks, they will take on more and more powerful capabilities, which will make it critical to study and advance AI safety. I want to continue on my mission to bring about AI that’s safe and beneficial to humanity. I’m announcing the launch of Babuschkin Ventures, which supports AI safety research and backs startups in AI and agentic systems that advance humanity and unlock the mysteries of our universe. Please reach out at ventures@babuschk.in if you want to chat. The singularity is near, but humanity’s future is bright!
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