@Recursive_SI @RichardSocher @jeffclune @tydsh @CaimingXiong @timshi_ai Huge congrats to the team! Can not wait to try the model with capabilities of 50K PhDs.
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Li Erran Li
69 posts
Li Erran Li
@erranlli
Dr. Li Erran Li is the head of Science for human-in-the-loop services at AWS AI, Amazon and an adjunct professor at Columbia University.
Palo Alto, CA Katılım Nisan 2009
849 Takip Edilen52 Takipçiler
@maxjaderberg @maxjaderberg @m_schaarschmidt Huge congrats!! Can not wait to see what diseases will be conquered soon.
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Huge news today at Isomorphic Labs!
We have secured $2.1 Billion investment to advance the most important mission that AI can unlock: to change the way we can improve human health and create new medicines for patients around the world.
This funding milestone was built on the strength of our AI drug design engine (IsoDDE), which has already proven its worth (aside from smashing benchmarks) by designing breakthrough new molecules and creating new scientific breakthroughs across our drug discovery programs.
Our IsoDDE is giving us a repeatable way to design new medicines for a wide range of diseases, building a future of medicine that we couldn’t unlock until now.
A massive thank you to our incredible team across London, Boston and Lausanne, whose relentless work made this possible, and to our partners who share our ultimate vision.
Now we have so much more to build together!
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@radixark @robertnishihara @Accel @sparkcapital @ying11231 congrats Ying and team! Can not wait to see what you will build next.
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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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@ZhitingHu @rsalakhu @andrewgwils @ericxing @mldcmu @HDSIUCSD @mbzuai @aistats_conf @ZhitingHu @rsalakhu @ericxing congratulations!!
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🏆Honored to receive the Test of Time Award Honorable Mention #AISTATS2026 for our 2016 work Deep Kernel Learning, with the amazing @andrewgwils @rsalakhu @ericxing
What a decade of AI progress! While GenAI is now driving massive real-world applications, the deepest underlying challenge remains: learning efficient representations of the world—for understanding, generation, predicting future worlds, and reasoning in the latent space.
So much fun to think about for the next decade!⏳
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I’ve been reflecting a lot on this journey, and I feel incredibly grateful.
To the Eigen AI team: thank you for choosing to build something hard together, and for bringing so much ambition, intensity, and care every day. I’m truly proud of what we have built, and even more grateful that we get to continue this next chapter together.
To our customers and developers: thank you for trusting us early, bringing us meaningful problems to solve, and shaping Eigen through your feedback, partnership, and belief in what we were building.
To our advisors, investors, and supporters: thank you for believing in us early, guiding us along the way, challenging us to think bigger, and standing with us through every stage of the journey.
And to the Nebius team: thank you for the conviction, trust, and partnership throughout this process. We’re excited to join forces, keep building with the same ambition, and take this next chapter even further.
This milestone would not have been possible without all of you. I’m deeply thankful, proud of what we have built together, and excited for what comes next! ❤️
Eigen AI@Eigen_AI_Labs
Today, we're announcing that Eigen AI is joining Nebius (NASDAQ: NBIS). From day one, our mission has been Artificial Efficient Intelligence — building the world's most efficient engines for generating intelligence. Together with Nebius, we're working toward the best AI cloud, uniting Eigen's full-stack model and inference software, ranked #1 on Artificial Analysis for inference speed, with Nebius's global hardware and infrastructure footprint, so any developer or enterprise can run the best models at the best price, with no capacity ceiling. After close, Eigen's optimization stack will be integrated directly into Nebius Token Factory. The entire Eigen AI team is joining Nebius in full, establishing Nebius's engineering and research presence in the San Francisco Bay Area. To our customers, our team, our investors at Tectonic Ventures, E14 Fund, Uncorrelated Ventures, and AGI House Ventures, our angel investors, advisors, mentors, and supporters — and to the Nebius team for the conviction and partnership — thank you. The mission doesn't change. The leverage behind it does. Ryan Hanrui Wang, co-founder and CEO of Eigen AI, said: “We’re proud to join Nebius and work alongside the Token Factory team to push the boundaries of inference performance. Nebius has built a world-class AI cloud with a deep engineering culture that perfectly aligns with our own. Together, we are removing the friction of AI model customization and deployment so developers can run models reliably in production without managing the underlying infrastructure.” Full announcement at: eigenai.com/blog/eigen-ai-…
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@michellearning @michellearning Exactly what we discussed at your UNLOCK. Building bespoke automated lab instruments just duplicates hardware. Generalist arms & legacy instruments = infinite flexibility without the CapEx nightmare.
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“Why are you using general purpose robot arms to automate human-useable instruments? Shouldn’t we just invest in more automated instruments?”
Same argument my dudes
Palmer Luckey@PalmerLuckey
@SarkaryShahvir Because the humanoid robot can amortize cost of batteries+actuators+sensors+compute across dozens of appliances and use cases rather than duplicating it for each one. It is the same reason humanoids will be a big deal as an autonomous interface to legacy weapons platforms.
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Symbols, space, and time can represent most of the "information". In this eval paper, we show how video models are generalist "space-time reasoners". It's like "let's think step by step" in LLMs in 2022. Veo3 is like GPT-3 in 2020, and can't wait for its thinking/RL moment.
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@michellearning @michellearning Great event! Amazing selection of speakers.
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The next industrial revolution isn’t software. It’s science.
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Honored to receive the 2026 Apple Scholars in AIML PhD fellowship! 🍎
Extremely grateful to my advisor @orussakovsky and all the incredible mentors, collaborators and friends I’ve had throughout the journey. Excited to push toward more scalable and capable multimodal system!
machinelearning.apple.com/updates/apple-…
Princeton Computer Science@PrincetonCS
Congrats to to @cindy_x_wu on receiving an @Apple Scholars in AIML fellowship! 🍎 🎉 The fellowship recognizes doctoral students doing innovative research in machine learning and artificial intelligence. bit.ly/3OV0fyP
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@rsalakhu @subail @chuckjhoover @asenkut @FHaskaraman Amazing mission. Huge congratulations Russ and team!!
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Foresight will be the defining frontier on the path to AGI.
I am excited to start Sooth Labs with my amazing co-founders: Yaser Sheikh @subail, Chuck Hoover @chuckjhoover, David LaRose, and Shih-En Wei.
Deeply grateful to Aydin Senkut @asenkut and Feyza Haskaraman @FHaskaraman at @felicis for leading the round, alongside an exceptional group of partners.
bloomberg.com/news/articles/…
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@jure Congrats @jure, @KexinHuang5 @YuanhaoQ and team on Biomni-AD! Using Biomni for antibody design. Ran a TREM2 multi-specific case, had a Stanford bio-eng PhD confirm the design makes sense. This is the bar: giving scientists something to build on, not just summarize.
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Thrilled that Biomni-AD won the $1M Alzheimer's Insights AI Prize at the AD/PD Conference in Copenhagen 🏆
Most AI tools answer a single question. Biomni-AD is a co-scientist agent. It explores hypotheses, integrates evidence across genetics, proteomics, neuroimaging & clinical data, and explains its reasoning so scientists can interrogate and build on it.
Alzheimer's will affect 152M people by 2050. No single researcher can synthesize all that data at once. That's exactly where AI agents change the equation.
Proud of the whole team. And it'll be freely available to researchers worldwide 🙏
stanforddaily.com/2026/04/15/bio…
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@joyjiao12 @yunyunash @kevinrao99 @edwardzhou_ @Davediego Great work! Does it understand novel protein structure? How do I input the protein structure to the model?
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it's been a crazy journey to train this model with my co-lead @yunyunash and the life sci team at oai @kevinrao99 @edwardzhou_ @davediego! beyond excited for even more capabilities to come, and to see GPT-Rosalind accelerate life sciences research!
OpenAI@OpenAI
Introducing GPT-Rosalind, our frontier reasoning model built to support research across biology, drug discovery, and translational medicine.
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@volokuleshov What a journey!! Still remember @StefanoErmon told me his dLLM reached GPT2 capability, but uses more compute back in 2024.
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It was great talking with Tim Tully from Menlo Ventures about the story of diffusion models and where they provide big gains over autoregressive models: speed, code, agents, and beyond!
Inception@_inception_ai
1,000+ tokens per second. 10x faster than autoregressive models. On standard GPUs. @StefanoErmon and @volokuleshov break down where that speed matters most: voice agents, coding, and production agent systems where latency compounds across every call. Our founder series with @timt at @MenloVentures.
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Excited that this is out, and proud to be a part of it! This is our first step in scaling — an intelligent and useful multimodal model 🥑 built on a foundation of scientific rigor and solid engineering.
Incredible velocity and culture of the team and the best is yet to come!
AI at Meta@AIatMeta
Introducing Muse Spark, the first in the Muse family of models developed by Meta Superintelligence Labs. Muse Spark is a natively multimodal reasoning model with support for tool-use, visual chain of thought, and multi-agent orchestration. Muse Spark is available today at meta.ai and the Meta AI app. We’re also making it available in private preview via API to select partners, and we hope to open-source future versions of the model. Learn more: go.meta.me/43ea00
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Big shout out to @hongyu & team on the incredible post-training work!!
Hongyu Ren@ren_hongyu
Check out Muse Spark, our first milestone in the quest for personal superintelligence! Scaling this with the team has been a total blast. Give it a spin and let us know what you think! 🥑
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It’s 11th year and counting! Teaching the first lecture of @cs231n every year has been a highlight of my spring seasons. As usual, I asked students which departments or schools they come from @Stanford . Increasingly, students raise their hands to indicate that they come from all seven schools on campus, from @StanfordEng to @StanfordMed @StanfordHumSci @StanfordGSB @StanfordLaw @StanfordEd @stanforddoerr . AI is truly a horizontal technology that excites students across all backgrounds and disciplines!🤩
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Academic titles are funny. After 14 years, I finally have the official title that people might have always assumed I had.
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@venkyganesan @axiommathai @CarinaLHong Congratulations on releasing Axplorer! Looking forward to try it out soon.
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we are ALL in on AI
We are ALL IN on @axiommathai
@CarinaLHong and her co-founders are building a true iconic AI company
technologyreview.com/2026/03/25/113…
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At lunch today with a xAI friend, we predict total headcount of technical staff at xAI, OpenAI, DeepMind, and Anthropic will fall by at least 50% from today's numbers. We assign a prob. of 0.25 of this happening within 1 year, 0.5 within 2 years, and an .85 within 4 years.
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@Azaliamirh @stephzhan @guruchahal Just listened to it. Super inspiring. Can not wait to hear the next milestone!
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It was great to chat with @guruchahal about Ricursive, chip design bottlenecks and what's next for this industry!
Lightspeed@lightspeedvp
What if AI could design the chips that power the next generation of AI? That’s the vision behind @RicursiveAI, an AI-driven semiconductor design platform that uses reinforcement learning to compress the chip development process from years to weeks. We led their $300M Series A in January, and Co-Founders @annadgoldie and @Azaliamirh went in-depth about Ricursive and the future of AI-driven chip design in this episode of The Investment Memo with Lightspeed partner @guruchahal. 0:00 Welcome, Anna Goldie and Azalia Mirhoseini! 3:10 How the Idea for AI Chip Design Started 4:58 How They Expanded From Software to Chip Design 5:27 Turning the Idea Into a Google Moonshot 7:20 When Google Leadership Realized the Potential 10:35 Why Physical Design Is the Hardest Part of Chip Design 13:51 The 3-Phase Vision for the Future of Chip Design 17:51 Market Opportunity & Industry Disruption 20:24 The “Designless” Future of Hardware 22:04 Speed, Innovation & AI-Driven Exploration 21:00 The Role of Engineers in an AI-Driven Future 24:22 The Founders’ Unique Partnership Story 25:44 How They Hire World-Class Talent 27:05 Choosing the Right Investors 30:42 Advice for AI Researchers & Founders 33:16 What’s Most Important in the Next 12 months?
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