Yuandong Tian

1.1K posts

Yuandong Tian

Yuandong Tian

@tydsh

Co-founder of @Recursive_SI. ex-Meta FAIR Director. ex-Google. Reasoning, Optimization and Understanding LLM. Novelist in spare time. PhD in @CMU_Robotics.

California, USA Katılım Aralık 2009
939 Takip Edilen43.7K Takipçiler
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Yuandong Tian
Yuandong Tian@tydsh·
Today we launch Recursive. We are building AI that discovers knowledge automatically and improves itself recursively, an open-ended process that will fundamentally change how science and technology advance. Our 25 top researchers and engineers in San Francisco and London bring diverse expertise spanning agentic AI scientists, architecture and algorithm design, world models, optimization, and interpretability, united by a shared conviction that this is the most important problem we could be working on today. If you are interested in joining, please send your resume to talent@recursive.com. Follow us at @Recursive_SI!
Recursive@Recursive_SI

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Dominik Schmidt
Dominik Schmidt@schmidtdominik_·
some news: I've joined @Recursive_SI as a member of the founding team in London. We are building safe, recursively self-improving intelligence. So excited about our discoveries so far and even more so about everything that lies ahead.
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Tim Rocktäschel@_rockt

Excited to co-found Recursive (@recursive_si) with an exceptional team in London and SF to create AI that experiments on how to safely improve itself, turning compute into knowledge that accumulates in an open-ended process of endless, automated scientific discoveries.

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Shengran Hu
Shengran Hu@shengranhu·
Some updates: I've joined Recursive as a member of the founding team. My core curiosity about the world centers on how complex patterns and knowledge emerge from the two open-ended processes we know: natural and cultural evolution. I've been lucky to explore this during my PhD through works like ADAS, Darwin Gödel Machine, and The AI Scientist. Excited to keep chasing this thread with the incredible team!
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Yingbo
Yingbo@yingbozhou_ai·
Personal update: I’ve joined @Recursive_SI as a member of the founding team. We’re working on safe, recursively self-improving intelligence. I’m excited by what we’ve learned so far, and even more excited for the work ahead!
Recursive@Recursive_SI

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Jianguo Zhang
Jianguo Zhang@JianguoZhang3·
Life update: I’ve joined @Recursive_SI as part of the founding team, based in San Francisco. At Recursive, we’re building safe, recursively self-improving superintelligence to automate knowledge discovery. Grateful to be part of this team ❤️, and excited for what’s ahead 🔥.
Recursive@Recursive_SI

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Mingchen Zhuge
Mingchen Zhuge@MingchenZhuge·
Today, @recursive_si is coming out of stealth. Over the past few years, I’ve become increasingly convinced that Recursive Self-Improvement (RSI) will define one of the most important frontiers in AI. Now feels like the right moment to help turn these possibilities into reality. I’m excited to join as a founding member and help build practical and safe self-improving AI systems. Thanks to all of our co-founders for the vision and opportunity ♥️
Richard Socher@RichardSocher

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Josh Tobin
Josh Tobin@josh_tobin_·
Today we’re launching Recursive (@Recursive_SI) We’re building AI that automates science, starting with the science of how to improve itself. I’ve spent a lot of time building AI products and tools for AI teams. One thing that has always stood out is how much progress depends on the experimental loop: deciding what to try, implementing it, running it, understanding what happened, and repeating. Recursive is automating that loop, safely and at scale. Excited to work on this with an incredible team across SF and London.
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huiche bu
huiche bu@Huiche2025·
@tydsh Service Unavailable The server is temporarily unable to service your request due to maintenance downtime or capacity problems. Please try again later. Apache/2.4.55 (Ubuntu) Server at blog.yuandong-tian.com Port 443
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Yuandong Tian
Yuandong Tian@tydsh·
Got a request from a professor wanting to cite my Zhihu new year blogpost in his paper, about my theory of "Fermi Level" for human society due to AI impact. So I translate it, together with building a personal blogpost site. yuandong-tian.com/blog/posts/ It only takes a few hours to nail down all the details, and it is only one of the concurrent workstreams. AI coding agents are just incredible nowadays!
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Yuandong Tian
Yuandong Tian@tydsh·
Another thing I would like to mention is that in the last 5 years in Meta, I always face the situation that as a manager/director, I cannot be too hands-on to take over my reports' scope. I was warned in the performance review at some point. After the OpenGo project in which I wrote 90%+ of the code, I was told "researchers need to do research and engineers do engineering work". Therefore, doing first author/solo work is one way to keep my sense of owning things end to end, and get to know what's really going on. Now I am super happy that the constraint is gone forever, thanks for the AI coding tools.
维尼诗人 | Winnie the Poet@JaredLipton

@tydsh Congratulations! I always admire senior authors that have time and energy to do solo work. Would you mind sharing a bit on how you balance this type of work with joint work with others? What are the main challenges?

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Yuandong Tian
Yuandong Tian@tydsh·
@MingchenZhuge Thanks for inviting me for the talk and the panel! It was super fun! Talk slides: yuandong-tian.com/talks/rsi_work…. Thanks for promoting my novel as well😁. I should have a RSI agent to help me finish the second one!
Mingchen Zhuge@MingchenZhuge

@tydsh always enjoy your presentations, whether at workshops or podcasts, as well as your insights on post-training, RSI, and even your sci-fi writing. 🥳🥳🥳 ~ recursive-workshop.github.io #RSI #ICLR2026 #破晓之钟

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Yuandong Tian
Yuandong Tian@tydsh·
History repeats itself 😀 The concept "learning mechanics" is not a new thing but actually has been explored for a very long time. It is human nature to think deeper than a blind belief of the scaling laws. I have been working on rigorously modeling training dynamics of deep nonlinear models for many years, with many non-trivial solvable examples in nonlinear dynamics that may be interesting for @learning_mech to take a look. This includes 1. Contrastive learning (e.g., arxiv.org/abs/2110.09348 arxiv.org/abs/2201.12680, arxiv.org/abs/2206.01342) 2. Non-contrastive learning (e.g., arxiv.org/abs/2102.06810, arxiv.org/abs/2110.04947) 3. Training dynamics in Transformers (e.g., arxiv.org/abs/2310.00535, arxiv.org/abs/2305.16380) 4. Grokking behaviors (arxiv.org/abs/2509.21519) 5. Spontaneous symmetry breaking (arxiv.org/abs/1703.00560) 6. Mechanism in forming symbolic solutions from gradient descent (arxiv.org/abs/2410.01779) I am the first/solo author in most of the works listed above. Code are here: github.com/yuandong-tian/…
Jamie Simon@learning_mech

1/ Deep learning is going to have a scientific theory. We can see the pieces starting to come together, and it's looking a lot like physics! We're releasing a paper pulling together these emerging threads and giving them a name: learning mechanics. 🔨 arxiv.org/pdf/2604.21691 🔧

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Keşfet

@Recursive_SI @recursive_si @RichardSocher @_rockt @Huiche2025 @MingchenZhuge @learning_mech @elonmusk