Sanghyuk Lee

Quasi MLE, Quasi SWE

[Soumith Chintala @soumithchintala]

Leaving Meta and PyTorch

I'm stepping down from PyTorch and leaving Meta on November 17th.

tl;dr: Didn't want to be doing PyTorch forever, seemed like the perfect time to transition right after I got back from a long leave and the project built itself around me.

Eleven years at Meta. Nearly all my professional life. Making many friends for life. Almost eight years leading PyTorch, taking it from nothing to 90%+ adoption in AI. Walking away from this was one of the hardest things I've ever done. But I'm leaving with a full heart.

PyTorch handles exascale training now. It powers foundation models that are redefining intelligence. It's in production at virtually every major AI company. It's taught in classrooms from MIT to rural India. The tools I dreamed about making accessible? They are. The barrier to entry I wanted to lower? It's almost gone.

To be clear, there’s so much more to do. As long as AI evolves at a breakneck pace, PyTorch will continue to play catch up. Obsessing over the yet-to-come sometimes makes us forget how much we’ve already done.

To everyone who built this with me—who believed research should be joyful, that tools should be elegant, that open source changes everything—thank you. This wasn't my journey. It was ours.

What's next for me? Something small. Something new. Something I don't fully understand yet. Something uncomfortable. I could have moved to something else inside Meta. But I needed to know what's out there. I needed to do something small again. I couldn't live with the counterfactual regret of never trying something outside Meta.

It's very hard to leave. I probably have one of the AI industry’s most leveraged seats, I lead the software layer that powers the entire AI industry. Every major AI company and hardware vendor are on a speed dial. This kind of power is really hard to give up. But curiosity ultimately won out in my head.

Keep making AI delicious and accessible. I'll be watching. Probably filing issues. Definitely staying involved.

Is PyTorch going to be okay?

I don't want to be doing PyTorch forever. I don't want to be like Guido or Linus— bound to a single thing for decades. Last November, coinciding with the birth of my daughter, I started planning my exit with Aparna. My goal was to leave PyTorch in a good and stable place.

By this August, during the second half of my parental leave, I knew: Edward, Suo, Alban, Greg, John, Joe and Jana were ready. The team faced hard people, product, technical and organizational problems and didn’t feel the need to lean back on me to solve these for them (unlike in the past). The product story they crafted for the PyTorch Conference was coherent—really coherent. The things I'd flagged red were turning healthy. The project didn't need me anymore. Unlike 2020-2022 (when I stepped down to go do robotics and came back when Lin, Dima and Dwarak left), I have strong confidence that this time PyTorch is truly resilient. The most aligned culture carriers of PyTorch – Greg, Alban, Ed, Jason and Joe are at the decision table now, and people with strong value alignment – Suo, John and Jana have joined them at the table. And there’s a long list of equally value-aligned people willing to sit at the table should any of these people leave. There are many little things that make up my confidence on the people – John worked on Julia and open-source for a very long time (in fact we hacked a Torch.jl in 2015), Suo has been the strongest systems builder and strategic partner I’ve had for the past two years, and Jana worked on resilient core systems for a very long time, I’ve had long technical and organizational discussions with her over the past few months that give me confidence. And the product lineup and execution in 2025 should be sufficient evidence for any remaining doubt.

I’m confident that this band of PyTorchers are going to do exceptionally well. PyTorch might change in flavor because I no longer impose my own taste from the top, but I’m confident that the values are going to stay intact and the product is going to be awesome.

My time at Meta

The early years of FAIR were absolutely magical. I was part of a small family of absolutely brilliant people building state-of-the-art AI out in the open. From working on GANs with Emily Denton, Rob Fergus, Leon Bottou, Martin Arjovsky and the (now legendary) Alec Radford to building Starcraft bots with Gabriel Synnaeve, to building the first FAIR Cluster with Howard Mansell, to working on object detection with Adam Lerer and Piotr Dollar, to building PyTorch. It was more fun than I can describe in words. 2015 and 2016 were probably the most productive and professionally enjoyable years of my life. I’ll probably romanticize this period of my life forever.

When I joined FAIR, I had massive impostor syndrome, and the first 3 months were very very difficult. I can’t credit Andrew Tulloch enough for being the most thoughtful, kind and welcoming mentor, without whom I wouldn’t have made it. I’m so damn bullish for Meta just from the fact that he’s back.

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My time on PyTorch was special.

I loved every part of building it—designing it, managing it, being the PM, TL, comms lead, doc engineer, release engineer, squashing bugs, growth hacking, turning it into a coherent product with hundreds of people, transitioning it to industry stakeholdership – the whole nine yards.

To the core PyTorch team at Meta: the engineers, researchers, open-source maintainers, docs writers, CI infrastructure folks, hardware partners, the community builders. To the hundreds more inside and outside Meta—thank you. You turned a library into a movement.

There are too many people to credit and thank, but I can't not mention Adam Paszke, Sam Gross, Greg Chanan, Joe Spisak, Alban Desmaison, Edward Yang, Richard Zou, Tongzhou Wang, Francisco Massa, Luca Antiga, Andreas Köpf, Zach DeVito, Zeming Lin, Adam Lerer, Howard Mansell and Natalia Gimelshein. And Schrep. They made the launch happen. And so many more people became centrally important later: Lu Fang, Xiaodong Wang, Junjie Bai, Nikita Shulga, Horace He, Mark Saroufim, Jason Ansel, Dmytro Dzhulgakov, Yangqing Jia, Geeta Chauhan, Will Constable, Briah Hirsh, Jane Xu, Mario Lezcano, Piotr Balecki, Yinghai Lu, Less Wright, Andrew Tulloch, Bruce Lin, Woo Kim, Helen Suk, Chris Gottbrath, Peng Wu, Joe Isaacson, Eli Uriegas, Tristan Rice, Yanan Cao, Elias Ellison, Animesh Jain, Peter Noordhuis, Tianyu Liu, Yifu Wang, Lin Qiao and hundreds more. It’s criminal of me to not take the space to list out everyone else I should be mentioning here. PyTorch is nothing without its people ❤️.

The most joyful moments of building PyTorch was meeting users eager to share their happiness, love and feedback. I remember a grad student coming to me at Neurips 2017, in a slurring emotional voice he said he’d been trying to make progress on his research for 3 years but within 3 months of using PyTorch he made so much progress that he was ready to graduate. That moment made it tangible that what we do matters, a lot, to a lot of people, even if you don't constantly hear from them. I do miss the intimacy of the PyTorch community, with a 300 person conference that felt like an extended family gathering, but I feel that’s a small price to pay considering the scale of impact PyTorch is truly having today – yes the Conference is now 3,000 people where market-moving deals get brokered, but it’s helping orders of magnitude more people to do their best AI work. I miss the intimacy, but I'm proud of that growth.

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To Mark Zuckerberg and Mike Schroepfer, who believed that open-sourcing is fundamentally important and is a sound business strategy. This is so hard to understand for most people within the course of business, but we’ve run lock-step on this strategy without ever having to discuss it. Without you two, neither FAIR nor PyTorch would’ve happened. And those mean so much to me.

To Yann LeCun and Rob Fergus, for building the magical early FAIR that I so revere.

To Aparna Ramani, a leader that I find so rare at Meta in her ability to hold a really high bar for the org, technically brilliant with the span to discuss deep infra systems and industry-strategy within the same conversation and for being an absolute execution-machine! I’ve learned so much from you.

To Santosh, Kaushik, Delia, Oldham and Ben for being so welcoming to Infra. For someone coming over from FAIR with a wildly different culture, you all made me feel at home and made me part of the family, and thank you for that.

To all my managers who've championed me through the PSC video game – Serkan, Howard, Jerome, Abhijit, Yoram, Joelle, Aparna and Damien – I owe you a lifetime of drinks.

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Signing off for now.

—Soumith

[Sanghyuk Lee @shylee2021]

@askalphaxiv Please fix the sign in process. It has been broken for more than a day I presume. I cannot even open a thread in the community since I am not able to sign in.

[Nathan Lambert @natolambert]

Language models may not get us to “superintelligence”, but they’re definitely already powerful enough to create very socially and economically destabilizing technologies so it doesn’t really matter. We have to make the world ready for that.

[meowbooks @meowbooksj]

the brittle lesson

[Kevin Patrick Murphy @sirbayes]

I'm happy to announce that v2 of my RL tutorial is now online. I added a new chapter on multi-agent RL, and improved the sections on 'RL as inference' and 'RL+LLMs' (although latter is still WIP), fixed some typos, etc.
https://t.co/dWe5uNgcgp

[Akshay 🚀 @akshay_pachaar]

Build and deploy LLM agents using just natural language! 🔥

AutoAgent is a fully-automated, self-developing framework that lets you create and deploy LLM agents using natural language alone.

(100% open-source)

[Tanvi @tanvitabs]

🚨Breaking: DeepSeek R2 has set the release date — March 17th

and Claude Sonnet 3.7 might just be in trouble coz DeepSeek R2 claims:

1. better coding
2. reasoning in multiple languages
3. better accuracy for fraction of the cost

(recap of R1👇🧵)

[Ray @rincidium]

I did it. I built "Cursor for Writing".

Introducing Lucid ✨
- Write at the speed of thought
- Pull in context from anywhere
- Chat + Deep Research

[Qwen @Alibaba_Qwen]

Today, we release QwQ-32B, our new reasoning model with only 32 billion parameters that rivals cutting-edge reasoning model, e.g., DeepSeek-R1.

Blog: https://t.co/jpNEx0Ck8p
HF: https://t.co/h91przQmoP
ModelScope: https://t.co/p0ztmZpWIZ
Demo: https://t.co/sxVVRFwunC
Qwen Chat: https://t.co/bg4tAU1p74

This time, we investigate recipes for scaling RL and have achieved some impressive results based on our Qwen2.5-32B. We find that RL training con continuously improve the performance especially in math and coding, and we observe that the continous scaling of RL can help a medium-size model achieve competitieve performance against gigantic MoE model. Feel free to chat with our new models and provide us feedback!

[Sanghyuk Lee @shylee2021]

@amelia_250212 I like Cola Independence 815

[Philipp Schmid @_philschmid]

The next big performance jump for AI Agents will come when we have more control over the reasoning/thinking process. LLMs should be able to use tools when they reason.

Reason -> Stop -> Execute tool -> Include result -> Continue reasoning

Why? Reasoning models have learned native self-verification, search, and backtracking! Thats all you need!

This would also allow us to fine-tune them for specific agent use cases and use smaller models.

We should return to basic “text completion” APIs, where we can add custom stop tokens and continue from any part I want (prefilling).

[Sanghyuk Lee @shylee2021]

저희 팀에서 AI agent를 만드는 개발자들이 tool use 를 쉽게 할 수 있도록 하는 라이브러리 Hyperpocket을 릴리즈했습니다.

바로 쓸 수 있는 tool들과 authentication 핸들링, 격리된 실행환경, 타 언어 및 타 라이브러리를 위한 tool 실행기능 등등을 제공하고요.
무엇보다도 이 모든 것을 오픈소스로 공개했습니다! 커뮤니티 여러분들의 많은 참여를 바랍니다.

https://t.co/fPTKhpCdub

[Sanghyuk Lee @shylee2021]

And check out this awesome demo of agent that releases Hyperpocket using the Hyperpocket autogui tool developed by my brilliant teammate! 🤣 The autogui tool will be uploaded to Hyperpocket repo soon.

l'm also looking forward to meet other wonderful tools like this from the community! 👏👏

[Sanghyuk Lee @shylee2021]

🎉 Excited to announce the release of Hyperpocket – a library that makes integrating AI agents with tools seamless and efficient! 🚀

Hyperpocket offers:
✅ Out-of-the-box tools
✅ Built-in auth
✅ Tool execution in isolated environments
✅ Self-hosted setup
✅ Easy import of tools from other communities
✅ And most importantly… it’s fully open-source!

Check it out and give us a ⭐ on GitHub:
🔗 https://t.co/fPTKhpCdub

[Sanghyuk Lee @shylee2021]

https://t.co/JXgiHtIZrw
와 이건 진짜

[Sanghyuk Lee @shylee2021]

12월 4일 새벽 1시 35분 대한민국 현 상황

[Rémi in 🌁 for AIEF @remilouf]

I’ve already deleted a couple thousands lines of code from Outlines. The v1.0 refactor is going very well.

[Sanghyuk Lee @shylee2021]

B2B 회사에 다닌다는 것은, 불매하고 싶은 회사가 갈수록 늘어난다는 것ㅋㅋㅋㅋㅋㅋ

[Ravid Shwartz Ziv @ziv_ravid]

Looking at ICLR submissions with the lowest score - What a work of art! 🧵

[Alex Heath @alexeheath]

exactly what the ghost of Steve Jobs intended the Dyamnic Island be used for