Chang Shi

PhD student @UTAustin. Interning @MSFTResearch NYC. Towards general-purpose robots 🤖. Previously @CMU_Robotics @Amazon Robotics @NECLabsAmerica

[Microsoft AI Frontiers @ms_aifrontiers]

We're at #ICML2026 in Seoul! Here's where to catch us

[Chang Shi @sshchang]

🔥

[Ziyan "Ray" Luo @RayZiyan41307]

🔥Thrilled to announce the Continual Reinforcement Learning (CRL) Workshop @RL_Conference 2026 in Montreal, Canada!

📣 We welcome submissions on broad topics of continual RL. Interested in submitting or reviewing? Check out our website for more details!

[Generalist @GeneralistAI]

Introducing GEN-1.

Our latest milestone in scaling robot learning.

We believe it to be the first general-purpose AI model to master simple physical tasks.

99% success rates, 3x faster speeds, adapts in real time to unexpected scenarios, w/ only 1 hour of robot data.

More🧵👇

[AMI Labs @amilabs]

Advanced Machine Intelligence (AMI) is building a new breed of AI systems that understand the world, have persistent memory, can reason and plan, and are controllable and safe.

We’ve raised a $1.03B (~€890M) round from global investors who believe in our vision of universally intelligent systems centered on world models. This round is co-led by Cathay Innovation, Greycroft, Hiro Capital, HV Capital, and Bezos Expeditions, along with other investors and angels across the world.

We are a growing team of researchers and builders, operating in Paris, New York, Montreal and Singapore from day one.

Read more: https://t.co/kyVAL7EoFx
AMI - Real world. Real intelligence.

[Andrej Karpathy @karpathy]

I packaged up the "autoresearch" project into a new self-contained minimal repo if people would like to play over the weekend. It's basically nanochat LLM training core stripped down to a single-GPU, one file version of ~630 lines of code, then:

- the human iterates on the prompt (.md)
- the AI agent iterates on the training code (.py)

The goal is to engineer your agents to make the fastest research progress indefinitely and without any of your own involvement. In the image, every dot is a complete LLM training run that lasts exactly 5 minutes. The agent works in an autonomous loop on a git feature branch and accumulates git commits to the training script as it finds better settings (of lower validation loss by the end) of the neural network architecture, the optimizer, all the hyperparameters, etc. You can imagine comparing the research progress of different prompts, different agents, etc.

https://t.co/YCvOwwjOzF
Part code, part sci-fi, and a pinch of psychosis :)

[Moonlake @moonlake]

https://t.co/vHXbGcwESD

[Tanishq Kumar @tanishqkumar07]

I've been working on a new LLM inference algorithm.

It's called Speculative Speculative Decoding (SSD) and it's up to 2x faster than the strongest inference engines in the world.

Collab w/ @tri_dao @avnermay. Details in thread.

[Carl Qi @carl_qi98]

Check out our work leveraging Entity-Centric Diffusion for Hierarchical RL🔥

[Chang Shi @sshchang]

“Video WMs are learnable physics simulators.” Can’t agree no more.

[Jim Fan @DrJimFan]

https://t.co/Npar79SvUh

[Chang Shi @sshchang]

I am at #NeurIPS25 from Dec 2nd to 7th. I will present our work at the https://t.co/FNgaxoU3aV workshop!

Would love to catch up with old friends and connect with new friends on robot learning, world models, RL, VLM/VLA … and more!

I am looking for 2026 internships and full time soon. Feel free to DM me and let’s chat!

[Chang Shi @sshchang]

As a robotics researcher, I believe accurately modeling complex interactions between agents would be a big step for scaling up robot learning from unlabeled video. Looking forward to some inspiring discussion with the Cohere Labs Embodied AI community!

[Cohere Labs @Cohere_Labs]

Don't miss our Embodied AI group's session this week on November 21st with @sshchang for a presentation on "FLAM: Scaling Latent Action World Models with Factorization."

Thanks to @nahidalam and Cole Harrison for organizing this event! ✨

Learn more: https://t.co/f08myuX4gn

[RL Beyond Rewards Workshop @RLBRew_RLC]

⚠️ Reminder! Submissions for @RL_Conference's RL beyond Reward Workshop are due May 30 (AoE)!

We are brewing an interesting program and seeking innovative research work in reward-free RL. All papers are welcome, from exploratory abstracts to complete research papers.

[Chang Shi @sshchang]

@harshit_sikchi @scottniekum @yayitsamyzhang @marcgbellemare @yukez @PeterStone_TX Big congrats Harshit! 🎉

[Chang Shi @sshchang]

@bauzavillalonga Super interested! Applied!