Michael Yu

AI Research

[Michael Yu @_michael_yu_]

@RiskHotTake @stevenyfeng @icmlconf We’d be interested to see a systematic study of those patterns though, for ex. RAG vs. agents vs. summarization. It’s an interesting direction.

[Michael Yu @_michael_yu_]

@RiskHotTake @stevenyfeng @icmlconf Thanks, appreciate it! The focus was on developing a unified framework that accommodates different use cases by changing the reference “world”, rather than characterizing how hallucination types vary across them.

[Steven Feng @stevenyfeng]

We keep saying LLMs "hallucinate." But what does that actually mean?

In our new position paper, we argue hallucination isn't just "wrong facts." It's inaccurate internal world modeling.

We formalize this precisely in a unified definition to appear at #ICML2026 (@icmlconf)👇

[Steven Feng @stevenyfeng]

We’re bringing back Stanford’s CS25 Transformers course tomorrow! 🤖

It’s open to everyone (in-person + online). Weekly talks (every Thursday) from top AI researchers.

One of Stanford’s most popular AI seminar courses. Don’t miss out!

More info below 👇 (1/7)

[Michael Yu @_michael_yu_]

If the world were to end in a year, how would we best preserve all our knowledge for aliens to discover in the future?
Would it be through compressing everything we knew into parameters of a large neural network and sending that into space?

[Michael Yu @_michael_yu_]

@wjy35 yes! energy and data I think

[Arjun Vikram @arjvik]

Proud to share what I've been working on for the past year, "Learning to (Learn at Test Time)"!

Our new architecture trains a model to "learn" from its context, replacing Attention's costly KV cache with an expressive hidden state: the weights of a ML model!🤯

🧵by @karansdalal

[Michael Yu @_michael_yu_]

@wjy35 very impressive!

[Michael Yu @_michael_yu_]

Me and my friends @stevenyfeng and @HaoranZhaoHRZ met @karpathy a few weekends ago when he was giving the keynote and winner pitches at UC Berkeley ai hackathon. It was great to have a face to face chat with a top AI researcher and educator. Super nice and humble guy.

[Michael Yu @_michael_yu_]

Machine learning should be thought of as an accelerator for the information revolution rather than a subset of computer science