Thanks for the repro! I also attached the result of running this layer norm kernel on an Nvidia 5090 (1311% perf of baseline) Kernels are very hardware (and problem size) dependent, but that’s great news for auto kernel optimization. AI can easily run architecture and workload

Exciting! Looking forward to it

This is a proper Vibe-coding setup for GPU programmers, and can result in getting surprisingly far! I honestly think that if this authoring experience is v1, then v10 might become the normal way GPU experts start writing serious custom kernels! Great work Anne Ouyang! (finally

We introduce CodeARC, a new benchmark for evaluating LLMs’ inductive reasoning. Agents must synthesize functions from I/O examples—no natural language, just reasoning. 📄 arxiv.org/pdf/2503.23145 💻 github.com/Anjiang-Wei/Co… 🌐 anjiang-wei.github.io/CodeARC-Websit… #LLM #Reasoning #LLM4Code #ARC

tech is full of people quietly haunted by the artist they could've been ✨

Ceci n'est pas une pipeline

cheburashka > labubu

Looking forward to attending ICML! Here are some works on memory/long context, verification, kernel design, multi-model AI systems, and theoretical understanding of test-time scaling from my awesome students and collaborators!

Title: Advice for a young investigator in the first and last days of the Anthropocene Abstract: Within just a few years, it is likely that we will create AI systems that outperform the best humans on all intellectual tasks. This will have implications for your research and

i asked gpt to rewrite a matmul kernel in cute