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Introducing The AI CUDA Engineer: An agentic AI system that automates the production of highly optimized CUDA kernels. The AI CUDA Engineer can produce highly optimized CUDA kernels, reaching 10-100x speedup over common machine learning operations in PyTorch. Our system is also able to produce highly optimized CUDA kernels...

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Sakana AI

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1,149,339 次观看 • 1 年前 •via X (Twitter)

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vittorio 的头像
vittorio1 年前

japan bros are back again

Globant 的头像
Globant1 年前

🚀 Agentic AI Systems are changing what AI can do by having the power to act independently. Unlike traditional AI, which needs constant human supervision, these systems can operate more autonomously. Learn how this shift is leading to smarter solutions that can transform industries.➡️ #TechTrends2025

ludwig 的头像
ludwig1 年前

I’m going to sleep if I wake up to this having 1M+ views I will read the paper tomorrow morning else pls give me a vibe check chat

Bing Xu 的头像
Bing Xu1 年前

I quickly take a look of their report on phone, there are a few misleading parts: 1. Torch C++ code is not CUDA kernel, it is calling CUDNN under hood. 2. The highlighted example Conv3D GroupNorm, conv code is not generated at all. The speedup doesn’t make sense if numerical is wrong. 3. It claims wmma can be faster than PyTorch (CUBLAS), is definitely wrong. Probably benchmark error.

main 的头像
main1 年前

isn't there clearly something wrong with level_1->15_Matmul_for_lower_triangular_matrices? claimed 152.9x speedup for the kernel on the left over the code on the right. really?

Viraat 的头像
Viraat1 年前

Hey - wondering if you all are only working with large enterprises right now. If not, we’d love to chat! This would be extremely useful to us - we’re building low-bit models to run efficiently on Jetsons. Generating optimized CUDA code for these would be a game-changer!

aizk ✡️ 的头像
aizk ✡️1 年前

A slow 14 seconds in AI developments

Dan Mac 的头像
Dan Mac1 年前

guys seriously I can't take it anymore need to slow down

Kristof 的头像
Kristof1 年前

Japan is back

Dr Futuro - e/acc 的头像
Dr Futuro - e/acc1 年前

Wow, Japan is back! 🇯🇵

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🎉 Stoked to share The AI CUDA Engineer 👷 - our end-to-end approach for automating the design and optimization of CUDA Kernels using agentic systems. Blog 📰: Paper 📜: WebUI 📈: Dataset 💽: Awesome team work done with Aaditya Prasad 🇺🇸, Suuun, Maxence Faldor, Yujin Tang, hardmaru 🤗
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