How can LLMs code for cutting-edge hardware when there's almost no training data?
— 机器之心 JIQIZHIXIN (@jiqizhixin) 8 avril 2026
Researchers from Shanghai Jiao Tong University, Shanghai AI Lab, and MemTensor present EvoKernel!
This self-evolving AI agent teaches LLMs to write code for new, data-scarce hardware. It uses a… pic.twitter.com/dHIJZlxYTd
How can LLMs code for cutting-edge hardware when there's almost no training data? Researchers from Shanghai Jiao Tong University, Shanghai AI Lab, and MemTensor present EvoKernel! This self-evolving AI agent teaches LLMs to write code for new, data-scarce hardware. It uses a clever memory system to prioritize and learn from the most valuable coding experiences, continually refining its drafts. EvoKernel boosts code correctness for NPU kernel synthesis from a mere 11% to an impressive 83% and speeds up programs by 3.6x over initial drafts! Towards Cold-Start Drafting and Continual Refining: A Value-Driven Memory Approach with Application to NPU Kernel Synthesis Project: evokernel.zhuo.li Paper: arxiv.org/abs/2603.10846 Our report: mp.weixin.qq.com/s/0TOzZ_rZn… 📬 #PapersAccepted by Jiqizhixin