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YC is wrong about LLMs for chip design

(www.zach.be)
321 points laserduck | 1 comments | 16 Nov 24 14:07 UTC | HN request time: 0.205s | source
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grepLeigh ◴[16 Nov 24 17:40 UTC] No.42157675[source]▶
Nvidia is trying something similar: https://blogs.nvidia.com/blog/llm-semiconductors-chip-nemo/

I'd want to know about the results of these experiments before casting judgement either way. Generative modeling has actual applications in the 3D printing/mechanical industry.

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therealcamino ◴[17 Nov 24 04:15 UTC] No.42161915[source]▶
That sounds like good work, but we can't ignore the context. Nvidia can train their own LLM's on proprietary Nvidia designs, which isn't a possibility for a random startup.

If the evaluation of the approach is "it works great if you train it on a few decades of the best designs from a successful fabless semiconductor company", I would say that if you plan to use that method as a startup, you're clearly going to fail. Nobody's going to give away their crown jewels to train an LLM that designs chips for other companies.

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1. shash ◴[17 Nov 24 17:56 UTC] No.42165637[source]▶
The problem _there_ is that there's very little diversity in the training data - it's all NVidia designs which are probably from the same phylogenetic tree. It'll probably end up regurgitating existing NV designs...