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.
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.
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...
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.