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It would be very surprising if a Large Language Model trained to speak English could adequately specify chip architecture...


why not? a netlist can be easily 'tokenized'. its already in parse-able format. you can just could just chop off the English input portion and it will consume. in fact I am sure you could write a 'read & speak' type program to read the RTL spec and feed it in but I'll suspect they'll a custom trained LLM on millions of generated RTL examples.


You'd need to spend a long time training it on something other than English... at which point it's not an LLM. I definitely agree that the LLM architecture is useful for a lot more than just language per se assuming you can appropriately tokenize your inputs.


Why? Chip architecture specifications are written in English!

Are you surprised that ChatGPT can write Python?




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