Nvidia Trains LLM on Chip Design
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Nvidia Trains LLM on Chip Design
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Re: Nvidia Trains LLM on Chip Design
#2The first chip they give it to design should be an ML chip that is optimized for ML chip design.
Re: Nvidia Trains LLM on Chip Design
#3"Nvidia Trains LLM on Chip Design" + " documentation"
Re: Nvidia Trains LLM on Chip Design
#4The title is a bit misleading as the first sentence says "to help chip designers with tasks related to chip design, including answering general questions about chip design, summarizing bug documentation, and writing scripts for EDA tools."
Still pretty cool though.
Re: Nvidia Trains LLM on Chip Design
#5[deleted]
Re: Nvidia Trains LLM on Chip Design
#6The title is a bit misleading as the first sentence says "to help chip designers with tasks related to chip design, including answering general questions about chip design, summarizing bug documentation, and writing scripts for EDA tools." Still pretty cool though.
Isn’t that what chip design is?
Re: Nvidia Trains LLM on Chip Design
#7Google has been using machine learning for chip design since at least 2021: https://www.nature.com/articles/s41586-021-03544-w
Hasn't brought about the singularity yet.
Re: Nvidia Trains LLM on Chip Design
#8The title is a bit misleading as the first sentence says "to help chip designers with tasks related to chip design, including answering general questions about chip design, summarizing bug documentation, and writing scripts for EDA tools." Still pretty cool though.
Isn’t that what chip design is?
The title suggested to me, and I see other commenters here, that the LLM was doing the chip design which isn't the case at all. So misleading title.
Re: Nvidia Trains LLM on Chip Design
#9Interesting concept that raised the question for me:
What is the primary limiting factor right now that prevents LLM’s or any other AI model to go “end to end” on programming a full software solution or full design/engineering solution?
Is it token limitations or accuracy the further you get into the solution?
Re: Nvidia Trains LLM on Chip Design
#10Interesting concept that raised the question for me: What is the primary limiting factor right now that prevents LLM’s or any other AI model to go “end to end” on programming a full software solution or full design/engineering solution? Is it token limitations or accuracy the further you get into the solution?
LLM's can't gut a fish in the cube when they get to their limits.
On a more serious note: I think the high-level structuring of the architecture, and then the breakdown into tactical solutions — weaving the whole program together — is a fundamental limitation. It's akin to theorem-proving, which is just hard. Maybe it's just a scale issue; I'm bullish on AGI, so that's my preferred opinion.