The idea of machines that can build even better machines sounds like sci-fi, but the concept is becoming a reality as companies like Cadence tap into generative AI to design and validate next-gen processors that also use AI.
In the early days of integrated circuits, chips were designed by hand. In the more than half a century since then, semiconductors have grown so complex and their physical features so small that it’s only possible to design chips using other chips. Cadence is one of several electronic design automation (EDA) vendors building software for this purpose.
Even with this software, the process of designing chips remains time-consuming and error-prone. But with the rise of generative AI, Cadence and others have begun exploring new ways to automate these processes.
In theory… In practice is another story.
I mean, they aren’t deploying language models for thos, as far as I know.
they are using… u know?.. more classic deep learning models which are hard-trained on rule-based feedback, so like, stuff which is explicitly made for this one task.
which… feels reasonable?
today’s transformer architecture makes this kinda stuff valid, so as long as someone with actual experience and knowledge is using the model as a draft kinda thing, it feels like a good starting point… (but eh, what I say doesn’t matter, I don’t work in the chip industry)