Short answer: Sohrab Haghighat says no direct link: physical design needs a custom model built from the ground up, so better LLMs mainly help his team code faster to build that model.
Watch this answer from Episode 53 (starts at 15:21) · Episode 53 notes and transcript
From Episode 53: He Ran a Rocket Launch Company. Now He Is Building Autocomplete for Hardware Design., starting at 15:21.
Sohrab Haghighat [15:20]: Yeah. So personally, I use Anthropic models for, programming, myself. And, yes, it is exciting that the cost of intelligence is going down. That's, always worth celebrating for. However, I do agree with you, Jordan, that there... As much as there are high level talks about we should slow down, there doesn't seem to be any of that talk really materialized. For our own development, so, obviously, the more advanced models that we can use to faster build our own product better. The advance in LLMs necessarily is not going to materialize in form of advancement in our model because we believe, to solve the problem for physical design, we need to have a custom architected model built from ground up meant for that specific application. So there's not a direct translation of LLM improves. That means that Hestus is going to improve. LLM improves means that we can code faster to build our model fast, but, which is always something that we're up for it. If it's cheaper for us to code, amazing. That's great.
Sam Nadler [16:38]: So, Rob, it was a pleasure. Thank you for joining. This may be the episode that kicks us over 40,000 subscribers, so that will be a big milestone for us. Everyone, go check out Hestus. It looks like a great product, that's accelerating people's ability to design hardware faster. So, Jordan, any final thoughts?
Jordan Metzner [16:58]: Great episode. Great product. So thanks for the demo. That was really cool. And, yeah, great episode. And thanks, Sam. Thanks, Rob. See you guys soon.
Sohrab Haghighat [17:05]: Thank you for having me here.
Jordan Metzner [17:06]: Awesome. Thanks, Rob. Bye, guys.
