OpenAI and Synopsys Team Up to Build GPT-Synopsys, an AI That Designs Chips
GPT-Synopsys: Frontier Intelligence to Revolutionize Chip Design
OpenAI and Synopsys have signed a multi-year partnership to develop GPT-Synopsys, a specialized model that learns to operate Synopsys' EDA tools like an expert engineer. It will run on OpenAI infrastructure and integrate with Synopsys.ai and Synopsys Autopilot, letting engineers delegate design objectives and iterate toward verified outcomes. The deal includes revenue sharing, joint go-to-market, and enterprise-grade data protection.
We're using our most advanced technology to improve the systems that power AI. With Synopsys, we're bringing that work to chip design, helping engineers explore more designs and get to a working chip faster.
- fwlr
GPT-Synopsys brings together OpenAI frontier models with Synopsys' EDA technology and domain expertise, enabling the specialized model [to] directly operate Synopsys' tools. Engineers will delegate design objectives … with agents running tools, interpreting results, implementing changes, and iterating toward verified outcomes for engineer review.
“Agents will do all the engineering work. Engineers will delegate and review.” Lol, no, what the engineers are gonna do is get laid off.
- aurareturn
From an investment perspective, I think chip fabs TSMC, Intel, and Samsung will benefit from better AI chip design tools.
If AI made it 100x faster and cheaper to build software, you suddenly have an explosion of software that need to be hosted. So companies like AWS/iOS App Store/cloud companies benefit.
If AI makes designing chips 100x faster and cheaper, you will have an explosion of custom chips for all sorts of applications. These chips still need to be physically made at TSMC, Intel, or Samsung.
Apple says it takes 3-4 years to design each Apple Silicon generation.[0] So the M6 was being designed in 2022-2023 already. Reports are that it costs hundreds of millions to a billion to design a cutting edge chip from scratch to finish.[0]
The cool thing is that we'll have niche ASIC chips for accelerating special applications that previously didn't have big of a market for someone to make a profit on. This is the same thing with software today. It's much easier to build custom software for a small niche and be profitable today than in 2022.
Maybe some day, a kid in his garage can just tell an AI to design a custom chip, send it to TSMC, and get the chip in the mail in a few weeks.
And given that Moore's Law is essentially dead in terms of density scaling, having an AI to automatically optimize the hell out of design and squeeze as much performance as possible out of the transistors could help us have a few more years of nice performance increase.
[0]https://fireflies.ai/blog/ […]
- karlkloss
We just buried an ASIC design that was nearly finished.
Reason: There was a deviation that would've needed a mask change, but because of AI chip demand, the manufacturer wanted so much money for it, that we said screw it.
So we now have AI powered chip design tools that make chip design cheaper, but because of AI, chip manufacturing has become so expensive, that we can't afford it anymore.
Nice.
- aniceperson
> I see you are using Cadence IP in your project, unfortunately this is not allowed per the terms and conditions and you will be reported to the authorities
Also : create proprietary locked down eda->no data to train models->models suck at it->reach out to ai lab to rl on it -> expect users to pay for eda and the model.
- joennlae
„The joint service offering will provide the bundled compute, model, and licenses, while ensuring customer-specific design data is protected.“
I am not sure if Nvidia want to send their chip designs to OpenAI.