An Apple executive says that the company is looking to use generative artificial intelligence to help design the custom chips used in its product lines. According to Reuters, Senior Vice President of Hardware Technologies Johny Srouji said that the company learned that it needs to use the latest, cutting-edge tools when designing its chips. This includes the use of AI in electronic design automation (EDA) software, which industry giants Cadence Design Systems and Synopsys have been racing to add to their offerings.
“EDA companies are super critical in supporting our chip design complexities,” Srouji said at the Belgian research and development organization Imec. “Generative AI techniques have a high potential in getting more design work in less time, and it can be a huge productivity boost.”
The news follows a report from China where researchers claim to have developed the world's first AI-designed processor, using an LLM to create a CPU architecture.
Imec, which began as a collaborative research initiative between Belgian academic institutions but has since evolved into a nanoelectronics and digital technology research hub, honored Srouji with its 2025 Innovation Award for his work in the development of Apple Silicon, starting with the development of the A4 chip — Apple’s first custom system-on-a-chip.
What began as a custom processor for iPhones and iPads has eventually evolved into the M-series SoC that powers Apple’s Mac lineup, which was first launched in 2020. This was the biggest change in consumer computing in recent years, with Apple using the Arm architecture to challenge x86’s domination in the desktops and laptops. More than that, the 13-inch Apple MacBook Pro (M1) delivered a far-improved battery life and performance that its peers struggled to match.
Apple went all-in with the M1 chip at launch, said Srouji, “Moving the Mac to Apple Silicon was a huge bet for us. There was no backup plan, no split-the-lineup-plan, so we went all in, including a monumental software effort.”
After all, despite delivering high performance, M-series SoCs would not have worked out without widespread software support from Apple and many third-party software developers. Part of this ‘monumental software effort’ was the development of the Rosetta 2 translation layer, which allowed x86 apps to run on Apple’s Arm chips at the price of a tiny performance penalty.
Despite its flaws, AI is slowly gaining widespread popularity for use, both by the general public and in specific scenarios, like EDA. Many companies are already using this technology to enhance their processes, and Nvidia is even building an industrial AI cloud in Germany to give European manufacturing companies a taste of AI computing power.
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