MIPS shifts strategy toward robots and designing chips

Reuters
03-04
MIPS shifts strategy toward robots and designing chips

By Stephen Nellis

March 4 (Reuters) - MIPS, a decades-old Silicon Valley company that once competed directly with Arm Holdings O9Ty.F in providing a computing architecture, said on Tuesday it was shifting strategies to design a suite of chips for artificial intelligence-enabled robots.

MIPS traces its roots back to the mid-1980s, when Stanford University Professor John Hennessey co-founded the firm to commercialize a nimbler way to carry out computing tasks, called a computing architecture.

MIPS chips were known for processing data very quickly in specialized applications like networking gear and self-driving cars.

The company traded through a succession of owners before licensing some of its technology for use in China and entering bankruptcy.

But MIPS emerged from bankruptcy in 2021 and announced that it would focus using the RISC-V computing architecture, an open alternative to Arm, and won customers such as autonomous driving firm Mobileye MBLY.O. Along the way, MIPS has always sold intellectual property to other firms who designed complete chips.

MIPS said Tuesday that it is shifting strategies and will design its own chips, though it will still license technology as well. The company will focus on three key areas of robotics - chips that do sensing, chips that calculate which action for a robot to take next and chips that can control a robot's motors and actuators.

Sameer Wasson, chief executive of MIPS, said those markets are expected to grow as recent advances in AI are applied to new areas such as humanoid robots. To win that business, it is better to show up with a working chip than a PowerPoint presentation, Wasson said, even if the end goal is a licensing deal.

"It doesn't mean MIPS is going to overnight turn into a silicon company. I don't see that," Wasson told Reuters. "But I think we've got to give the ecosystem confidence that this can be done."

Wasson said MIPS will initially focus on the automotive industry.

"I expect this technology to be in a car towards the end of '27 and start to hit volume in the '28 timeframe," Wasson said, without naming specific customers.

(Reporting by Stephen Nellis in San Francisco; Editing by Jamie Freed)

((Stephen.Nellis@thomsonreuters.com;))

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