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Canadian AI computing startup Tenstorrent and LG partner to build chips

Published 05/30/2023, 09:04 AM
Updated 05/30/2023, 09:06 AM
© Reuters. FILE PHOTO: Jim Keller, CEO of Canadian AI computing startup Tenstorrent, poses for a photo at the company's office in Santa Clara, California, U.S. in this picture taken in 2022.   Tenstorrent/Handout via REUTERS
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By Jane Lanhee Lee

OAKLAND, California (Reuters) - Canadian AI computer design startup Tenstorrent said on Tuesday it was partnering with South Korea's consumer electronics firm LG Electronics Inc to build chips that power smart TVs, automotive products and data centers.

Tenstorrent, started in 2016, designs computers to train and run artificial intelligence models and works on both the software and hardware, CEO Jim Keller said in an interview. Keller is an engineer best known for his pioneering work in designing chips at Apple Inc (NASDAQ:AAPL), Tesla (NASDAQ:TSLA) Inc , and chipmaker Advanced Micro Devices (NASDAQ:AMD) Inc .

Keller, an early investor in Tenstorrent, took the helm in 2023. The company, already worth $1 billion according to data firm PitchBook, has not revealed any of its customers until now.

LG will initially use Tenstorrent's AI chip blueprint to design its own chips, but the partnership is more strategic, said David Bennett, Tenstorrent's chief customer officer.

"What we're looking at is also some of the technology that LG has developed. Could it not be something that we use either in our own products or potentially with other future customers."

Tenstorrent has also designed a processor chip using RISC-V, a relatively new open standard chip architecture competing with Arm Ltd's Arm architecture. While many chip startups focus on one type of chip, Keller said his team was developing both the AI chip and processor as they will need to work closely together to handle the fast-changing AI models.

© Reuters. FILE PHOTO: Jim Keller, CEO of Canadian AI computing startup Tenstorrent, poses for a photo at the company's office in Santa Clara, California, U.S. in this picture taken in 2022.   Tenstorrent/Handout via REUTERS

"We have to aim at the whole thing. ... It's quite early. And it was built on the available components," said Keller about today's AI and AI hardware landscape.

"In the last five years people learned so much about how this works and made real progress. But it doesn't look like we're anywhere close to 'this is the right way to do it, the best way to do it, or the final thing.'"

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