Japanese Startup Turing Inc Secures AMD Backing to Challenge Nvidia in Self-Driving Race

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Turing Inc, a five-year-old Japanese self-driving startup, has secured investment from AMD Ventures and shifted 10% of its AI training to AMD chips. The move aims to reduce costs and diversify supply chains as the company targets consumer cars and robotaxis by 2028, positioning itself as a cost-effective alternative in Japan's autonomous vehicle race.

Turing Inc Shifts AI Training Workloads to AMD Chips

Turing Inc, a Japanese self-driving startup founded five years ago, has added AMD Ventures to its investor roster and begun migrating portions of its AI training workloads away from Nvidia hardware

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. The Tokyo-based company now runs approximately 10% of its AI training on AMD graphics processing units, marking a strategic effort to diversify away from Nvidia while pursuing cost reduction in the capital-intensive autonomous vehicle systems market

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The decision to adopt AMD's AI accelerators stems from two primary factors: supply chain resilience and lower compute resources costs. AMD, headquartered in Santa Clara near Nvidia, offered Turing Inc the opportunity to secure a second supplier while accessing more affordable AI hardware

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. For a smaller player in the self-driving space, cheaper compute represents one of the few levers available to compete against better-funded rivals.

AMD Ventures Investment Fuels Expansion Plans

The AMD Ventures investment forms part of a $79 million equity and debt extension to Turing's Series A funding round, which valued the company at approximately $600 million

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. While neither party disclosed the specific investment amount, the backing signals AMD's broader strategy to gain ground in autonomous driving. The chip maker recently backed UK-based Wayve Technologies as well, demonstrating a pattern of supporting self-driving firms seeking alternatives to Nvidia's dominant position

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"We've made notable progress with the technology. There's a lot more we can show to potential auto partners," said Masato Morishima, Turing's chief financial officer. "We need to focus our efforts more on the business aspect"

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. The funding round remains modest compared to what rivals across Asia have raised, but Turing executives view their cost-effective approach as a competitive advantage rather than a disadvantage.

Consumer Cars and Robotaxis Targeted for 2028 Launch

Source: Japan Times

Source: Japan Times

Turing Inc aims to deploy its software in consumer cars and robotaxis by 2028, entering a market where competition is already heating up

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. A partnership between Nissan, Wayve, and Uber plans to launch a pilot robotaxi service in Tokyo by the end of this year, while US firm Nuro and others are testing on Japanese streets

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The company has conducted test drives starting with a 30-minute journey outside Tokyo last year, subsequently replicating experiments in more congested urban areas across Japan

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. Morishima downplayed concerns about entering the market later than competitors, noting that new car models typically follow three-to-five-year product cycles. "We may look like we're late to the game, but we'll make it work and we'll do so more cost-effectively," he stated

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Japan's Automotive Industry Stakes Drive National Ambitions

For Turing co-founder and CEO Issei Yamamoto, the venture carries implications beyond one company's success. "Autos is a very important industry in Japan. If Japan ends up losing this industry, we won't have anything to export. And autonomous driving will be a key factor for the future," Yamamoto explained

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. He positioned Turing as having "the most advanced tech in this field, at least here in Japan"

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The shift to AMD chips represents more than a technical decision—it reflects a broader industry hunt for alternatives to Nvidia's near-monopoly in AI hardware for autonomous vehicles. Every design win AMD secures from Nvidia strengthens its position in the self-driving sector, while giving startups like Turing Inc leverage to negotiate better terms and maintain operational flexibility as they scale toward commercial deployment.

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