AI startup Thinking Machines clinches capital and a major chip supply deal from Nvidia

March 10 (Reuters) - AI startup Thinking Machines Lab said on Tuesday it has struck a multi-year partnership with Nvidia that will see it ‌receive a significant investment and procure at least one gigawatt of ‌the chipmaker's next-generation processors.

Financial terms of the deal were not disclosed.

Under the agreement, Thinking Machines - founded last ​year by former OpenAI Chief Technology Officer Mira Murati - will deploy Nvidia's upcoming Vera Rubin systems starting early next year. The computing power will primarily be used to train the startup's artificial intelligence models.

Industry executives have said 1 gigawatt of computing ‌power, enough to power roughly ⁠750,000 U.S. homes, can cost around $50 billion.

The deal will help Thinking Machines compete with larger rivals in building powerful AI systems, ⁠and underscores the industry's eagerness to scale computing capacity.

Thinking Machines quickly became one of Silicon Valley's most closely watched AI startups after raising about $2 billion in a seed funding ​round ​led by Andreessen Horowitz that valued the ​company at $12 billion. Nvidia was also ‌an investor in the round.

The startup has recently been seeking to raise more in a new funding round that could value it at tens of billions of dollars, sources told Reuters earlier.

The company has recently seen several departures, including co-founder and former Chief Technology Officer Barret Zoph and co-founder Luke Metz, who both ‌returned to their former employer OpenAI amid fierce ​competition for AI talent.

The partnership also highlights Nvidia’s ​growing role as a financier ​of the startups that rely on its AI chips.

It has made ‌a recent $30 billion investment in OpenAI ​and invested $10 billion in Anthropic, while ​also supplying the graphics processing units (GPUs) used to train and run their models, a dynamic that some industry analysts say creates a circular flow ​of capital and computing ‌resources. That in turn has given rise to comparisons with the late ​1990s tech bubble.

(Reporting by Krystal Hu in San Francisco; Additional reporting ​by Deepa Seetharaman; Editing by Edwina Gibbs)