Tokyo-based generative AI start-up Sakana AI has received tens of millions of dollars of investment from AI chip giant Nvidia as part of a $137 million (£104m) funding round that values the small company at more than $1bn.
The investment makes Sakana, founded in July 2023 by two former Google engineers, the fastest company founded from scratch in Japan to reach “unicorn” or $1bn status, Nikkei reported.
It is one of the larger investments Nvidia has made in Japan’s growing AI industry, according to Bloomberg.
The Series A or early-stage funding round was led by New Enterprise Associates, Khosla Ventures and Lux Capital. Nikkei said Nvidia appeared to be the largest contributor.
The company said it will work with Nvidia on research, data centre access and “AI community-building” in Japan.
Nvidia chief executive Jensen Huang said he was impressed with the way Sakana has been developing small-scale generative AI products tailored for the Japanese environment.
“Countries are embracing sovereign AI to capture and codify their data, culture and language through their own unique large language models,” he said in a statement.
“The team at Sakana AI is helping spur the democratisation of AI in Japan.”
Nvidia will become a large shareholder in Sakana after the funding round, which is valued in all at around 20bn yen ($137m, £104m), Nikkei said.
Sakana is taking a different approach to generative AI models compared to competitors such as OpenAI, with smaller models that require less training data and can reach a high level of intelligence with less drain on power-intensive computing infrastructure.
The company, previously valued at around $200m, says it applies principles of natural selection to the way its AI models process language and images in order to reduce the amount of human input required.
In January Sakana raised 4.5bn yen from NTT Group, Sony Group, Khosla Ventures and others.
Nvidia’s first Japanese investment was AI start-up Abeja in 2017.
Some 20 of the 39 companies it invested in worldwide in 2023 were related to generative AI.
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