AI bigshot Andrew Ng's AI Fund, a startup incubator that supports small teams of experts to solve critical problems using AI, has raised over $120 million for its second tranche. intends to
The AI Fund's second fund, AI Venture Fund II, has so far raised $69.75 million from 13 partners — with about $50 million remaining to invest, according to filings with the SEC. AI Fund's PR declined to comment.
Ng, founder of the Google Brain Deep Learning Project, co-founder of Coursera, and recent Amazon board appointee, was one of the most recognizable names in the AI community when he became Baidu's chief scientist in 2014. He left Baidu in 2017. Jumpstart several AI projects, including the Deeplearning.ai course and Landing AI, a startup developing AI tools aimed at manufacturing companies.
Ng launched the AI Fund in 2018 with $175 million, serving as the incubator's GP and leading it. (On the aforementioned SEC filing, he is named as the “managing member of the general partner” for AI Venture Fund II.) The idea was to fund the seed and Series A stages of the company's lifecycle, making Allowing teams to operate in relative stealth until they're ready—and connecting them to Ng's vast professional network.
Greylock Partners, New Enterprise Associates, Sequoia Capital and SoftBank Group were among the early backers of the AI Fund. Crunchbase lists 38 portfolio companies, including AI observation platform WhyLabs, Ng's own Landing AI, and AI app building tool Beeston.
At $120 million, AI Venture Fund II will be significantly smaller than the first AI Fund tranche. Still, that's double what Ng had reportedly hoped to raise — $50 million — for the follow-up AI fund.
Take this as another possible sign that the AI bubble — especially the buzzy AI segment within it — may be bursting.
Pitchbook recently reported that, for two consecutive quarters, early-stage generative AI dealmaking has declined, falling 76% from its Q3 2023 peak. VC deal value for pre-seed and seed-stage deals fell to $122.9 million in Q1 2024, down from a high of $517.7 million in Q3.
Reluctance in enterprise may be to blame.
In a pair of recent surveys by the Boston Consulting Group, nearly half of respondents — all C-suite executives — said they don't expect productivity AI to yield substantial productivity gains and are concerned about the potential for errors. and compromising data generated by generative AI-powered tools. As my colleague Ron Miller wrote last week, enterprises are finding that implementing generative AI at scale is more difficult than they once assumed — and that executives should be careful. are