Ex-Greylock GP Sarah Guo announces Conviction Partners, her new AI fund

Venture capital is subject to cycles of hype, like the funding glut for Web3 last year and for artificial intelligence in the late 2010s. Now AI has come back into the zeitgeist , but venture capitalist Sarah Guo is convinced the hype is here to stay, so much so that she’s betting her new venture capital fund on that bet.

Guo on Tuesday announced the first closing of an initial $101 million fund for his new investment firm Conviction Partners. After spending nine years at Greylock, where she rose through the ranks to become the Silicon Valley company’s second female general partner, Guo left the company in June. With Conviction, it plans to invest in AI startups up to the Series A stage with checks worth between $1 million and $10 million. Guo is starting out as a solo investor, but plans to build a team around her suited to the nature of AI research.

For example, she recruited a visiting scholar to conduct research on AI and says she plans to hire more academics who could create new models and collaborate on ideas with startups Conviction invests in. a venture capital firm thinks it belongs at home and out,” she said Forbes in an interview. She pointed out that for generalist companies, hiring a team of AI researchers “doesn’t make sense.”

Guo grew up in Wisconsin as the daughter of Chinese immigrants who worked at Bell Labs before becoming tech entrepreneurs. She immersed herself in technology as a teenager, creating a website for her parents’ company. After graduating from the University of Pennsylvania, she worked for two years at broadband networking startup Casa Systems and in technology investment banking at Goldman Sachs. She joined Greylock in 2013 and credits the generalist company for giving her access to investments in spaces such as health tech and crypto.

But it was above all the AI ​​that stayed with her. She says she seriously considered leaving Greylock to start a business with Google Brain co-founder Andrew Ng in 2016 (also the year she was named to Forbes‘ List of 30 under 30 for venture capital). Yet, like Web3 last year, AI had its own VC hype cycle that died out once the technology and revenue proved to be growing too slowly. “A couple of very smart investors invited me to dinner in 2018, in the depths of disillusion [about AI], what I was wrong about robots and natural language,” she said. “I admitted with shame that the underlying technology wasn’t quite there.”

Now, recent rapid technical breakthroughs from companies like Hugging Face and Stability AI indicate that the pace of research is progressing on an exponential curve, Guo says. Instead of blockchain-based Web3, Guo believes the fundamental technology for the coming years is AI. She says she left Greylock to invest in this type of technology, in line with “the classic startup story of wanting to do something really different – often times it’s a lot easier to do from scratch. “.

Guo says her fund took just 10 weeks to raise and includes both institutional investors like university endowments (though she said she can’t name names) and about 50 founders and executives who are bullish on AI. She considers herself lucky to have raised the fund during a downturn, as it gives her access to higher quality companies at less inflated prices. “It would be really problematic to start a venture capital fund at the height of the bull market,” she says. “Capital was incredibly plentiful and that affected the actual quality of investing and the quality of decision-making.”

Conviction Partners will likely make a maximum of 20 investments in startups that are building with AI from the ground up. “To do that, you have to design a business differently: the talent you hire is different, and the challenges to be solved in the product are different,” Guo said. For example, these companies will need to spend significantly more on IT costs than incumbent software giants that rely on infrastructure like Amazon Web Services.

“There are a lot of smart investors I respect who say, ‘it’s a hammer looking for a nail’ or ‘no machine learning company I’ve ever invested in has made any money'” , Guo said. “But they are wrong this time. A lot of things don’t work until they work.