While the mid 2010s were filled with massive financing rounds for companies looking to shift business models like Instacart, Uber, and others along those lines, today’s hottest sector is a more technical one: artificial intelligence.
That’s required a different approach to building companies. As tools become more and more powerful, and frameworks like TensorFlow become more robust, building a company centered around AI — and the big technical problems that either feed it or stem from it — are powering the next wave of potentially massive startups. That’s why Lu Zhang and Homan Yuen, two Stanford technical graduates, are raising a big fund based on their extensive technical experience to find companies that have that strong technology backbone that will become the next big startup.
The pair are raising $85 million for a new fund called Fusion Fund. Fusion Fund’s companies are going to be focused on connected industries, networking technology like communications protocols, data-rich AI products and some health and medical devices. That third bit — investing in AI — is what pretty much every fund is doing, though Yuen made it clear the company isn’t investing in just algorithms, which are eventually going to be a race to the bottom.
“We noticed there weren’t many venture capitalists focusing on technology companies and actually have technical backgrounds,” Yuen said. “We thought, that’s a good opportunity to help early stage companies that need different help, and advice, and connections.”
Zhang and Yuen are two technical founders that sold their companies and were looking to figure out what to do after that. In Zhang’s case, with a masters in material science, she was approached by investors to do a fund, while Yuen had known her at Stanford and ended up syncing up to work on the fund, he said. Zhang started the fund and raised the initial $17 million. The fund will be focused on seed-stage companies, looking to write checks between $500,000 and $1 million for companies with technical founders and a pretty difficult problem to solve that requires that expertise.
“We’re not funding science products, or expedition missions, we want clear vision in building a business on the technical advantages,” Yuen said. “Part of our thesis is, over the last five to ten years, we saw a lot of investment into business model innovation. We decided it was time to flip back to tech and infrastructure investing.”
On that front, a lot of these areas are going to get a lot more interesting as time goes on. The tech industry is in the early stages of 5G development and rollout, and once there are more rigorous standards, there will likely be a lot of activity in that space, such as new connection protocols. There’s also a strong security element to that, and all of this requires heavy technical expertise to build something pretty defensible, Yuen said.
“When I raised the first fund in 2015, we were one of few funds to focus on supporting truly technical founders,” Zhang said. We felt our entrepreneur and technical backgrounds could be an asset as they began their journeys.”
But if you want just one example — and this is one where Yuen is sitting on the sidelines for now — on how technical these problems are getting, you can look at the rapid emergence of the custom AI chip space. That problem requires an expertise in rethinking the actual silicon where operations happen to more efficiently tackle machine learning problems, whether that’s focusing on speed, lowering the power consumption, reducing the overall space the processors take up, or getting the cost down to something more reasonable than a bleeding-edge GPU. Right now the space has a ton of VC money flowing into it, and given the size of the checks Yuen is looking to write, it’s an area where the firm has to be more thoughtful about the companies it picks.
This is actually Fusion Fund’s second fund, as it previously went under a different name. Zhang started and raised the first $17 million fund when it was previously called NewGen capital. The firm has backed 36 seed-stage companies in companies like TVision Insights, Stratifyd, Paperspace, MissionBio, and Paradromics.
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