Bill Maris

After Google Ventures, Bill Maris returned to investing with Section 32, which he introduced as having raised $150 million. He says a smaller fund lets him be selective about companies and hires, while financial return is the only measurable objective; his central venture call is that funds below $750 million structurally outperform megafunds. He cites top-decile DPI of 4.76x below $750 million versus 2.42x above $1 billion; smaller funds produced 95% of top-decile performers, and DPI is, to the extent it can be measured, the only venture metric that counts in his view.

Fund-size arithmetic makes the megafund hurdle almost market-sized just to return capital. At 10% ownership, a $500 million fund needs $5 billion of exits to return capital and $15 billion for 3x, while a $7 billion fund needs $210 billion—more than total venture-backed M&A and IPO exit value in most years. Maris says Section 32’s six funds average roughly $400 million and all perform in their top decile.

Google’s war chest could turn tokens into a weapon and make current AI economics “go super critical.” Maris asks what happens if Gemini offers a basically identical product at 80% less: companies would have reason to switch, and OpenAI and Anthropic would face brutal compression. The companies may burn investor cash Uber-style to buy market share, but “at some point, you got to have cash generation.”

The late-stage AI bounty remains paper wealth until somebody buys the stock, and Maris asks whether retail, 401(k), or passive capital will ultimately be that buyer. He objects to companies claiming public benefit while reserving early value for elite investors and later relying on exceptions that make passive funds and ETFs pick them up: “Don’t say you’re doing this for the benefit of humanity and do the other thing.” A putative $100 billion gain still requires a public-market buyer to justify the valuation through discounted future cash flows; lockups may delay that verdict.

AI is only at the “Atari command-line stage,” so Maris would fund enabling layers rather than another large model. Using Zork’s brittle commands as the analogy, he expects gaming’s leap to photorealistic immersion to compress into roughly five years for AI, reaching the “PlayStation 10 stage.” The opportunities are memory, consistency, ambient computing, controllers, physics engines, GPUs, and other machinery.

Computational biology could unlock healthcare’s enormous TAM, but biology and regulation keep the curve from becoming instantly exponential. Maris is less involved in life sciences than before but remains interested in the area; discovering a compound is “like 5% of the work,” with titration, safety, and human trials remaining. A realistic in-silico simulation of a human cell could accelerate progress. He also warns that gutting CDC and NIH support, an “anti-science vibe,” and pressure on H-1B holders are pushing scientific mindshare and people elsewhere.

A panelist argues that the venture incentive stack rewards asset gathering even when fund returns are mediocre. A $5 billion fund returning 1.01x can claim 75th-percentile status and its GP can out-earn a $500 million fund returning 3x, while giant checks inflate a researcher’s $100 million startup toward a $4 billion valuation. The panelist concludes that late-stage sniping is not durable and “the pendulum will swing back.”

🔗 Original source & video: Bill Maris: How Google Could Crush AI Competitors, Why Small Funds Win, and AI’s Atari Stage