2 VCs and 3 funds investing in ai
Founder
Khosla Ventures
Check: $500K-$50M+ (across seed fund and main fund)
Explicitly optimizes for ~70% failure rates to back 'black swan' outcomes. Actively seeks opportunities that appear 'crazy' to most of the market. Capital-intensive, science-heavy bets. Believes fusion and superhot geothermal will be primary energy sources by mid-2030s. Bets on the future being radically different from the present. Co-founded Sun Microsystems. Famous for saying 'expertise is the enemy of imagination' — believes experts are often the worst at predicting disruption in their own fields because they're anchored to existing paradigms. Has been one of the most aggressive climate tech investors, putting billions into energy transition companies. Views AI as the most transformative technology in history, predicting it will replace 80% of jobs in 80% of occupations within decades. Runs both a seed fund (for earlier, riskier bets) and a main fund (for larger investments). Willing to lose money on most investments if the winners are transformational.
Venture Partner
Benchmark
Check: $5M-$15M
Sarah's investing worldview is built on a few interlocking beliefs: (1) The best consumer companies create compounding engagement loops where users do MORE over time, not less. She formalized this into the Hierarchy of Engagement framework: first get users to a 'core action,' then create 'accruing benefits' and 'mounting loss' to retain them, then achieve self-perpetuation through network effects. (2) For marketplaces, aggregate GMV is a vanity metric and a red herring. What matters is 'Happy GMV' — the portion of transactions where both buyer and seller had an experience good enough to drive retention. Happiness, not scale, is your moat. No matter how large an incumbent, they are vulnerable to a new entrant that makes buyers and sellers happier. (3) She prefers founders who start in a 'thimble' of a market — a small, constrained market adjacent to very large ones — and expand outward, rather than going after a big market from day one. (4) In AI, she believes the next wave of consumer AI will be social, not solo. AI avatars, chatbots, and social AI products will win over single-player tools. (5) For B2B AI, she coined 'sell work, not software' — rather than selling a 15% productivity improvement via software, AI startups should sell the completed work itself, delivering a 95% improvement. Incumbents are stuck selling software; startups can leapfrog them. (6) She believes markets have their own physics — 'you can't change those physics, regardless of how great the founder is.'