『Silicon Valley Venture Capitalists Double Down on AI and Quantum Computing Amidst Economic Challenges』のカバーアート

Silicon Valley Venture Capitalists Double Down on AI and Quantum Computing Amidst Economic Challenges

Silicon Valley Venture Capitalists Double Down on AI and Quantum Computing Amidst Economic Challenges

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 Silicon Valley venture capital firms are charging ahead into AI and quantum computing amid economic headwinds, with funding surges defying bubble fears. Lightspeed Venture Partners just raised $9 billion, a record haul, and led Resolve AI's Series A at a nominal $1 billion valuation despite its $4 million ARR, using a multi-stage structure for lower actual pricing, per AIbase reports. This reflects VC bets on AI ops tools like autonomous SRE, even as investors like Kindred Ventures' Steve Jang admit an AI bubble but call it fuel for innovation, drawing top talent from Google and Meta.

Quantum computing draws massive capital too. Global funding jumped 128% year-over-year in Q1 2025 to $1.25 billion, with governments pledging $10 billion by year's end, fueling a $72 billion market by 2035, according to AInvest. IonQ, backed by deep pockets with a $3.5 billion war chest, eyes 10,000 qubits by 2030, prioritizing scale over profits, while D-Wave hits 77.7% gross margins on near-term annealing tech.

Firms adapt to challenges by eyeing AI beyond chips. Diameter Capital Partners, managing $25 billion, scored on telco debt as AI shifts to data networks, signing $10 billion hyperscaler contracts, as Scott Goodwin told Goldman Sachs Exchanges podcast. Sapphire's Cathy Gao pushes enterprise workflow tools over gimmicky AI-for-X, warning robotics startups face heartbreak from lagging models.

No big climate tech or diversity shifts in latest news, but regulatory tailwinds like U.S. Quantum Initiative boost hybrids. Bubbles may pop, but VCs see endless cycles in infrastructure like GPUs and models.

These trends point to a future where Silicon Valley VC doubles down on capital-intensive deep tech, blending private risk with public funds, prioritizing execution in AI's long game over quick wins.

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