Moonshots

Peter Diamandis × Cathie Wood × Salim Ismail × Dave Blundin × Dr. Alexander Wissner-Gross

Cathie Wood argues that robotics, energy storage, AI, blockchain, and multi-omic sequencing could lift real global GDP growth above 7% as falling costs unlock explosive unit demand and convert household labor into measured commerce.The thesis concentrates capital around power, open-source AI, robotaxis, and convergent platforms, with $10 trillion of global power investment and Tesla’s potential $0.20-per-mile rides as catalysts, while China’s open-source lead and legacy infrastructure remain key uncertainties.

Peter Diamandis × Salim Ismail × Emad Mostaque × Eric Pulier

NVIDIA’s first U.S.-made Blackwell wafer marks a sovereignty milestone, but advanced packaging still returns to Taiwan, leaving fabrication expertise and capacity as the critical supply-chain bottleneck through the 2028 timeline.The panel’s 2026-to-2029 AGI window, 500,000-to-1-million-chip clusters, and humanoid price points signal accelerating capital intensity, while persuasion risks, unsettled household reliability, debt, and quantum’s nonlinear security implications remain key uncertainties.

Peter Diamandis × Alexander Wissner-Gross × Dave Blundin

The AI race is becoming an energy race as China targets nuclear leadership by 2030 and produced roughly 700 GW of solar panels in 2024, while US licensing takes 10–12 years.Frontier models could become winner-take-all through self-improvement, while Cursor’s $500 million ARR and AI startup revenue demonstrate unusually capital-light economics; generation, distribution, storage, and regulation remain key constraints.

Salim Ismail × Dave Blundin × Peter Diamandis

Michael Saylor’s doubled “42/42” plan could fund $84 billion of Bitcoin purchases, while corporate buying already equals 3.3 times 2025’s new supply.Saudi Arabia is combining Middle Eastern capital with US technology through Amazon and HUMAIN’s $5 billion AI zone and Nvidia’s 18,000 GB300 Blackwell chips.The investable battleground spans concentrated AI leadership, debt-financed compute, TSMC exposure, software labor displacement, and robotics deadlines including Archer’s LA28 air-taxi commitment.