Eric Schmidt

Peter Diamandis × Eric Schmidt × Dave Blundin

AI may have delivered only 10–15% of its eventual impact, while software development has shifted from assisted coding to autonomous orchestration within months.citeturn0search0 Recursive self-improvement remains two to three years away in San Francisco’s consensus but does not yet work, while a projected 92-gigawatt US power shortfall by 2030 makes electricity the key constraint to monitor.

Peter Diamandis × Eric Schmidt × Dave Blundin

Eric Schmidt expects America to retain the top-end AGI lead while China embeds AI everywhere and dominates inexpensive physical systems, including Unitree’s $6,000 R1; electricity, not chips, may become America’s binding constraint.Falling compute costs and open Chinese models weaken static controls and could establish global standards through price, while biology remains the catalyst most likely to force coordinated policy and a major test of startup defensibility.

Peter Diamandis × Fei-Fei Li × Eric Schmidt

Schmidt puts true ASI beyond the industry’s “San Francisco consensus” of three to four years, even as compounding gains could pull the date forward.He defines it as intelligence equal to “the sum of everyone” or better than all humans, but today’s systems cannot quickly feed newly learned reasoning back into themselves; creative superintelligence may…

Eric Schmidt

Schmidt now expects China’s chip constraints and shallower capital markets to favor ubiquitous AI deployment, while open weights and training data could make model distribution a geopolitical contest that America must not concede.Cheap autonomous drones are overturning defense economics, with a $4,000-$5,000 aircraft carrying a 2-kilogram payload able to destroy a $30 million tank, raising unresolved questions about deterrence and escalation.

Peter Diamandis × Eric Schmidt × Dave Blundin

AI’s next constraint may be electricity rather than chips, with Eric Schmidt estimating the US needs another 92 GW as reasoning and test-time compute consume efficiency gains.His aggressive timeline points to world-class AI mathematicians within one year, programmers within one or two, and digital superintelligence within 10, while enterprise software, jobs, China, and AI security remain unresolved.