Quote · Moonshots with Peter Diamandis
Michael Kratsios on the New Golden Age of American Science | EP #276
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Open Source vs. Closed Source AI: The China Problem
At 21:02 · chapter starts 19:50
Peter flags a geopolitical issue that's dominating Washington: open-source AI and the risk that China uses it as an instrument of global influence. Kratsios is unusually candid: the US leads in closed models, but its open-source ecosystem is underperforming, and cash-strapped American entrepreneurs cannot be blamed for using cheaper Chinese models — because right now, Chinese models are cheaper. [1] — Michael Kratsios "Kratsios makes a blunt admission: right now, the cheapest open-source AI model available to bootstrapped American entrepreneurs is Chinese.…" 19:55 His response is the American AI Exports Program: a Commerce-led, whole-of-government effort to package the best American chips (NVIDIA, AMD), models, and applications into a complete, turnkey AI stack for foreign governments, backed by Export-Import Bank and Development Finance Corporation financing. The explicit motivation is avoiding a repeat of the Huawei telecom playbook, where a subsidized Chinese stack was rapidly proliferated across the Global South before America could respond. This time, Kratsios argues, America has the advantage — its chip lead over Chinese competitors is widening year over year due to EUV export controls.
Kratsios makes a blunt admission: right now, the cheapest open-source AI model available to bootstrapped American entrepreneurs is Chinese. The US has to cultivate its own vibrant open-source ecosystem, and the administration's American AI Exports Program is the first step toward making the American AI stack the world's default.
Rather than letting China replicate the Huawei telecom playbook with AI, the US launched a program at Commerce to bundle the best American chips, models, and applications into a turnkey AI stack for foreign governments. Export-Import Bank and Development Finance Corporation financing makes it economically viable for developing nations.