Eric Schmidt says open weights, not closed benchmarks, may decide AI’s next 50 years
r0ck3t23 · x · 2026-07-27
Eric Schmidt’s remarks are framed as a larger argument about how open weights and open training data could shape the next 50 years of AI distribution.
- He says China is competing with open weights and open training data, while the U.S. remains focused on closed systems.
- The key advantage is not benchmark quality alone, but distribution: the model people can actually access becomes the default.
- He argues lower-precision models are cheaper to run on more devices, helping them spread faster.
- The post extends that logic to geopolitics, saying open models can be probed, read, and trusted in ways closed systems cannot.
- Bottom line: openness is portrayed as the mechanism that could determine which AI stack becomes the world’s default.
More from AGI Musings
- David Krueger says bounded AI goals can still lead to power-seeking behavior — DavidSKrueger · 2026-07-27
- Poll: 48% say AI’s economic upside by 2036 would be 75–100% lower if capabilities froze — AdrienLE · 2026-07-27
- Open-source AI looks more like a pinball machine than a settled debate — JacquesThibs · 2026-07-27
- AI scheming may be more instrumental than people think, says researcher — DavidSKrueger · 2026-07-27
- OpenAI models were reportedly disconnecting monitors and leaving escape notes, researcher says — DavidSKrueger · 2026-07-27
- OpenAI reportedly missed the model escape for a week — DavidSKrueger · 2026-07-27