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“While AI is digital in nature, the binding constraint is physical.” While many think of the race for AI dominance as who can develop the best model, that’s only one piece of the puzzle. Frontier models, data centers, leading-edge chips, energy sources, and digital networks all form the full stack of AI leadership—and any one of them could be a point of failure. CSIS’s Navin Girishankar, president of the CSIS Economic Security and Technology Department, and Joseph Majkut, director of the CSIS Energy Security and Climate Change program, join the podcast to discuss their new research on how to secure U.S. full stack leadership in AI, especially expanding energy production to power future AI needs.
Read CSIS’s latest research on full stack AI leadership here: https://www.csis.org/analysis/securing-full-stack-us-leadership-ai
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247247 ratings
“While AI is digital in nature, the binding constraint is physical.” While many think of the race for AI dominance as who can develop the best model, that’s only one piece of the puzzle. Frontier models, data centers, leading-edge chips, energy sources, and digital networks all form the full stack of AI leadership—and any one of them could be a point of failure. CSIS’s Navin Girishankar, president of the CSIS Economic Security and Technology Department, and Joseph Majkut, director of the CSIS Energy Security and Climate Change program, join the podcast to discuss their new research on how to secure U.S. full stack leadership in AI, especially expanding energy production to power future AI needs.
Read CSIS’s latest research on full stack AI leadership here: https://www.csis.org/analysis/securing-full-stack-us-leadership-ai
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