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Naveen Rao: 4D Computing, AI's Energy Wall & Beating Biology

Technology

グローバル

September 22, 2026に開始

(0:00) Welcome Naveen Rao (4:45) Is energy really the problem? The cost of a token, power contracts & the gap to close (10:24) Cutting out the middleman: abstractions, dynamical systems & a new kind of machine (19:46) Chamath joins: the path to product, porting existing models & building the team Thanks to our partners for making this possible! IREN is a vertically integrated AI Cloud platform, delivering data centers, compute and software for AI training and inference. https://iren.com/ Orac...

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Naveen Rao: 4D Computing, AI's Energy Wall & Beating Biology

All-In Podcast (United States) | Sep 21, 2026

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CLAIM 投稿者： admin • Sep 22, 2026

Cutting out the middleman in AI development will lead to more innovation and faster deployment of new technologies.

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CLAIM 投稿者： admin • Sep 22, 2026

Investment in AI infrastructure must prioritize energy-efficient technologies to address the upcoming energy wall.

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CLAIM 投稿者： admin • Sep 22, 2026

4D computing will revolutionize data processing by providing unprecedented levels of computational efficiency.

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CLAIM 投稿者： admin • Sep 22, 2026

The race to beat biology in AI could lead to harmful consequences if ethical boundaries are not established.

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CLAIM 投稿者： admin • Sep 22, 2026

Dynamic systems in AI will enable more responsive and adaptive technologies that can meet real-time needs.

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CLAIM 投稿者： admin • Sep 22, 2026

The development of new AI models should focus on enhancing human capabilities rather than replacing them.

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CLAIM 投稿者： admin • Sep 22, 2026

Tokenization in AI ecosystems could create unnecessary financial barriers that limit access to technology.

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CLAIM 投稿者： admin • Sep 22, 2026

The collaboration between data centers and AI developers is crucial for the future of scalable AI solutions.

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CLAIM 投稿者： admin • Sep 22, 2026

The current energy demands of AI technologies are unsustainable and will hinder future advancements.

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CLAIM 投稿者： admin • Sep 22, 2026

AI training and inference should be hosted in vertically integrated platforms to maximize efficiency and reduce costs.

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