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Back to Jensen Huang | Does AI Revenue Justify Capex, '27 AI Bottlenecks, Singularity, Open vs Closed & more, with Jensen Huang & Brad Gerstner.

Why Put Nvidia Computers on Starship?

Jensen Huang says NVIDIA's engineers and Elon Musk's team are designing a server that works in space and on Earth. Musk wants computing and physical buildouts in the same place, and Huang says nobody knows energy better. The case is not that a launch is cheap. NVIDIA's performance per unit of energy makes the return on the computer high enough that the launch cost is a small share of it. Low-cost computing does not belong in orbit. High-value computing does, and he calls this the highest-value system in the history of computing.

The machine also has to stay useful after it is up there. Huang says NVIDIA is the only hardware company that still ships new software, including new algorithms, for a chip a customer bought eight years ago. A satellite can keep receiving those updates for as long as it flies. The compute is fungible. NVIDIA works with every closed-model company, runs every open model, and already has thousands of startups and enterprises as customers, so the plan is not an empty satellite. He calls that mix the right payload for SpaceX.

Transcript

Jensen Huang | Does AI Revenue Justify Capex, '27 AI Bottlenecks, Singularity, Open vs Closed & more ·

BG2Pod with Brad Gerstner and Bill Gurley

More from this episode

  1. Why Did Jensen Huang's Parents Fly in Overnight?Jensen Huang says five of the six people on the medal stage were born outside the United States. He received the National Medal of Science for NVIDIA.
  2. Why Will the Cost of Intelligence Keep Falling?Jensen Huang says the last year unlocked knowledge, working memory, and tool use.
  3. Why Didn't Keynes's 15-hour Week Happen?Jensen Huang says the hope of more free time is wrong. For most people, intelligence unlocks more opportunities, and ambitious people will pursue them.
  4. Did Jensen Huang Understate Physical Artificial Intelligence?Jensen Huang says he understated the $100 billion figure. The first six months already produced $10 billion in physical artificial intelligence.
  5. How Many Computers Does Physical AI Need?Jensen Huang says building a physical artificial intelligence platform takes three computers and three complete stacks, and he says it takes three robots as…
  6. Is AI Alignment a Forever Problem?Jensen Huang says alignment is a forever problem. Safety that depends on perfect alignment never arrives. The answer is containment.
  7. How Did Nvidia's Dollars Per Gigawatt More Than Double?Jensen Huang says Nvidia's market share is still increasing even though the company is already large and the share was already very high.
  8. Why Do Most AI Startups Use Open Models?Jensen Huang says the frontier labs are only part of NVIDIA's machines. He puts them at about a quarter of the compute, maybe 30 percent.
  9. Why Does Jensen Huang Expect Four Trillion a Year?Jensen Huang says that as the decade ends, yearly infrastructure build-out will probably land between three and four trillion dollars, closer to four than to…
  10. Why Can't Nvidia Fill Its Order Book?Jensen Huang says every large cloud, every neocloud, and every big manufacturer had already ordered, and so had the startups.
  11. Why Did Jensen Huang Call Specialization the Enemy?Jensen Huang says specialization is the enemy of fungibility and the enemy of durability.
  12. What Yearly Computing Build Would Not Surprise Jensen Huang?Jensen Huang says the world is running about a trillion dollars of information technology buildout each year.

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