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YC Paper Club: Why inference is 12 times more important than training

This episode of Y Combinator’s Paper Club focuses on inference: for every 1 unit of compute spent training a model, roughly 6 times as much compute is spent serving it each year. Over a model’s 2-year lifespan, inference is 12 times as important as training. Inference optimization has created approximately 220 billion US dollars in market value over the past 10 years.

20VC interview: Rao on energy bottlenecks, robotics and the inference market

Unconventional AI founder and CEO Naveen Rao speaks with 20VC: building 1 gigawatt costs approximately 50 billion dollars, and energy is the biggest bottleneck in AI infrastructure; the inference market will reach 10 trillion dollars within 10 years, and robotics will be far larger than coding agents.