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Back to 20VC: Why Robotics Will be 100x Bigger than Coding Agents | Inference Will Be a $10TRN Market: What No One Sees | Why Software Investors are F***** Today with Naveen Rao, Unconventional, with Naveen Rao.

Have Physical Efficiency Gains in Chips Stopped?

Naveen Rao says physical efficiency gains in chips have largely stopped. The last few generations of GPUs and other chips show little new efficiency at the physical layer. Moore's law and Dennard scaling made devices smaller, denser, and more efficient, and the innovations have largely stopped.

He splits how a computer is built into three levels. The physical level is the energy required to move a bit between two states, the way a phone's weight changes the energy needed to flip between zero and one. Most efficiency gains over the last several years, and over several generations, have come from the next layer, computing architecture, by moving to smaller data types: 32-bit, then 16-bit, then 8-bit, then 4-bit. Fewer bits means less data moved and less computation. The level above that is still not well exploited. Mosaic started work on enforcing locality and cutting data movement at the model level.

Five or six years ago the model was not the primary driver of compute. Compute was a general-purpose tool for websites and databases. A computer treated as a physical device built to deliver intelligence can be co-designed from the model to the architecture to the physical layer. The remaining advantage sits in the top layers, not only in the physical layer.

Grokipedia·Naveen Rao

Transcript

20VC: Why Robotics Will be 100x Bigger than Coding Agents | Inference Will Be a $10TRN Market: What No One Sees | Why Software Investors are F***** Today with Naveen Rao, Unconventional ·

The Twenty Minute VC: Venture Capital | Startup Funding | The Pitch

More from this episode

  1. Should I Trust AI Agent Decisions Yet?Naveen Rao says people should not trust AI agent decisions as much as human decisions in a lot of cases just yet.
  2. Why Are Big AI Model Companies a Data Problem?Naveen Rao says the big AI model companies are largely a data problem. Most of their capabilities have not come from advances in the model itself.
  3. Is Reinforcement Learning Less Efficient Per Dollar?Naveen Rao says reinforcement learning is more inefficient.
  4. Are Pure Software Investors in Trouble?Naveen Rao thinks hardware is the place to be over the next 10 years and is confident a pure software investor is in trouble.
  5. Why Does AI Leave Developer Budgets About the Same?Naveen Rao says the share of developer salary that shifts to coding tools may stay roughly stable, because training people to judge good code is the hard part.
  6. How Much Bigger Will Robotics Be Than Coding Agents?Naveen Rao thinks robotics is going to be 100 times larger than agentic coding.
  7. What Did Naveen Rao Change His Mind About?Naveen Rao changed his mind in the last 12 months on the useful metric for progress in investing. Market validation is an old way of looking at it.
  8. How Did Naveen Rao Feel Meeting Steve Jurvetson?Naveen Rao walked into an early meeting with Steve Jurvetson nervous. He had heard Jurvetson was super smart and expected to be taken apart.
  9. Why Is Naveen Rao Excited About AI?Naveen Rao is personally pumped that AI is a tool and capability for asking much bigger questions about the universe.

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