Sep 21, 2026 · 23 min
Unconventional AI bets on new hardware to break the energy wall
Naveen Rao: 4D Computing, AI's Energy Wall & Beating Biology
As conventional AI systems demand ever more energy, Naveen Rao argues that changing the underlying computing architecture may be unavoidable.
- 1Unconventional AI is developing time-varying, dynamical-systems hardware that departs from conventional matrix multiplication.
- 2The company aims to turn an early prototype into a full data-center rack within roughly two years.
- 3Porting existing models requires substantial model-layer work, making migration effort a central tradeoff alongside performance gains.
Don't miss
Rao explains how Unconventional AI replaces conventional matrix-multiplication framing with time-varying computation based on states and transitions.
The brief
Naveen Rao, the CEO of Unconventional AI, argues that AI’s energy demands call for more than incremental hardware improvements: the computational substrate itself may need to change.
Unconventional AI is targeting a full data-center rack within roughly two years, with tokens entering and leaving over a network while the underlying computation works differently.
Rao describes a time-varying architecture that moves beyond conventional matrix multiplication, treating each step as a current state interacting with a transition matrix.
The approach can support existing models, but migration requires substantial compute and work at the model layer, creating a direct tradeoff between performance gains and compatibility.
The company’s hardest organizational problem may be as unusual as its hardware: bringing dynamical-systems theorists together with experienced chip designers.
Featuring
Chamath Palihapitiya
Intel CorporationListen to the full episode and explore every guest, topic, and moment on PodLume.