Energy-gated compute means centralization by default
Sponsored Session: Powering PyTorch: Decentralized Training for an Energy-Hungry Future - Greg Osuri (PyTorch)
“If compute access is functionally gated by energy, we risk centralization by default — only a few players can pay the bill. So here’s the constraint in one line: AI demand is exponential; our energy response can’t be linear. We need architectures that use energy smarter — spreading load, lifting utilization, and collocating compute with abundant, cheaper renewables.” — 00:04:26
Context: Framing why energy must be treated as a first-class constraint in the training stack; “if we don’t adapt, energy — not algorithms — will be the bottleneck for AI” ([00:19:55]).