AI Weekly Malaysia

SF Compute's Evan Conrad explains the company's shift from subleasing a GPU cluster to operating much of a cloud so it can physically settle traded GPU-hour contracts, not just cash-settle against an index. The episode details how contracts encode constraints like interruptibility, storage-recovery speed, GPU generation, networking, and software configuration, and why SF Compute matches orders across variants rather than waiting for fully interchangeable clusters. It was recorded at AI Engineer NYC's new Compute Trading track.

Why: If you rent GPU capacity, the practical question is what the contract guarantees: a cheap GPU-hour may come with interruption, slow storage recovery, or a specific GPU/network configuration that changes your real job cost. Builders evaluating reserved capacity should ask for those settlement terms explicitly, because SF Compute says its market spreads liquidity across variants while clusters remain non-interchangeable.