Carmen Li
Founder and CEO of Silicon Data, a GPU market-intelligence and benchmarking company building pricing transparency, indices, and market data products for AI compute markets. She is also CEO of Compute Exchange and has been a public voice on turning AI computing power into a tradable, hedgeable commodity, including through Silicon Data’s partnership with CME Group on compute futures.
GPU Futures Would Hedge AI Compute Rental-Rate Risk
Silicon Data, which has raised $30.5 million, is building pricing and performance benchmarks that CEO Carmen Li says could underpin a risk-management market for rented AI compute. Li said CME’s planned cash-settled GPU futures, tied initially to Silicon Data’s H100 and A100 indices, would let server owners hedge falling rental revenue and compute customers hedge rising costs. She argues that chip depreciation alone does not determine value: residual value depends on the cash flow older hardware can still generate.
AI Demand Pushes Beyond Nvidia Into Power, Memory, and Compute Markets
Bloomberg Technology framed Nvidia’s earnings as a test of the wider AI infrastructure trade rather than a simple chip-demand story. Caroline Hyde, Ed Ludlow and Bloomberg Intelligence’s Mandeep Singh said investors were looking past headline growth to constraints around China access, margins, memory prices, inference workloads and supply, while a $67 billion NextEra-Dominion deal showed how the data-center boom is already reshaping power markets. The program’s broader argument was that AI demand remains strong, but the bottlenecks have moved across the physical and financial stack.
CME and Silicon Data Plan Futures Market for AI Compute
Silicon Data CEO Carmen Li told Bloomberg Technology that AI compute is becoming a commodity market large and volatile enough to require futures and options. She said Silicon Data’s planned work with CME would create a regulated hedging layer for GPU-price exposure, using Silicon Data’s indices to normalize fragmented pricing across chip types, locations and contract terms. Li argued that banks, data centers, cloud providers and AI companies need those tools because on-demand GPU prices can swing sharply and bottlenecks keep moving across the supply chain.