@carmenli , CEO of @silicondata and @computeexchange , joins the show to explain how compute is becoming a brand-new asset class. A former energy options market maker at DRW who later ran global data integrations at @Bloomberg , Carmen was pre-seeded by DRW founder Don Wilson to build the GPU industry benchmarks. Silicon Data is the referee "the Bloomberg for compute" while Compute Exchange is the liquidity layer where GPUs, tokens and servers change hands. We get into why token price indexes are falling, recent token & model consumption trends, why GPU residual values are above accounting depreciation schedules, and how neoclouds, their lenders, and compute users can hedge GPU exposure to reduce business volatility. • "The A100 has been around for six years at this point, and we still see three-year contracts signed on A100s." Residual values are still hovering above five-year straight-line depreciation. • “we'd definitely be looking at 30 trillion of [GPU] derivatives every year." Topics: Compute as an asset class, GPU indices, CME compute futures, GPU depreciation and useful life, neoclouds, token pricing, AI chip supply chain, 💡 This episode is presented by: @OxfordDataPlan –The Home of Alternative Data *Not Investment Advice. Highlights: (0:00) Doug introduces Carmen Li, CEO of Silicon Data and Compute Exchange (0:20) From energy options market maker at DRW to Bloomberg Data, and why AI startups' swinging GPU costs made compute an industry-wide hedging problem (4:09) How DRW founder Don Wilson pre-seeded Silicon Data, and building products with no product or sales team (6:10) Two sides of the coin: Silicon Data as "the Bloomberg for compute" and Compute Exchange as "the Nasdaq for compute" (7:49) Licensing indices to CME for H100 and B200 compute futures, and four ETFs filed before the futures even trade (10:22) What makes an index the source of truth: tracking supply-demand, resisting manipulation, staying neutral (12:57) Normalizing 50 B200 server configurations, and what earns a premium or a discount to the benchmark (16:04) Sizing the market: from 1–3 trillion in spot compute to a potential 30 trillion in derivatives notional (18:13) Who hedges first: neoclouds, hyperscalers and the financiers holding GPUs on their balance sheets (21:06) Michael Burry's depreciation bear case vs. the physical market: A100s still signing three-year contracts after six years (22:49) Why older chips stay productive: cooling, floor weight, wait times and the second-hand market (26:20) 300+ neoclouds and why more data sources make an index harder to manipulate (28:48) B200s at ~$5 per GPU hour, the implied forward curve and the shift into contango (31:18) Why an index provider can't give forward guidance, or own the assets it measures (33:59) Token indices on the Bloomberg Terminal, and a leading indicator for AI revenue (37:03) Why token prices are falling: workflows moving to open-source and open-weight models (38:51) Token pricing has no transparency, and why customers will demand control (41:49) Where to invest in the AI stack, lessons from the internet era and why "AI is a gigantic baby" (45:03) Homegrown silicon, fab capacity and why a hundred chip designers can't create a bubble (48:56) Why compute futures enable price discovery, not a bubble (49:29) Running a data company and a marketplace at the same time (52:47) Carmen's lesson for entrepreneurs: pick something you love (54:08) The vision: the liquidity provider and the referee for every layer of the cake Research Sponsors: @Fiscal_ai - Delivering Modern Financial Data Infrastructure. 15% discount with code PITCH @AlphaSenseInc Grade AI @CarbonArcAI Infrastructure for the AI Economy Pitch The PM Links: 📩Early episode drops episode feedback on Substack Daily industry chatter and market color on LinkedIn Carmen Li Links: Carmen LI on LinkedIn: Silicon Data: silicondata.com Compute Exchange: compute.exchange