Carmen Li, CEO of Silicon Data and Compute Exchange, 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:Oxford Data Plan–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.
(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
Oxford Data Plan–The Home of Alternative DataAlphaSense–Decision Grade AICarbon Arc–The 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:https://www.silicondata.comCompute Exchange:https://compute.exchange
