Steeve Morin

Morin’s headline call: the H100 is a bubble that may blow sometime — “probably this year” for the potential compute oversupply/distress scenario. The market runs on the A100 financial model — generation zero trains, last generation does inference — but the H100 arrived at 5x the price with only ~2x the inference performance, financed by six-to-seven-year amortization plans with the GPUs themselves as collateral. “Something has got to give” — he’s already getting cold-email discounts from providers he’s never heard of, and speculates GPUs may be bought for “30 cents on the dollar.”

The value split in five years: “95% inference, 5% training.” Agents and reasoning flip compute economics from throughput-bound to latency-bound — a GPU can serve 10,000 tokens/second across 100 streams but not to one user — and “this is where Nvidia can be attacked.” Yet forced to buy one stock today, he still picks Nvidia “because the supply,” hoping to come back later and say buy AMD “as much as you can.”

Google is the sleeping giant. His winning triangle is products, data, and compute — “who has all three? Google… they can sprinkle everywhere.” The shallow take is that OpenAI threatens search; in reality “OpenAI is amazing, but it’s not their compute” — it’s Microsoft’s, and “if you don’t own your compute, you’re starting with something at your ankle.”

The margin stack is the tradeable insight for anyone building on AI: TSMC sells at 60% margin, Nvidia at 90%, Amazon takes another ~30% — “you are a very thin crust on a very big cake.” His advice to startups: do not resell compute if you can; of $1 of spend, ~98% is somebody else’s margin, impossible to square into a $20/month subscription.

Switching economics explain why AMD hasn’t closed the gap despite ~4x inference efficiency: “being seven times better is not enough to get people to switch — people will choose nothing over something.” The workaround is top-down: Microsoft bought AMD’s supply and runs ChatGPT on it, which puts OpenAI’s inference “in the green.” ZML’s thesis is to make the buy-in zero so “if you are 30% better, I’ll switch to you.”

On new silicon: Gro and Cerebras prove single-stream speed via SRAM but the economics don’t scale (Gro has 230MB per chip; a 70B model in BF16 is 140GB — “you do the math”). The companies he sees going in the direction of lower prices: Etched and likely VSORA — “if you can deliver this at a price comparable to GPUs, you’ve won” — with compute-in-memory (likely Rain AI, Fractile) as the frontier after that.

Stargate: “I don’t buy it… it’s an American car of AI — it’s big, it consumes a lot of gas, but ultimately it’s not a good car.” The real limits are “talent and energy, that’s it.” Meanwhile Blackwell orders are getting cancelled over heat-dissipation and chip-bending problems, and Jensen’s true challenge is “how to navigate the down slope — the highs are very high, but they don’t last forever.”

🔗 Original source & video: Steeve Morin: Why Google Will Win the AI Arms Race & OpenAI Will Not | E1262