a16z两位合伙人分享真实数据：工程师AI支出差异巨大，代币消耗暴增100倍，算力短缺比AI泡沫更值得关注。
a16z合伙人David George和Gavin Baker指出，工程师使用AI的支出差异达10-100倍。全球有15亿知识工作者，AI需求被严重低估。Atreides公司内部代币消耗从3月到8月增长了100倍，使用Grok Bot Enterprise后可能再增长10-20倍。
David George and Gavin Baker on why AI demand is just getting started, and the numbers they're seein...
David George and Gavin Baker on why AI demand is just getting started, and the numbers they're seeing across power users: David: "If you actually look at the power law of the actual engineers in those companies, the highest-spending engineers are spending 10 or sometimes 100x more than the median engineer." "And so there's this question of, where are we at in diffusion? There's one and a half billion knowledge workers. It feels like we're nowhere on the demand side and we're massively supply constrained." Gavin: "At Atreides, our internal token consumption has gone up 100x from the month of March. March through August, 100x our token spend." "And we just got access to Grok Bot Enterprise, and with two people using it, it looks like token spend might 10 or 20x in a month from August." David: "It's actually extremely valuable. We have some heavy Grok Bot users here, and it is very productive use. This is not wasteful token spend." @DavidGeorge83 @GavinSBaker Your browser does not support the video tag. 🔗 View on Twitter a16z @a16z Gavin Baker and a16z's David George on the state of the AI boom: The future doesn't have to be winner-take-all. Labs, open-source, applications, and the clouds can all capture value. Demand for intelligence is still dramatically underestimated. Today's power users number in the millions and will grow to hundreds of millions. Gavin and David argue a compute shortage is a more real risk than an AI bubble, and building through it is an opportunity to reindustrialize America. In this episode, they get into why compute investments pay back so fast, what the data center backlash gets wrong, the case for putting compute in orbit, why enterprises will run several models at once, and how Nvidia ended up at the center of the entire supply chain. 00:00 Intro 01:06 The bear case Gavin couldn't find 05:50 Why a lab would cut its own revenue 75% 08:05 What LPs get wrong about a crash 10:50 Microsoft slowed its capex and regrets it 14:33 The engineers spending 100x the median 17:35 Why 23-year-olds use AI better than Gavin 21:45 How much copper 500M AI users need 23:00 Stop promising to cure cancer 26:00 America's richest county is full of data centers 30:48 Who gets priced out of compute 33:05 The age of Elon and Jensen 34:25 Orbital data centers 44:40 Asteroid mining 48:12 Why Microsoft doesn't need a frontier model 54:02 Who becomes the abstraction layer 55:40 Everyone wanted a deity, Cursor wanted a product 1:00:25 Never take shots at Jensen 1:07:40 What happens when the chip doesn't work 1:12:10 What chip deals reveal about customer demand YouTube: youtube.com/watch?v=FGC4of… @GavinSBaker @DavidGeorge83 Your browser does not support the video tag. 🔗 View on Twitter 🔗 View Quoted Tweet 💬 0 🔄 0 ❤️ 12 👀 4573 📊 2 ⚡