AI demand is a barbell, with the labs on one end and enterprise cost-cutting on the other. Amazon CEO Andy Jassy says the biggest market sits in the middle, and inference is still "an order of magnitude too expensive" to reach it. "On one end of the barbell are the AI labs who are consuming gobs and gobs of compute, unlike anything I've seen. And then a few runaway apps, ChatGPT, Claude Code, things like that." "On the other end of the barbell are enterprises who are largely using AI for cost avoidance and productivity, so automating customer service or fraud or business process automation." "In the middle of the barbell are the current production workloads of enterprises, many of which are using AWS and using inference today, but I would say the overwhelming majority of which still aren't in any pervasive way." "And that I think is gonna be the largest absolute segment of AI usage." "The cost of inference has come down quite a bit in the last few years, but it's still an order of magnitude too expensive, in my opinion, for it to be used as pervasively as possible." "If you're asking enterprises to rewrite their applications that use CPU today with AI accelerators... the amount of incremental benefit they have to get is a much higher bar to want to rewrite those apps. But if you can take the cost of inference down, that bar is much lower, and all applications are gonna be better and smarter and more capable." @ajassy Quoted @a16z: Five years into his run as CEO, Andy Jassy has nearly tripled the size of AWS, grown Amazon's revenue by about 80%, and expects to spend $220 billion this year to win AI. Amazon's AI business hit a $25 billion run rate in three years, growing several hundred times faster than early AWS. Jassy joins a16z's Ben Horowitz and Erik Torenberg to discuss the decisions behind that run, from rebuilding Amazon's fulfillment network after the pandemic to the AWS origin story. They also cover why data centers became a political fight, Amazon's custom chips, its stakes in Anthropic and OpenAI, why inference needs to get 10x cheaper, AI's most underrated risk, and why every company will have to reinvent its products from scratch, plus Jassy's advice for anyone who's 18 today. 0:47 How Amazon has changed since 2021 1:51 How the pandemic reshaped retail 3:30 Why AI supercharged AWS's growth 5:20 When leadership principles clash 9:36 $60M vs. $25B: early AWS vs. early AI 13:20 How the AI CapEx cash cycle works 15:44 Why the US must build data centers 20:55 The labs-to-enterprise AI barbell 23:12 Demand vs. longtime AWS customers 28:11 Annapurna, Graviton, and Trainium 33:55 Backing Anthropic and OpenAI 37:15 Why AI means smaller teams 42:13 AI's underrated risk: security 46:29 Why Amazon rewired Alexa's brain 53:07 What Jassy tells his kids about AI 56:36 Betting on AI, robotics, and space YouTube: https://t.co/zE8sSmmO6N @ajassy @Amazon @bhorowitz @eriktorenberg