Anjney Midha wrote the first check to Anthropic. He teaches a viral course at Stanford on how AI works. And he was, until recently, a partner at a16z. In other words, he is AI-industry royalty. Midha's new project is AMP PBC, a company that believes it can radically lower the price of compute. To accomplish that, he is working on building a compute grid that turns GPUs into a standardized utility. But right now, compute is too fragmented. It's too heterogeneous. And given the way contracts are structured, he says that labs are being forced to spend money on capacity that often goes unused. In other words, small labs are forced to pay up for big, long-term contracts, even though their own demand (particularly during model training) may be very spiky. On this episode, Midha explains how the market for compute currently works and why he believes there's a software solution that could significantly improve compute utilization. He also tells us why he does not anticipate one company will emerge as the dominate player and that instead we'll have a wide range of models, each optimally used in specific applications.

Read more:
Amazon Says Its Data Centers Use 2.5 Billion Gallons of Water
Oracle Falls Most in Six Months on Mounting Data Center Costs

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Anjney Midha wrote the first check to Anthropic. He teaches a viral course at Stanford on how AI works. And he was, until recently, a partner at a16z. In other words, he is AI-industry royalty. Midha's new project is AMP PBC, a company that believes it can radically lower the price of compute. To accomplish that, he is working on building a compute grid that turns GPUs into a standardized utility. But right now, compute is too fragmented. It's too heterogeneous. And given the way contracts are structured, he says that labs are being forced to spend money on capacity that often goes unused. In other words, small labs are forced to pay up for big, long-term contracts, even though their own demand (particularly during model training) may be very spiky. On this episode, Midha explains how the market for compute currently works and why he believes there's a software solution that could significantly improve compute utilization. He also tells us why he does not anticipate one company will emerge as the dominate player and that instead we'll have a wide range of models, each optimally used in specific applications.
Read more: <a href="https://www.bloomberg.com/news/articles/2026-06-11/amazon-says-its-data-centers-use-2-5-billion-gallons-of-water?utm_medium=referral&amp;utm_source=podcast&amp;utm_campaign=odd_lots&amp;utm_content=article" data-prosemirror-content-type="mark" data-prosemirror-mark-name="link">Amazon Says Its Data Centers Use 2.5 Billion Gallons of Water</a> <a href="https://www.bloomberg.com/news/articles/2026-06-10/oracle-reports-higher-than-expected-data-center-spending?utm_medium=referral&amp;utm_source=podcast&amp;utm_campaign=odd_lots&amp;utm_content=article" data-prosemirror-content-type="mark" data-prosemirror-mark-name="link">Oracle Falls Most in Six Months on Mounting Data Center Costs</a>
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Bloomberg's Joe Weisenthal and Tracy Alloway explore the most interesting topics in finance, markets and economics. Join the conversation every Monday, Thursday, and Friday

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Odd Lots

On Bloomberg’s Odd Lots podcast Joe Weisenthal and Tracy Alloway explore the most interesting topics in finance, markets, and economics. Join the conversation every Monday, Thursday, and Friday.

On Bloomberg&rsquo;s Odd Lots podcast Joe Weisenthal and Tracy Alloway explore the most interesting topics in finance, markets, and economics. Join the conversation every Monday, Thursday, and Friday.

Anjney Midha's Plan to Radically Lower the Price of Compute

https://api.omny.fm/orgs/e73c998e-6e60-432f-8610-ae210140c5b1/clips/90cd8aa8-11c9-4cd3-813a-b467011c7f57/transcript