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Patrick OShaughnessy
@patrick_oshag
参加 June 2013
2.5K フォロー中    364.6K ファン
Cliff Sosin on why you want to own the complements to cheap intelligence, like Meta does: "I've found it helpful to assume everyone has really great intelligence and ask what's left. If intelligence becomes cheap and ubiquitous, what you want to own are the complements to intelligence. The complements are data, attention, love, physical proximity, scale, regulatory capture. Let's talk about Meta. They have $250 billion of revenue, and they spend $250 billion a year. The question you might ask is, what do they spend it on? A really reductionist view is that they spend it all on intelligence. They're buying data centers. They're literally buying inference. They're paying really smart people to write algorithms. They're writing code. That's just intelligence. If you think forward with the fact that the price of intelligence is falling by a factor of a hundred or something over the next five years, their costs kind of go away. Maybe instead of taking their cost to zero with much better intelligence at much lower prices, maybe they can sell a few more ads. All of this is downstream of what they possess, which is not destroyed by ubiquitous intelligence, which is data and attention. I don't think that the availability of cheap and ubiquitous intelligence is gonna cause people not to be interested in watching funny 20-second videos."
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Cliff Sosin (@CliffordSosin) is one of my favorite people to call, ask some big questions, and then shut up and listen. This conversation is a version of one of those calls. We discuss: - The limits of intelligence - Owning the complements to it - Meta, the frontier labs, and the AI build-out - Capital markets - Why he's comfortable with 80% of his portfolio in Carvana. TIMESTAMPS 0:00 Intro 10:41 The Limits of Intelligence 18:03 Investing Beyond Cheap Intelligence 24:03 Will AI Become Commoditized? 35:10 Who Profits From AI? 43:00 AI Agents Reshape Competition 52:06 America's Capital Markets 58:04 Transforming Companies With AI 68:19 AI and Portfolio Concentration 73:16 Education in the AI Era
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