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Speaker 1: Bloomberg Audio Studios, podcasts, radio news, single best idea.

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Speaker 2: And to give you a reality into how we do this,

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Speaker 2: How Emily House, Gonzol and Rachel Worspan and I invented

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Speaker 2: this over the years with wonderful, wonderful people helping out,

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Speaker 2: Ken Pruitt, David Gerrol, Michael McKee, John Pharaoh and all.

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Speaker 2: The way we invent it is to go find voices.

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Speaker 2: And last night Sunday evening in New York, a concerted

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Speaker 2: effort was just put in and it's just text messages

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Speaker 2: back and forth people watching the football game and all that.

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Speaker 2: But it's just named. There's not a lot of discussion,

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Speaker 2: there's not a lot of meetings and all that. It's

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Speaker 2: just go get Joe Wisenthal. We did. Joe was brilliant

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Speaker 2: at odd LA on using deep seek. We said, go

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Speaker 2: get Stacy Raskin at Bernstein. He's in Los Angeles Chemical

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Speaker 2: Engineering MIT. He's definitive on this AI stuff. He was

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Speaker 2: spellbinding from Bernstein getting up in his case at I

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Speaker 2: think the five thirty six am hour in LA. But

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Speaker 2: really the first email I sent yesterday and it wasn't

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Speaker 2: just me, it was a whole team. We all agreed.

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Speaker 2: Man Deep Sing and Inner Ragrana at Bloomberg Intelligence have

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Speaker 2: a holistic view of this uproar in technology from this

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Speaker 2: Chinese company, Deep Seek like nobody first. Man Deep Sing

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Speaker 2: on the impact of this AI shock.

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Speaker 3: Clearly, I think the investor expectations were different, which is

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Speaker 3: why you see this sort of stock reaction. So, yes,

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Speaker 3: we have Moore's law and we have other laws in

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Speaker 3: terms of figuring out how the cost curve may look

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Speaker 3: like over time. But clearly this is a step change

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Speaker 3: in terms of you know, what you can do with

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Speaker 3: the existing chips that are out there, as well as

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Speaker 3: what you will need going forward. So I think this

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Speaker 3: is a big moment in terms of just the efficiency

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Speaker 3: that we can see with these chips and the kind

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Speaker 3: of scale that is required for the next versions of

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Speaker 3: these foundational models. But there is no doubt that this

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Speaker 3: makes generative AI more accessible to software companies as well

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Speaker 3: as you know, overall users.

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Speaker 2: Men Deep saying there, one thing came up today. I

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Speaker 2: didn't even have time on the show to talk about it.

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Speaker 2: Multiple times today people spouted about Jevins paradox. William Stanley

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Speaker 2: Jevons is one of my heroes. He in the middle

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Speaker 2: of the nineteenth century, and he has a claim for

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Speaker 2: like sun spot theory, figuring out what sunspots mean. He

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Speaker 2: did things in the coal industry, very colectic, very applied

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Speaker 2: economics in the nineteenth century. William Stanley Jevons is the

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Speaker 2: person who dragged ancient economics into the modern age. There's

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Speaker 2: another guy named Walrus as well, but William Stanley Jevons

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Speaker 2: is the one who brought the calculus into static economics.

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Speaker 2: In a generalization, Jevins took the static economic analysis of

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Speaker 2: before over to a more dynamic economic analysis that was

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Speaker 2: picked up by Marshall and others at the turn of

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Speaker 2: the century. There's Jevons paradox, which I'm not going to

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Speaker 2: go into, but to make a long story short, you're

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Speaker 2: going to hear a lot about it, and it's just

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Speaker 2: about the system of technology's impact on the entire macroeconomic structure.

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Speaker 2: Andro Rana knows that he doesn't need to be lectured

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Speaker 2: by me on Jevins paradox. Aner Rana expert on the

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Speaker 2: cloud here on this uproar in tech.

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Speaker 4: So one of the things, if you would say, is

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Speaker 4: if this AI adoption could which is absolutely in infancy

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Speaker 4: right now, The only thing we have seen is in

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Speaker 4: the consumer world. If enterprises start to put this in

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Speaker 4: their core applications, then they would need a lot more

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Speaker 4: you could say, firepower to run it. Most of the

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Speaker 4: things that we have discussed is people would not want

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Speaker 4: to do this on their own premise. They're bigger companies well,

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Speaker 4: but most of them will go to a handful of

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Speaker 4: cloud providers and that would be Microsoft, Aws, Google and

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Speaker 4: then Oracle. So for all these companies to increase their

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Speaker 4: capacity now they are only seeing the orders and based

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Speaker 4: on that they are expanding their data center footwork.

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Speaker 2: Enter Agrana we had time with both enter Agrana and

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Speaker 2: man Deep saying to try to get forward to the

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Speaker 2: earning season upon us. That'll be our focus, I think

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Speaker 2: in the later this week, maybe tune into Bells of

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Speaker 2: Power with Joe Matthew and Kaylee Lyons because we hardly

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Speaker 2: talked about politics today. In international relations, thank you Damian Sasaur,

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Speaker 2: some currency chat, but all in all, just an extraordinary

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Speaker 2: day into the earning season, which we'll cover this week.

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Speaker 2: On your commute across the nation, Apple CarPlay, Android Auto

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Speaker 2: on Sirius and XM, and of course good morning on

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Speaker 2: a warmer Boston, down to Washington and New York City.

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Speaker 2: Bloomberg eleventh th toe to Oho. We're out on YouTube.

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Speaker 2: Subscribe to Bloomberg podcasts. This is a single best idea.