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Speaker 1: From the heart of where innovation, money and power collide

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Speaker 1: in Silicon Valley and beyond. This is Bloomberg Technology with

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Speaker 1: Caroline Hyde and Ed Ludlow.

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Speaker 2: Live from New York.

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Speaker 3: I'm Caroline Hyde and I'm Jackie Devalas in San Francisco.

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Speaker 2: This is Bloomberg Technology coming up in video. Shares slipping

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Speaker 2: despite an upbeat view on the Blackwell lineup, has US

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Speaker 2: investors see a mixed outlook after two years of blowout results.

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Speaker 2: Plus investors unsure of Salesforce's new AI product if it

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Speaker 2: can spur faster sales growth or break down the company's earnings.

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Speaker 2: And we sit down with the CEO of Amazon after

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Speaker 2: the company unveiled the long awaited AI version of its

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Speaker 2: Elexor assistant and just announced its new quantum computing chip.

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Speaker 2: At first quick check on these markets, as we can currently,

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Speaker 2: we are under pressure once again. This is a macro

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Speaker 2: picture that weighs heavily on the market. Perhaps some inflatory

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Speaker 2: pressures worries about Taris and Nvidiant numbers did not do

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Speaker 2: enough to ease those concerns. Were down some three point

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Speaker 2: seven percent. Looks still a three trillion dollar company, But

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Speaker 2: here in lies the issue. Of whether or not Blackwell

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Speaker 2: is ramping as fast enough to offset some of the

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Speaker 2: concerns around China and tariffs and limitations on exports. Jonson

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Speaker 2: Wang does a lot to talk about the new cycle

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Speaker 2: of scaling laws that come, of course from reasoning models.

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Speaker 2: We move on to some other individual names that we're

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Speaker 2: going to be diving into across the board. Salesforce under

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Speaker 2: pressure off by two percent. Will discuss the earnings a

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Speaker 2: little bit later. Agent Force not bringing in the revenue

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Speaker 2: as quickly has had been anticipated, And let's just finish

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Speaker 2: on the all important Amazon currently trading as we see

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Speaker 2: macro pressure on tech more broadly, we're currently flat a

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Speaker 2: new quantum chip and most notably, of course, the generative

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Speaker 2: AI infusion into Alexa Plus, which we can delve into

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Speaker 2: in the CEO in a moment, because we now want

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Speaker 2: to welcome to our TV and radio audiences worldwide. Amazon's

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Speaker 2: president and CEO, Andy Jesse. Great to have you on

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Speaker 2: New York.

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Speaker 4: Thanks for having me. It's great to be here.

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Speaker 2: Back home where you grew up and you were unveiling

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Speaker 2: generative AI infused Alexa Plus. How is this going to

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Speaker 2: really well excite your customer base? What are you most

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Speaker 2: excited for it.

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Speaker 5: Well, you know, we've had Alex has been around for

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Speaker 5: ten years. We have six hundred million devices in customers'

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Speaker 5: homes and offices. And Alexa Plus is our next generation

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Speaker 5: Alexa Personal Assistant, and she's meaningfully smarter and more capable

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Speaker 5: and useful than her prior self. You can do all

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Speaker 5: the things that you used to do, but every single

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Speaker 5: one of those functions is better.

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Speaker 4: And I can give you just an example. There are

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Speaker 4: so many examples.

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Speaker 5: But you know, if you have smart home controls with

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Speaker 5: Alexa now, you can say, Alexa, I have guests coming

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Speaker 5: over at seven pm?

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Speaker 4: Could you raise the drapes, could you raise.

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Speaker 5: The temperature by five degrees, turn on the porch lights

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Speaker 5: and the driveway lights, and put on Melo dinner music in.

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Speaker 4: The dining room.

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Speaker 2: And music you're not a guy. May I choose shop.

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Speaker 5: Fighters, but most people will choose Melo dining music. But

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Speaker 5: you can do that all verbally and simply using conversational

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Speaker 5: language like that.

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Speaker 4: You don't need a nap. It just happens.

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Speaker 5: And so Alexi Plus, with what we've just announced and

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Speaker 5: what we're launching, it really is. There have been a

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Speaker 5: lot of chatbots around that are good at answering questions,

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Speaker 5: but they don't take actions. Alexi plus is really Alexa

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Speaker 5: is going to be the first one that not only

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Speaker 5: is highly intelligent to answer various questions, but she can

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Speaker 5: do so many things for you. She can play music

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Speaker 5: and play video, and control your smart home and make

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Speaker 5: reservations for you and hire people to fix your oven.

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Speaker 4: I mean, it really is the first.

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Speaker 5: Big, large scale practical use of gender of AI. The

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Speaker 5: consumers are going to be able to see and use naturally.

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Speaker 2: I can see how you're going to obsess over it,

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Speaker 2: whether it's ordering the latest buffalo in New York and

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Speaker 2: seeing where the best space is to do that. But

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Speaker 2: how are your stakeholders of shareholder based going to obsess

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Speaker 2: about this about gender to AI in Alexa plus. How

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Speaker 2: is that adding value for them?

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Speaker 4: Well?

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Speaker 5: You know, I think if you think about what Alexa

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Speaker 5: allows customers to do, it makes shopping more easy because

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Speaker 5: it's so much more intuitive now to buy products. It

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Speaker 5: makes enjoying music easier, It makes enjoying video and streaming

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Speaker 5: media better. It allows you to control your smart home

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Speaker 5: in a different way. So every single one of our

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Speaker 5: consumer customer experiences gets better with Alexa Plus. And then

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Speaker 5: you know, of course Alexa has its own business model.

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Speaker 5: We have a brand new lineup of devices that are

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Speaker 5: coming in the fall. I think that are beautiful. I

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Speaker 5: think people are going to really like we have opportunities

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Speaker 5: to service new products and advertising in various interfaces like

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Speaker 5: our mobile and our desktop interface that's coming in Alexa.

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Speaker 5: And then we have subscriptions, and you know, so I

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Speaker 5: think there's a sustainable business model there as well.

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Speaker 2: Talk to me about the subscriptions because you're getting it free.

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Speaker 2: If you've got Prime, I get a lot with Prime.

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Speaker 2: Now are you able to increase the prices there?

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Speaker 4: Do you think of Prime?

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Speaker 5: Well, Prime is an incredible value if you think about

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Speaker 5: getting free shipping on three hundred million plus items. You know,

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Speaker 5: when we launch Prime, it is free shipping on about

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Speaker 5: a million items, to say, it's three hundred million items,

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Speaker 5: and most of the time you're getting your products now

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Speaker 5: inside of a day. And so you know, between that

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Speaker 5: and what you get with Prime Video and Prime Music

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Speaker 5: and the grocery subscription, and you know our unique selling

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Speaker 5: events Primes and incredible values you could increase to add

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Speaker 5: on top of it Alexa Plus.

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Speaker 4: You know, it's just great value. So what do they

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Speaker 4: plan right now?

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Speaker 5: But it's I do think prime is unusual value and

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Speaker 5: it's why people use it so expansively.

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Speaker 2: And to increase that use has been this invention, this

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Speaker 2: innovation of generative AI, and that costs money. And you've

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Speaker 2: actually just took to the stage yesterday to say, out

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Speaker 2: of all companies, you are spending the most on AI.

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Speaker 2: How much are you spending on AI?

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Speaker 5: Well, you know, I think we don't disclose the exact amount,

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Speaker 5: but you know we you know, we're spending a pretty

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Speaker 5: significant amount of cappax, and the allion's share of it

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Speaker 5: is on generative AI. We've said in our AWS business,

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Speaker 5: even though general AI for US is a many billion

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Speaker 5: dollar a year business and growing triple digit percentages year

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Speaker 5: over year, that if we hadn't even more capacity, we

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Speaker 5: could use.

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Speaker 4: It to monetize it.

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Speaker 5: And we have this really interesting and very fortunate flywheel

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Speaker 5: and AI inside of Amazon, which is if your mission

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Speaker 5: is to make customers' lives easier and better every day,

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Speaker 5: which it is for.

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Speaker 4: Us, and if you believe that.

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Speaker 5: All the customer experiences we know of today are going

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Speaker 5: to be reinvented through generative AI, which we also believe

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Speaker 5: you believe those two things, you're going to be building

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Speaker 5: a lot of genera AVEAI apps. If you build a

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Speaker 5: lot of general of AI app By the way, other

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Speaker 5: companies are too on top of AWS, which is the

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Speaker 5: leading technology infrastructure platform.

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Speaker 4: So if there are a lot of AI apps being.

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Speaker 5: Built on top of you, you can't help but get

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Speaker 5: a lot of feedback from people on how they want

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Speaker 5: those building blocks that create gender AI to be better.

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Speaker 5: And if you're willing to invest in those building blocks,

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Speaker 5: which we are, as you know, with our own chips

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Speaker 5: with Trainium and with our own frontier.

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Speaker 4: Model with Amazon Nova and Model.

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Speaker 5: Building Services and Sage Maker AI and better Rock, if

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Speaker 5: you're willing to invest in those building blocks and you're

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Speaker 5: getting a lot of feedback, they get better much more quickly,

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Speaker 5: which can't help them make it easier and quicker for

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Speaker 5: people to build gender AI applications, which means you get

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Speaker 5: more running on the platform. So that flywheel is very

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Speaker 5: unique for Amazon.

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Speaker 2: The line share though you did say basically one hundred

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Speaker 2: billion dollar run rate for CAPEX expenditure, can you give

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Speaker 2: us even like a percentage ratedown of how much that

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Speaker 2: goes to distribution logistics and how much goes to AI?

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Speaker 5: Well, line shares, you know, you tell you boast of it,

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Speaker 5: you know most of it. You know the lions share

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Speaker 5: is more than fifty percent?

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Speaker 2: Yes, is it more than eighty percent?

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Speaker 4: We're playing the warmer and colder game.

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Speaker 2: Yes, exactly. I love a game. But taught us about

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Speaker 2: that capacity that you talked about. Yeah, AWS could grow

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Speaker 2: even faster if you had all the chips that you needed,

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Speaker 2: all the power you needed, the motherboards you needed. How

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Speaker 2: much faster could AWS go?

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Speaker 4: I could.

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Speaker 5: It's hard to put an exact percentage, but I do

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Speaker 5: think it could be growing faster. I'm confident could be

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Speaker 5: growing faster. And you know there is you know, for

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Speaker 5: a long time, there still aren't as many chips as

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Speaker 5: we all want.

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Speaker 4: We have.

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Speaker 5: We're fortunate in that we're very big partners with Nvideo,

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Speaker 5: But then we also have our own custom AI silicon

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Speaker 5: in Tradium.

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Speaker 4: Too, which we just released to Reinvent.

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Speaker 5: Which is thirty to forty percent more price performance than

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Speaker 5: the GPU powered instances, which is a big deal at

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Speaker 5: scale if you're doing gender of AI on the inference side.

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Speaker 5: So we have maybe more chips than some others might

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Speaker 5: have access to, but we still don't have enough, and

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Speaker 5: then there just is not enough power in the world

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Speaker 5: right now, and we're all working really hard on that.

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Speaker 5: I expect that to relieve some the second half of

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Speaker 5: this year, but right now, you know, the world can change,

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Speaker 5: but right now we have just insatiable demand.

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Speaker 2: We had amazing demand coming from Jensen Wong who had

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Speaker 2: his numbers out yesterday and Nvidio. Was there a limitation

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Speaker 2: on the in video chips in particular that pull back

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Speaker 2: capacity And at what point do you think can depend

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Speaker 2: even more on your own in house built chips offset

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Speaker 2: any of that.

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Speaker 5: Well, you know, I would say, I mean there's a

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Speaker 5: lot of demand for gener Ai right now.

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Speaker 4: People are very excited about it.

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Speaker 5: I think that all the different providers of chips have

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Speaker 5: been constrained to some extent.

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Speaker 4: I think some of.

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Speaker 5: The some of the new generations maybe have gone through

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Speaker 5: different evolutions and when they're going to be released maybe

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Speaker 5: a little later than people thought. There are some components

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Speaker 5: like motherboards and things like that that we all use,

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Speaker 5: that particular ones that are in shorter supply than others.

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Speaker 5: So you know, I do think there's some there are

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Speaker 5: some supply chain issues which I expect to get better.

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Speaker 5: I do you know, people are very excited about training

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Speaker 5: them too. To your question and whether we could see

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Speaker 5: more demand there, and we have gone back at least

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Speaker 5: a couple occasions to make more trainium too than we'd

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Speaker 5: intended because we have so much demand. So I expect

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Speaker 5: the will of customers for as long as I can

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Speaker 5: foresee wanting to run compute on instances that have in

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Speaker 5: vidio chips. But I think a lot of the demand

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Speaker 5: will also be served by.

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Speaker 2: Training the customers that you couldn't serve because of the

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Speaker 2: limited capacity. Is it that you just had to put

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Speaker 2: it back from everyone a little bit more generally or

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Speaker 2: who lost out here?

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Speaker 4: Do you think it's it's always a combination.

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Speaker 5: I mean, there's for people that just have a very

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Speaker 5: small amount of accelerators that they need, they don't usually

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Speaker 5: have a problem.

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Speaker 4: We have something called capacity blocks with.

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Speaker 5: It's kind of like an on demand way to use

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Speaker 5: accelerators and and generate e chips, and that continues to go.

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Speaker 4: It's really the folks who.

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Speaker 5: Have built, you know, have an idea for a new application,

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Speaker 5: but they need a lot of of chips, where if

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Speaker 5: we don't have the capacity, we have to you know,

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Speaker 5: we have to give them what we can give them

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Speaker 5: and give it to them as fast as we can

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Speaker 5: and push our partners to get it in sooner. And

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Speaker 5: they can't get their initiatives done as quickly as they

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Speaker 5: want to if the capacity isn't there.

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Speaker 2: Anthropics had all the capacity it needs. You've got on

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Speaker 2: a close relationship.

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Speaker 5: Yeah, we have a very close partnership with Anthropic. We

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Speaker 5: have this project called Project right near with them. They're

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Speaker 5: building their next model, their next version of their frontier

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Speaker 5: model on top of trainingum to and our custom AI silicon.

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Speaker 5: They're going to use over four hundred thousand trainum two

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Speaker 5: chips and so yes, they have capacity. They're they're ramping

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Speaker 5: up and we're excited about that partnership and what they're building.

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Speaker 2: You mentioned the power side. How much is that something

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Speaker 2: you're talking to the administration about? How much is the

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Speaker 2: administration supportive of the buildout that you need to do.

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Speaker 5: We have been talking to administration, you know, multiple administrations

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Speaker 5: in this country over the years, as well as in

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Speaker 5: other countries as well. And I think the power shore

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Speaker 5: is really knuck up on people, you know, really right

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Speaker 5: after the pandemic. And I would say that the current

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Speaker 5: administration is very receptive to it. They understand the constraints

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Speaker 5: it's having on the economy right now and are convicted

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Speaker 5: about solving it.

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Speaker 2: What about the restrictions around chips? And what's interesting is

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Speaker 2: Microsoft just called on the administration today to say, this

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Speaker 2: limitation on chip access for some of our close allies

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Speaker 2: around the world is going to limit our global business.

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Speaker 2: You are a global business. Is that something you're worried about?

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Speaker 4: Hey, we are? You know?

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Speaker 5: I think I think that you're really talking about that

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Speaker 5: AI Diffusion Act. I think, and I'm going to be

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Speaker 5: curious to see where that goes. I mean, it was

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Speaker 5: enacted pretty quickly at the very end of the last administration.

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Speaker 5: I don't know how this administration feels about it, but

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Speaker 5: I would say that we share the concern that it

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Speaker 5: has limitations on certain countries who are natural allies of

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Speaker 5: the US who just to be able to do their business,

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Speaker 5: and those companies to be able to get done what

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Speaker 5: they want to get done on top of these technology

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Speaker 5: infrastructure platforms like AWS, they're going to need more chips,

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Speaker 5: and so I think if we don't do it, we're

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Speaker 5: going to basically give up that business and those relationships.

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Speaker 5: To other countries who can provide those chips, and I

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Speaker 5: think we're better off being partners with them.

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Speaker 2: Is it a risk to AWS, It's not.

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Speaker 4: So much risk.

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Speaker 5: I mean, I mean it had it, you know, in

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Speaker 5: the scheme of things. It's not a big swinger. But

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Speaker 5: I also think that there are so many countries who

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Speaker 5: are in the early stages of their economic development who

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Speaker 5: both really need access to the most cutting edge sophisticated

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Speaker 5: technology to build the right customer experiences. And that could

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Speaker 5: be big geographic markets for companies like ours and lots

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Speaker 5: of other technology companies where I think it would be

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Speaker 5: a shame to limit them and to limit the companies.

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Speaker 2: Did the AI diffusion rules that was born in very

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Speaker 2: swiftly by the Biden administration. All of this is in

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Speaker 2: the context of US versus China and not wanting to

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Speaker 2: get the most sophisticated equipment and chip and technology into China.

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Speaker 2: What rate for us for a moment the administration and

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Speaker 2: whether it's been positive or negative for your business when

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Speaker 2: it comes to China Dominimus, for example, the fact that

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Speaker 2: Chinese competitors, if we call them nat Sheian and the like,

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Speaker 2: it can have to pay more to get goods into

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Speaker 2: the country. Does that help or hinder you?

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Speaker 5: Well, you know, I would say, you know, on Deminimus specifically,

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Speaker 5: you know, we have a certain number of items that

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Speaker 5: are shipped in that way as well, for things like Hall,

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Speaker 5: which is our new low price offering. We maybe have

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Speaker 5: less of it than some other companies, like the ones

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Speaker 5: that you mentioned, but I think it's early in this administration.

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Speaker 5: But what I would say is that it is encouraging

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Speaker 5: to us that we have an administration that wants to

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Speaker 5: hear from business. I would say that, you know, we've

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Speaker 5: been a business through six administrations. Every single A lot

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Speaker 5: of them are primary for focuses to take care of customers.

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Speaker 5: But we try to build a productive relationship with the

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Speaker 5: administration because we want to help the country. And I

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Speaker 5: would say that some administrations are more receptive to it

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Speaker 5: than others. But this administration cares about what business thinks.

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Speaker 5: And I've always been surprised that it isn't obvious that

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Speaker 5: the best economic results for a country are going to

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Speaker 5: be when the public and the private sector collaborate. And

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Speaker 5: you know, I don't expect the government to kout out

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Speaker 5: to what companies want, but they should get their feedback

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Speaker 5: and their input because they're going to make policies better

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Speaker 5: together if they collaborate. And I'm encouraged early on that

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Speaker 5: this administration wants to talk to businesses.

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Speaker 2: Are you taking calls passingly?

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Speaker 5: You know, I take calls. We talked to you know,

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Speaker 5: the same thing with all the administrations. We talk to

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Speaker 5: people in the administration. We share what's working for us,

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Speaker 5: what's not working for us, concerns that we have. As

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Speaker 5: I said, some administrations care more about our feedback than.

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Speaker 2: Others about yours.

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Speaker 4: Have you spoken to I've spoken to the president.

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Speaker 5: Look, as I said, this administration has been pretty busy

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Speaker 5: the first month, and when I am encouraged that they

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Speaker 5: are having conversations with businesses and they do care about

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Speaker 5: our feedback. And we'll see what happens. But I you know,

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Speaker 5: it starts with a dialogue. You have to have a

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Speaker 5: dialogue to have any kind of relationship.

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Speaker 2: And they care about AI infrastructure. Just take stargate. Are

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Speaker 2: we going to hear more from you on how much

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Speaker 2: you're investing here in the United States on the AI

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Speaker 2: infrastructure build out as well?

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Speaker 4: Well?

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Speaker 5: You know, as we talked about earlier, we said it

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Speaker 5: was you know, directionally right in terms of the run

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Speaker 5: rate on our capex. But you know, we're spending a

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Speaker 5: lot on AI infrastructure, and the lion's share of it

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Speaker 5: is not just on AI, but also in this country

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Speaker 5: in the US. We spend elsewhere because we have a

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Speaker 5: global business. We have customers everywhere. We have customers and

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Speaker 5: you know, a couple hundred countries, but we have a

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Speaker 5: pretty substantial investment that I don't expect to to attenuate soon.

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Speaker 2: Only we could get a number. I'm interested in something

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Speaker 2: that perhaps is going to feel a more sensitive topic,

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Speaker 2: and it comes around perhaps some words that were missing

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Speaker 2: in your annual report this year, which were diversity and inclusion.

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Speaker 2: I put this in the context of the administration as

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Speaker 2: it stands, because I know that Amazon strives to be

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Speaker 2: the Earth's best employer, and I'm just wondering how your

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Speaker 2: employees react to perhaps the lack of certain words now involved,

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Speaker 2: and whether or not programs might be forced to change

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Speaker 2: or not.

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Speaker 4: Yeah.

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Speaker 5: Well, what I would tell you, just at a high level,

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Speaker 5: if you serve as many customers as we do, in

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Speaker 5: as many diverse groups as we do, and we intend

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Speaker 5: to moving forward, you have to have a diverse team

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Speaker 5: to be able to build products that work for everybody,

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Speaker 5: and that has always been our intention.

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Speaker 4: It continues to be our intention.

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Speaker 5: I think that you know, there were so many programs

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Speaker 5: that we launched and other companies launched in the pandemic,

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Speaker 5: and as you probably have seen over the last three years,

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Speaker 5: we've gone through very thoroughly every single one of our

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Speaker 5: business areas, and the programs that we had conviction about.

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Speaker 4: We doubled down on, and the programs that we don't have.

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Speaker 5: Conviction about, we streamline and we stopped doing. And so

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Speaker 5: we did the same thing and looking at all of

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Speaker 5: our programs on diversity, and you know, we have some

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Speaker 5: programs that we have doubled down on. A good example

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Speaker 5: is our Career Choice inside our Fulfillment Network our Fulfillment Center,

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Speaker 5: teammates are able to get an advanced education for free

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Speaker 5: on us to advance their career and their own development.

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Speaker 5: And that has been very, very successful and very meaningful,

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Speaker 5: and so we doubled down our program like that.

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Speaker 4: There are other programs.

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Speaker 5: That really just haven't been that successful and haven't moved

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Speaker 5: the needle much, and those we just moved away from.

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Speaker 5: But we have a diverse group we're trying to continue

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Speaker 5: to build out a diverse group and that won't change.

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Speaker 2: And you can't can still use that word ultimately not

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Speaker 2: having to reframe it.

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Speaker 4: That is.

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Speaker 5: I mean, look, you can call lots of people, call

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Speaker 5: lots of different things, but we have a giant customer

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Speaker 5: base of every imaginable group of people where we want

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Speaker 5: builders who can build for them.

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Speaker 2: Culture is key. Yeah, and you just talked about how

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Speaker 2: you're doing mores less. It's always a focus on frugality.

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Speaker 2: That's in your very principles. That's something you've been doing

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Speaker 2: at the employee base as well. You wrote out made

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Speaker 2: it very clear that they were going to be reducing layers.

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Speaker 2: How is that going?

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Speaker 4: Yeah, it's gone well.

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Speaker 5: You know, I look, if you have a company where

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Speaker 5: the culture is an important ingredient in your success, which

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Speaker 5: has absolutely been true for Amazon, it's not your birth

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Speaker 5: rate to keep having a strong culture, you know, especially

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Speaker 5: as you grow the number of people, the number of

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Speaker 5: businesses you're in, the geographies that you're in, and so

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Speaker 5: you have to work at it all the time. And

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Speaker 5: for us, you know, there were two areas when we

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Speaker 5: looked at it as a leadership team last year that

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Speaker 5: we wanted to strengthen. One was we have always fired

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Speaker 5: really strong owners, smart ambitious, strong owners who get to

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Speaker 5: own the allion's share of In this case, you know,

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Speaker 5: I would say, you know ninety plus percent of the decisions,

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Speaker 5: and they.

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Speaker 4: You know, as you add a.

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Speaker 5: Lot of people, you end up with a lot of

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Speaker 5: middle managers. And those middle managers, all well intended, want

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Speaker 5: to put their fingerprint on everything, So you end up

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Speaker 5: with these people being in the pre meeting for the

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Speaker 5: pre meeting, for the pre meeting for the decision meeting,

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Speaker 5: and not always making recommendations and owning things.

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Speaker 4: The way we want that type of ownership.

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Speaker 5: So we took a goal collectively to increase the ratio

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Speaker 5: of individual contributors to managers by over fifteen percent as

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Speaker 5: a company by the end of this quarter. We've made

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Speaker 5: very good progress in that we've beat that already and

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Speaker 5: it's going to allow us for the people that are

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Speaker 5: doing the work, they're going to have more ownership and they're.

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Speaker 4: Going to be able to move more quickly.

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Speaker 5: And then I think the other thing we saw was

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Speaker 5: that if you're a culture that invents a lot and

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Speaker 5: collaborates a lot like we do, if you don't have

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Speaker 5: people in the office together doing that invention, it's just

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Speaker 5: meaningfully worse. And you know, you don't invent the same way,

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Speaker 5: you don't collaborate the same way, you don't connect with

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Speaker 5: each other the same way, you.

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Speaker 4: Don't learn the culture the same way.

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Speaker 5: And so having people back in the office together more frequently,

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Speaker 5: we felt very strong.

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Speaker 4: We bet it's going to be better for customers in

445
00:21:19,600 --> 00:21:20,040
Speaker 4: the business.

446
00:21:20,400 --> 00:21:23,880
Speaker 2: Let's talk about that invention and that collaboration. We've got

447
00:21:23,880 --> 00:21:27,119
Speaker 2: a new quantum chip us alot love the name. What

448
00:21:27,200 --> 00:21:29,360
Speaker 2: does that mean for you to have this more efficient

449
00:21:29,440 --> 00:21:32,280
Speaker 2: chip at this exact moment. Will we start seeing it

450
00:21:32,280 --> 00:21:33,680
Speaker 2: be practically useful soon?

451
00:21:34,160 --> 00:21:38,439
Speaker 5: Welltum quantum computing is very high potential. It has the

452
00:21:38,600 --> 00:21:43,719
Speaker 5: chance to solve some very computationally intense problems, and I

453
00:21:43,760 --> 00:21:48,000
Speaker 5: still think it's realistically a few years away from having

454
00:21:48,000 --> 00:21:49,919
Speaker 5: a real shot at solving those problems. But you have

455
00:21:49,960 --> 00:21:53,480
Speaker 5: to solve a bunch of these challenges that relate to

456
00:21:53,520 --> 00:21:56,440
Speaker 5: quantum computing along the way, and one of them really

457
00:21:56,520 --> 00:21:59,280
Speaker 5: is around error correction on the cubits and that's what

458
00:21:59,359 --> 00:22:02,399
Speaker 5: Osilla does. It's a very unique inventive way to do

459
00:22:02,520 --> 00:22:05,560
Speaker 5: error correction with CUBIS that makes a meaningful difference, and

460
00:22:05,840 --> 00:22:08,600
Speaker 5: we're excited about that milestone. You can't get to something

461
00:22:08,600 --> 00:22:11,280
Speaker 5: that has real impact unless you get those milestones done

462
00:22:11,320 --> 00:22:13,040
Speaker 5: along the way, and you invent along the way.

463
00:22:13,040 --> 00:22:14,600
Speaker 4: And it's just another example of invention.

464
00:22:15,040 --> 00:22:19,000
Speaker 2: I feel the learning of how generative AI suddenly became

465
00:22:19,640 --> 00:22:23,760
Speaker 2: not just in the business parlay, but suddenly everyone was

466
00:22:23,800 --> 00:22:27,000
Speaker 2: discussing it. I think people are aware quantum could do

467
00:22:27,119 --> 00:22:29,560
Speaker 2: the same thing. So when you hear people debating between

468
00:22:29,600 --> 00:22:31,600
Speaker 2: two decades or five years, where do you sit on

469
00:22:31,640 --> 00:22:32,639
Speaker 2: the grounder scope of that?

470
00:22:33,960 --> 00:22:36,560
Speaker 4: Gosh, you know, I don't know for sure.

471
00:22:37,240 --> 00:22:40,200
Speaker 5: You know, I would say I'm hopeful that it's more

472
00:22:40,240 --> 00:22:42,720
Speaker 5: in the five ish year range than it is the

473
00:22:42,800 --> 00:22:45,399
Speaker 5: twenty year range. You know, all these things that are

474
00:22:45,440 --> 00:22:50,240
Speaker 5: successful are seven, ten, twenty year overnight successes. You know,

475
00:22:50,240 --> 00:22:52,280
Speaker 5: it wasn't like you know, if you look at gener

476
00:22:52,320 --> 00:22:55,400
Speaker 5: of AI, it's just kind of another evolution of AI.

477
00:22:55,520 --> 00:22:58,840
Speaker 5: But we've been working on AI for fifty some odd years.

478
00:22:58,880 --> 00:23:01,880
Speaker 5: I mean, like just boom, it happened, and it really

479
00:23:01,880 --> 00:23:04,720
Speaker 5: shocked us when it actually was more accessible and worked.

480
00:23:05,320 --> 00:23:06,880
Speaker 4: And I think the same thing.

481
00:23:06,720 --> 00:23:09,000
Speaker 5: Could happen with quantum computing, which is you know, takes

482
00:23:09,040 --> 00:23:11,080
Speaker 5: a long time, takes a long time, takes a long

483
00:23:11,119 --> 00:23:13,600
Speaker 5: and then all of a sudden, it's functional and solves

484
00:23:13,640 --> 00:23:17,320
Speaker 5: problems that you couldn't solve easily or cost effectively before.

485
00:23:17,359 --> 00:23:19,800
Speaker 5: And it just feels like it happened overnight. But quantum

486
00:23:19,840 --> 00:23:22,520
Speaker 5: computing we've been working on now for ten post years.

487
00:23:22,840 --> 00:23:25,840
Speaker 2: And then the euphoria comes, and then people try to

488
00:23:25,920 --> 00:23:29,160
Speaker 2: make head or tail of how long that eu floria lasts.

489
00:23:30,119 --> 00:23:32,440
Speaker 2: Going back to the investment that you make, and particularly

490
00:23:32,480 --> 00:23:34,520
Speaker 2: in generous AI, do you think it's going to be

491
00:23:34,560 --> 00:23:37,760
Speaker 2: peak year for generative AI in terms of that investment

492
00:23:37,760 --> 00:23:40,119
Speaker 2: that Amazon makes, I don't know.

493
00:23:40,160 --> 00:23:40,879
Speaker 4: You know, it's funny.

494
00:23:41,119 --> 00:23:45,240
Speaker 5: I have this feeling that you're going to end up

495
00:23:45,280 --> 00:23:48,919
Speaker 5: with some people that feel disillusioned about gender AI because

496
00:23:49,040 --> 00:23:50,000
Speaker 5: the investment or.

497
00:23:50,000 --> 00:23:52,720
Speaker 4: You getting the commensurate return. It's still very early.

498
00:23:52,760 --> 00:23:55,080
Speaker 5: You have so many companies that are really doing pilots

499
00:23:55,160 --> 00:23:58,440
Speaker 5: right now their gender of AI applications, and you already.

500
00:23:58,200 --> 00:23:59,199
Speaker 4: See a little bit of it.

501
00:24:00,280 --> 00:24:03,840
Speaker 5: But I think that the smart companies are going to

502
00:24:03,840 --> 00:24:07,159
Speaker 5: figure out which are the initiatives that can really change

503
00:24:07,200 --> 00:24:09,840
Speaker 5: their customer experience and their businesses and keep investing in

504
00:24:09,880 --> 00:24:15,080
Speaker 5: general AI and the slower companies are going to wait

505
00:24:15,119 --> 00:24:17,440
Speaker 5: to see if it's safe to go outside, and they'll

506
00:24:17,480 --> 00:24:20,440
Speaker 5: be behind by two or three years, maybe more because

507
00:24:20,480 --> 00:24:24,200
Speaker 5: the reality is even more soll than software development, general

508
00:24:24,200 --> 00:24:27,600
Speaker 5: of AI is very iterative. It's not on software development.

509
00:24:27,680 --> 00:24:29,399
Speaker 5: You can get on a whiteboard with a team of

510
00:24:29,520 --> 00:24:32,360
Speaker 5: architects and design something and maybe it doesn't work exactly

511
00:24:32,400 --> 00:24:35,119
Speaker 5: as you design it, but largely you know, whereas in

512
00:24:35,200 --> 00:24:38,760
Speaker 5: general of AI, the models they get better at kind

513
00:24:38,800 --> 00:24:41,960
Speaker 5: of disproportionate rates, sometimes scaling low.

514
00:24:42,040 --> 00:24:43,359
Speaker 2: Have We've got a new scaling law Stu.

515
00:24:43,520 --> 00:24:45,800
Speaker 5: I mean, I think that a lot of times when

516
00:24:45,800 --> 00:24:47,920
Speaker 5: you're building models and the model gets so much better

517
00:24:47,960 --> 00:24:49,960
Speaker 5: and you talk to the scientists and the team, they

518
00:24:50,000 --> 00:24:51,800
Speaker 5: just can't believe how much better it got because the

519
00:24:51,800 --> 00:24:55,160
Speaker 5: model is learning itself. And so I think that if

520
00:24:55,160 --> 00:24:57,800
Speaker 5: you actually aren't investing in general AI, you're going to

521
00:24:57,840 --> 00:25:00,480
Speaker 5: be behind by even the amount of time that you weighted,

522
00:25:00,880 --> 00:25:03,600
Speaker 5: because there are so many lessons you get from iterating

523
00:25:03,640 --> 00:25:05,320
Speaker 5: and building applications.

524
00:25:04,680 --> 00:25:07,800
Speaker 2: Today, and you want to be the supermarket of AI

525
00:25:08,119 --> 00:25:10,919
Speaker 2: feels like agnostic to the models, as it is with

526
00:25:11,040 --> 00:25:12,160
Speaker 2: Amazon alexiplus.

527
00:25:12,520 --> 00:25:15,840
Speaker 5: Well, you know, look, the truth is what we care

528
00:25:15,920 --> 00:25:18,840
Speaker 5: most about in all our businesses, but as it relates

529
00:25:18,840 --> 00:25:21,879
Speaker 5: to a WS and AI, we want our customers to

530
00:25:21,920 --> 00:25:24,680
Speaker 5: be able to change their customer experiences and improve their

531
00:25:24,720 --> 00:25:28,040
Speaker 5: businesses so they can last over a long period time successfully.

532
00:25:28,080 --> 00:25:30,680
Speaker 5: And if we do right by our customers and take

533
00:25:30,680 --> 00:25:32,200
Speaker 5: the long term approach we do.

534
00:25:32,600 --> 00:25:34,520
Speaker 4: And they're able to run their.

535
00:25:34,400 --> 00:25:38,840
Speaker 5: Applications successfully on top of our technology infrastructure services, then

536
00:25:38,920 --> 00:25:41,480
Speaker 5: they're successful and we ride along with them. And so

537
00:25:41,880 --> 00:25:44,520
Speaker 5: you know, we in all these areas, we have services

538
00:25:44,560 --> 00:25:47,040
Speaker 5: we build ourselves. In the models area, we have Amazon Nova,

539
00:25:47,080 --> 00:25:50,320
Speaker 5: which people are really excited about because it's got comparable

540
00:25:50,480 --> 00:25:52,560
Speaker 5: intelligence to the leading models in the world, but it's

541
00:25:52,960 --> 00:25:55,000
Speaker 5: meaningfully less expensive and lower latency.

542
00:25:55,440 --> 00:25:57,440
Speaker 4: But if customers prefer to run.

543
00:25:57,320 --> 00:26:00,520
Speaker 5: Other models, we have huge partnership with Anthropic and Lama

544
00:26:00,640 --> 00:26:04,399
Speaker 5: and Deep Mistraw Deep Seeg. I mean, we have the

545
00:26:04,560 --> 00:26:07,800
Speaker 5: largest collection of leading foundation models in the world and

546
00:26:07,880 --> 00:26:11,359
Speaker 5: if customers are having success with those, then we're happy.

547
00:26:11,400 --> 00:26:13,080
Speaker 5: And the truth is, if you build a lot of

548
00:26:13,119 --> 00:26:16,680
Speaker 5: general of AI applications, people don't realize this. You use

549
00:26:16,960 --> 00:26:20,840
Speaker 5: multiple model types often in the same application. Even Alexa Plus,

550
00:26:20,840 --> 00:26:24,199
Speaker 5: as we talked about using multiple foundation models, and so

551
00:26:24,720 --> 00:26:28,320
Speaker 5: we want people to use the right model for their applications,

552
00:26:28,400 --> 00:26:30,320
Speaker 5: and then we make it easy for them to switch

553
00:26:30,359 --> 00:26:33,760
Speaker 5: between them and run it easily and successfully in AWS.

554
00:26:33,800 --> 00:26:37,160
Speaker 2: Andy Jesse, perfect place to leave it. Start with alexaplus

555
00:26:37,240 --> 00:26:40,360
Speaker 2: and non Alexa plus and all the generation and generative

556
00:26:40,400 --> 00:26:42,160
Speaker 2: AI that comes with it. We thank you so much,

557
00:26:42,240 --> 00:26:45,480
Speaker 2: thanks for having me, Andy Jesse, President and CEO of Amazon.

558
00:26:46,359 --> 00:26:49,440
Speaker 2: We're going to be right back talking more around what's

559
00:26:49,440 --> 00:26:51,399
Speaker 2: happening with then. As that one hundred under pressure is

560
00:26:51,440 --> 00:26:54,879
Speaker 2: in video sells us post its numbers, what Solace did

561
00:26:54,920 --> 00:26:57,000
Speaker 2: in video give to its in besta base when it

562
00:26:57,040 --> 00:27:07,520
Speaker 2: comes to generative AI adoption. Welcome back to mine mag techn.

563
00:27:07,359 --> 00:27:09,720
Speaker 3: On a jam Cautline hid to New York and I'm

564
00:27:09,760 --> 00:27:11,240
Speaker 3: Jackie Devllas in San Francisco.

565
00:27:11,359 --> 00:27:12,600
Speaker 2: Let's get a check on the markets.

566
00:27:13,000 --> 00:27:15,679
Speaker 3: The Nasdaq one hundred is down on the day about

567
00:27:15,680 --> 00:27:18,680
Speaker 3: five tenths of one percent, reflecting this tepid sentiment coming

568
00:27:18,720 --> 00:27:21,320
Speaker 3: out of earnings, and that's after results in some cloud

569
00:27:21,520 --> 00:27:24,920
Speaker 3: and chip players are leaving more questions than answers about

570
00:27:24,920 --> 00:27:28,800
Speaker 3: the longevity of the AI rally. We're also looking at Microsoft,

571
00:27:28,920 --> 00:27:31,600
Speaker 3: also down on the day about four tenths of one percent.

572
00:27:31,880 --> 00:27:35,960
Speaker 3: The company today urged the Trump administration to rethink regulations

573
00:27:35,960 --> 00:27:38,679
Speaker 3: that would cap the export of AI chips to what

574
00:27:38,720 --> 00:27:42,359
Speaker 3: it believes are vital markets. Microsoft argued those chip curbs

575
00:27:42,359 --> 00:27:45,879
Speaker 3: could for countries to turn to China for advanced chips. Broadly,

576
00:27:46,040 --> 00:27:48,880
Speaker 3: Microsoft is following a similar change as other tech stocks

577
00:27:48,960 --> 00:27:51,439
Speaker 3: that are showing the nees about whether AIS boom is

578
00:27:51,560 --> 00:27:55,520
Speaker 3: actually losing steam. Perhaps the most important barometer of that

579
00:27:55,680 --> 00:27:58,800
Speaker 3: is in video. Shares are also down today, reflecting these

580
00:27:58,840 --> 00:28:02,680
Speaker 3: concerns about profit margins that eclipsed a sales beat and

581
00:28:02,920 --> 00:28:06,800
Speaker 3: upbeat revenue forecast. Bloomberg's Ian King joins US now to

582
00:28:06,840 --> 00:28:08,919
Speaker 3: break down some of these results. I really want to

583
00:28:08,960 --> 00:28:11,960
Speaker 3: home in on what was really going on that probably

584
00:28:12,040 --> 00:28:15,399
Speaker 3: left investors feeling weary. It's newer line of chips Blackwell,

585
00:28:15,640 --> 00:28:18,200
Speaker 3: they're rolling out, but at what cost?

586
00:28:18,480 --> 00:28:20,439
Speaker 6: Yeah, I mean this is a continuation of what we

587
00:28:20,480 --> 00:28:23,520
Speaker 6: saw three months ago, where they're saying, look, everybody wants

588
00:28:23,520 --> 00:28:25,680
Speaker 6: these chips. We want to get them out as fast

589
00:28:25,680 --> 00:28:28,119
Speaker 6: as you possibly can. Guess what, It's more complicated. The

590
00:28:28,119 --> 00:28:30,760
Speaker 6: computers that are based on are way more complicated.

591
00:28:30,840 --> 00:28:31,840
Speaker 4: It's going to cost us.

592
00:28:31,760 --> 00:28:34,159
Speaker 6: More, but don't worry about it. Once we get to

593
00:28:34,240 --> 00:28:36,840
Speaker 6: full production everything, we'll come back on our margins or

594
00:28:37,000 --> 00:28:39,080
Speaker 6: go back cope. But at the same time, the margins

595
00:28:39,120 --> 00:28:40,560
Speaker 6: are still above seventy percent.

596
00:28:41,240 --> 00:28:44,240
Speaker 2: I mean, people would weep to have more than seventy

597
00:28:44,280 --> 00:28:47,800
Speaker 2: percent margins. And then we hear, of course from trying

598
00:28:47,800 --> 00:28:49,920
Speaker 2: to signal that they'll get back to mid seventy percent

599
00:28:50,200 --> 00:28:52,320
Speaker 2: by the end of the year. But when we've got

600
00:28:52,400 --> 00:28:55,520
Speaker 2: the market still skating on thin ice here in was

601
00:28:55,680 --> 00:29:00,400
Speaker 2: enough said about China? Was enough said about potential hits

602
00:29:00,480 --> 00:29:03,520
Speaker 2: to their future demand from competitors such as Amazon for example.

603
00:29:04,480 --> 00:29:07,400
Speaker 6: Yeah, I mean the world as as you're indicating the words,

604
00:29:07,400 --> 00:29:10,560
Speaker 6: several areas of concern coming into this, and the company

605
00:29:10,600 --> 00:29:14,240
Speaker 6: had clearly done their homework. They pretty much answered everything

606
00:29:14,560 --> 00:29:17,520
Speaker 6: in order and went at it pretty hard with statistics

607
00:29:17,520 --> 00:29:20,920
Speaker 6: and assertions. But at the same I mean underlying this, though,

608
00:29:21,000 --> 00:29:22,680
Speaker 6: is that this is a company that investors have got

609
00:29:22,760 --> 00:29:25,600
Speaker 6: used to actually having every innings be a blowout, and

610
00:29:25,640 --> 00:29:31,640
Speaker 6: this wasn't a blowout. This was just regular common garden brilliant. Right.

611
00:29:31,880 --> 00:29:35,480
Speaker 2: You said almost growth in revenue, Yeah, I mean.

612
00:29:35,400 --> 00:29:38,040
Speaker 6: We you know, one hundred and twenty our billion dollar company.

613
00:29:38,320 --> 00:29:40,160
Speaker 6: Two years ago, we were in the twenties.

614
00:29:40,240 --> 00:29:41,400
Speaker 4: Right in terms of revenue.

615
00:29:42,240 --> 00:29:46,400
Speaker 6: Margins are up you know, ten fifteen basis points from

616
00:29:46,480 --> 00:29:48,320
Speaker 6: where they were a couple of years ago.

617
00:29:48,400 --> 00:29:50,280
Speaker 4: So we're not suffering here.

618
00:29:50,320 --> 00:29:53,360
Speaker 6: But but we're just not surprising people on the upside

619
00:29:53,400 --> 00:29:53,840
Speaker 6: in the way that.

620
00:29:53,840 --> 00:29:54,280
Speaker 4: We used to.

621
00:29:54,680 --> 00:29:57,120
Speaker 3: And let's talk about what took in videos wind out

622
00:29:57,120 --> 00:29:59,920
Speaker 3: of its sales earlier this month. Last month when Deep

623
00:30:00,080 --> 00:30:02,960
Speaker 3: secretly came onto the scene, sparked a lot of concerns

624
00:30:02,960 --> 00:30:04,520
Speaker 3: that we might not need as many chips as we

625
00:30:04,560 --> 00:30:05,080
Speaker 3: thought we might.

626
00:30:05,280 --> 00:30:06,680
Speaker 2: What did the company have to say about that?

627
00:30:06,760 --> 00:30:07,480
Speaker 4: Yeah, I mean a.

628
00:30:07,440 --> 00:30:10,840
Speaker 6: Lot of what they had to say was clearly designed

629
00:30:10,880 --> 00:30:15,120
Speaker 6: to deal with that concern. And Jensen Wang, the CEO,

630
00:30:15,240 --> 00:30:17,040
Speaker 6: what he was saying is like, look, this is a

631
00:30:17,080 --> 00:30:19,000
Speaker 6: new way of doing things, but don't worry. Our chips

632
00:30:19,040 --> 00:30:20,880
Speaker 6: are really good at that as well. And guess what,

633
00:30:21,040 --> 00:30:22,880
Speaker 6: in the end, this is going to speed everything up.

634
00:30:22,960 --> 00:30:25,400
Speaker 6: Everybody's going to be flowing into this way of doing things.

635
00:30:25,400 --> 00:30:27,600
Speaker 6: This is good for everybody. And he gave a lot

636
00:30:27,600 --> 00:30:30,479
Speaker 6: of technical explanations that were obviously self serving but at

637
00:30:30,520 --> 00:30:33,320
Speaker 6: the same time logical and reason that that appeared to

638
00:30:33,360 --> 00:30:36,320
Speaker 6: sort of slay that dragon. But again, you know, the

639
00:30:36,400 --> 00:30:38,640
Speaker 6: numbers are what people really focus on.

640
00:30:39,320 --> 00:30:42,600
Speaker 2: What's so interesting is at this time we're wondering about

641
00:30:42,600 --> 00:30:45,880
Speaker 2: what the administration means for Nvideo, for its access to

642
00:30:46,320 --> 00:30:49,760
Speaker 2: selling chips to China but also to allies. And we've

643
00:30:49,800 --> 00:30:53,160
Speaker 2: got this push from Microsoft today Brad Smith calling on

644
00:30:53,200 --> 00:30:58,280
Speaker 2: the administration to basically avoid this focus on AI diffusion

645
00:30:58,840 --> 00:31:01,960
Speaker 2: rule as was in Poe. What do you think Jensen's

646
00:31:02,000 --> 00:31:03,600
Speaker 2: reaction would be to Microsoft letter.

647
00:31:05,320 --> 00:31:08,240
Speaker 6: I mean you could argue that, you know, in Video

648
00:31:08,560 --> 00:31:10,760
Speaker 6: kind of the precursor to this sentiment, and you got

649
00:31:10,800 --> 00:31:13,360
Speaker 6: a little bit of that from Aws as well. I mean,

650
00:31:13,360 --> 00:31:16,520
Speaker 6: the fundamental argument here is like if you hobble, if

651
00:31:16,520 --> 00:31:19,920
Speaker 6: your efforts to hobble China are totally successful, guess what

652
00:31:20,200 --> 00:31:23,600
Speaker 6: it might backfire. It might hobble us, it might hurt

653
00:31:23,640 --> 00:31:27,120
Speaker 6: our research and development budgets, it might hurt our end

654
00:31:27,160 --> 00:31:30,480
Speaker 6: market access, and eventually China is going to be so

655
00:31:30,640 --> 00:31:33,120
Speaker 6: motivated that they're going to get there themselves and we'll

656
00:31:33,160 --> 00:31:36,400
Speaker 6: have no play there and we'll have created a monster

657
00:31:36,440 --> 00:31:39,520
Speaker 6: that we can't control. That's the fundamental argument that's been

658
00:31:39,560 --> 00:31:42,520
Speaker 6: given in different ways and Invidia has been definitely one

659
00:31:42,560 --> 00:31:45,440
Speaker 6: of the ones that's been voicing that m Magsie and

660
00:31:45,520 --> 00:31:46,400
Speaker 6: King brilliant.

661
00:31:46,400 --> 00:31:48,440
Speaker 2: To wrap it up with you, thank you. Let's bring

662
00:31:48,440 --> 00:31:50,800
Speaker 2: in the invested tate now. Ioka, Yoshioka is with US

663
00:31:50,800 --> 00:31:53,760
Speaker 2: portfolio manager at Wealth Enhancement Group. Let's just go back

664
00:31:53,800 --> 00:31:56,960
Speaker 2: to the fundamentals of Nvidia's business right now. What did

665
00:31:57,000 --> 00:31:59,000
Speaker 2: you make of the numbers? Was they're not enough there

666
00:31:59,040 --> 00:32:01,160
Speaker 2: to excite you at this three trillion evaluation?

667
00:32:02,480 --> 00:32:05,760
Speaker 7: Hi, Caroline, you know, we think we thought the results

668
00:32:05,760 --> 00:32:07,800
Speaker 7: were actually pretty much in line with what we were

669
00:32:07,840 --> 00:32:11,200
Speaker 7: expecting and maybe slightly better. You know, it's just that

670
00:32:11,680 --> 00:32:16,000
Speaker 7: in this environment where there's so much uncertainty in the markets,

671
00:32:16,240 --> 00:32:19,120
Speaker 7: you know, people are just a little skittish about just

672
00:32:19,560 --> 00:32:22,160
Speaker 7: waiting and being a little bit more patient to see

673
00:32:22,640 --> 00:32:24,640
Speaker 7: some of these numbers come through. I mean, they did

674
00:32:24,680 --> 00:32:28,440
Speaker 7: talk about how margins will expand in the second half

675
00:32:29,080 --> 00:32:32,800
Speaker 7: once Blackwell becomes a greater portion of the mix, but

676
00:32:33,000 --> 00:32:35,720
Speaker 7: you know, people are a little bit impatient in this environment.

677
00:32:36,800 --> 00:32:38,120
Speaker 2: Ayaka, what do you make.

678
00:32:37,960 --> 00:32:41,560
Speaker 3: Of the company already starting to talk about its next

679
00:32:42,160 --> 00:32:45,000
Speaker 3: model of AI chips, the rubenschip. I mean, it just

680
00:32:45,040 --> 00:32:47,320
Speaker 3: seems like a lot of these newer models are just

681
00:32:47,360 --> 00:32:50,400
Speaker 3: coming out really fast. Do you think that's going to

682
00:32:50,400 --> 00:32:53,800
Speaker 3: be a longer term drag on margins or even risk

683
00:32:53,920 --> 00:32:55,080
Speaker 3: exhausting customers.

684
00:32:56,480 --> 00:32:58,560
Speaker 7: I think so, And I think we see this just

685
00:32:58,680 --> 00:33:01,600
Speaker 7: in the sort of end use case and how quickly

686
00:33:01,640 --> 00:33:05,479
Speaker 7: we can adopt AI into all of our everyday lives.

687
00:33:05,680 --> 00:33:08,320
Speaker 7: I mean, Amazon's a perfect example of how they're trying

688
00:33:08,360 --> 00:33:13,320
Speaker 7: to incorporate more agentic AI into our lives through Alexa Plus.

689
00:33:13,880 --> 00:33:16,600
Speaker 7: But know, we have to see this in more areas,

690
00:33:16,760 --> 00:33:20,600
Speaker 7: and consumer behavior is really slow to change when it

691
00:33:20,640 --> 00:33:23,280
Speaker 7: comes to adopting new technology, and so we've got to

692
00:33:23,520 --> 00:33:29,040
Speaker 7: really see the pace of consumer demand and enterprise demand

693
00:33:29,200 --> 00:33:34,000
Speaker 7: really match the build out of AI. But the structure,

694
00:33:34,080 --> 00:33:36,760
Speaker 7: the underlying infrastructure of AI is going to take a

695
00:33:36,800 --> 00:33:41,680
Speaker 7: lot more compute power, as jensen As has mentioned, and

696
00:33:41,720 --> 00:33:43,640
Speaker 7: so that's going to continue, I think. In order to

697
00:33:43,640 --> 00:33:46,280
Speaker 7: just set the stage, what did you make of.

698
00:33:46,240 --> 00:33:49,520
Speaker 3: The company's comments around inferencing and its ability to really

699
00:33:49,560 --> 00:33:52,640
Speaker 3: take advantage of this next frontier where a lot of

700
00:33:52,680 --> 00:33:55,040
Speaker 3: these new reasoning models are going to depend on this

701
00:33:55,160 --> 00:33:58,640
Speaker 3: type of training. Are you confident that the company is

702
00:33:58,680 --> 00:34:01,960
Speaker 3: poised to really benefit from that, you.

703
00:34:01,920 --> 00:34:05,480
Speaker 7: Know, I think I won't doubt Jensen and you know,

704
00:34:05,560 --> 00:34:10,600
Speaker 7: the technological advances that he's been able to create at Nvidia,

705
00:34:10,960 --> 00:34:13,640
Speaker 7: and I do believe that just the overall you know,

706
00:34:14,000 --> 00:34:18,760
Speaker 7: inferencing market and just all the reasoning, just the amount

707
00:34:18,800 --> 00:34:21,400
Speaker 7: of compute that they talked about, you know, one hundred

708
00:34:21,440 --> 00:34:24,839
Speaker 7: times more compute power needed in order to do all

709
00:34:24,880 --> 00:34:27,360
Speaker 7: the reasoning behind the scenes. I do believe that that

710
00:34:27,600 --> 00:34:30,759
Speaker 7: is probably the right direction. I know there was a

711
00:34:30,760 --> 00:34:33,680
Speaker 7: lot of concern when deep seat came out, but you know,

712
00:34:33,719 --> 00:34:36,000
Speaker 7: I think this is just a new level and another

713
00:34:36,160 --> 00:34:39,960
Speaker 7: area that AI is going to continue to proliferate, you know,

714
00:34:40,000 --> 00:34:42,080
Speaker 7: in more use cases for AI.

715
00:34:43,280 --> 00:34:46,520
Speaker 2: There are these limitations though, I think and agreed Jensen

716
00:34:46,520 --> 00:34:48,960
Speaker 2: Wang did a lot to talk around these new scaling

717
00:34:49,040 --> 00:34:53,400
Speaker 2: laws that come with the latest and greatest models and reasoning.

718
00:34:53,719 --> 00:34:56,760
Speaker 2: He didn't really talk to those some of the geopolitical

719
00:34:56,760 --> 00:34:59,600
Speaker 2: limitations right now, and when you've got Microsoft coming out

720
00:34:59,600 --> 00:35:02,239
Speaker 2: brad with asking the government to basically do away with

721
00:35:02,280 --> 00:35:06,719
Speaker 2: Biden's AI diffusion rule to allow companies to sell globally

722
00:35:06,920 --> 00:35:11,640
Speaker 2: with ease, is that something that you're thinking about absolutely?

723
00:35:11,760 --> 00:35:13,680
Speaker 7: I think even you know, when you go back to

724
00:35:13,840 --> 00:35:17,319
Speaker 7: when deep seeks you know news came out and really

725
00:35:17,360 --> 00:35:21,360
Speaker 7: impacted the whole sector. It really goes to show the

726
00:35:21,840 --> 00:35:25,879
Speaker 7: arms race or the AI race that's in hand at

727
00:35:25,880 --> 00:35:28,919
Speaker 7: the moment. And you know, it is critical and really

728
00:35:28,960 --> 00:35:31,759
Speaker 7: important for the US to be you know, in that

729
00:35:31,840 --> 00:35:34,640
Speaker 7: pole position. And I think that's what's going on here,

730
00:35:34,680 --> 00:35:37,480
Speaker 7: and we'd like to get as many you know, friendly

731
00:35:37,800 --> 00:35:42,239
Speaker 7: faces on board with how we the United States and

732
00:35:42,360 --> 00:35:46,120
Speaker 7: Nvidia and other chip companies are deploying.

733
00:35:45,760 --> 00:35:50,080
Speaker 2: AI okay pole positions. Then which companies are in the

734
00:35:50,080 --> 00:35:52,560
Speaker 2: pole positions for you right now? Which ones do you

735
00:35:52,560 --> 00:35:54,040
Speaker 2: want to be adding to at this moment?

736
00:35:55,280 --> 00:35:55,560
Speaker 4: Sure?

737
00:35:55,640 --> 00:35:58,440
Speaker 7: So, I mean I think you know, from a tech standpoint,

738
00:35:59,200 --> 00:36:01,600
Speaker 7: you still want to have some of the big tech names.

739
00:36:01,640 --> 00:36:04,319
Speaker 7: You know, in Vidia, we're not selling any Nvidia at

740
00:36:04,320 --> 00:36:06,880
Speaker 7: the moment. We know it's been range bound for a while.

741
00:36:07,000 --> 00:36:09,680
Speaker 7: We do believe in the long term it will continue

742
00:36:09,719 --> 00:36:13,640
Speaker 7: to grow. Broad prom is another name in Microsoft as well.

743
00:36:13,680 --> 00:36:16,200
Speaker 7: I mean, Microsoft is you know, at the forefront here

744
00:36:16,360 --> 00:36:21,840
Speaker 7: pushing for you know, additional globalization of their technology and

745
00:36:22,200 --> 00:36:25,799
Speaker 7: allowing for their technology to be more ubiquitous so that

746
00:36:25,880 --> 00:36:28,840
Speaker 7: they can again you know, everybody wants to be in

747
00:36:28,840 --> 00:36:30,640
Speaker 7: that cole position, and I think we want to put

748
00:36:30,680 --> 00:36:31,480
Speaker 7: America first.

749
00:36:32,440 --> 00:36:35,399
Speaker 3: That's a Yako Yoshioka from the Wealth Enhancement Group things

750
00:36:35,400 --> 00:36:36,080
Speaker 3: for joining.

751
00:36:35,920 --> 00:36:46,520
Speaker 2: US shares a salesforce under pressure. The company telling investors

752
00:36:46,520 --> 00:36:49,160
Speaker 2: on its earning school yesterday that it expects its AI

753
00:36:49,280 --> 00:36:52,480
Speaker 2: product Agent Fools to give just a modest contribution to

754
00:36:52,520 --> 00:36:55,920
Speaker 2: twenty twenty six revenue. That's unpacket all with Alex Okin

755
00:36:56,239 --> 00:36:59,880
Speaker 2: of Wolf Research, Alex, look, the full cost was what

756
00:37:00,040 --> 00:37:02,560
Speaker 2: red people here? Forty point five to forty point nine

757
00:37:02,600 --> 00:37:06,760
Speaker 2: billion dollars? Is Agent Force just not bring enough force

758
00:37:06,880 --> 00:37:07,600
Speaker 2: quickly enough?

759
00:37:08,320 --> 00:37:11,640
Speaker 8: Look, I think with new innovations like Agent Force, particularly

760
00:37:11,680 --> 00:37:14,480
Speaker 8: when you're dealing with very large, complicated customers, a lot

761
00:37:14,520 --> 00:37:17,240
Speaker 8: of times in regulated industries, you want to be slow.

762
00:37:17,400 --> 00:37:19,560
Speaker 8: You want to be methodical, you want to really be

763
00:37:19,680 --> 00:37:22,120
Speaker 8: in there and delivering value, but you want to be conservative.

764
00:37:22,360 --> 00:37:24,719
Speaker 8: And I think that's that's a feature, that's not a bug.

765
00:37:24,719 --> 00:37:27,960
Speaker 8: And I think investors generally speaking, they've seen this movie

766
00:37:27,960 --> 00:37:32,040
Speaker 8: before with the Arrival of the Cloud, where it does

767
00:37:32,120 --> 00:37:34,640
Speaker 8: take time, and I think with Agent Force, we would

768
00:37:34,680 --> 00:37:36,920
Speaker 8: expect it to be less than a point of contribution.

769
00:37:37,680 --> 00:37:41,600
Speaker 8: A lot of times you're seeing companies start small, experiment

770
00:37:41,760 --> 00:37:44,160
Speaker 8: and then have the ability to get a lot bigger.

771
00:37:44,800 --> 00:37:46,680
Speaker 8: I think it's also important to remember there's a labor,

772
00:37:49,120 --> 00:37:51,880
Speaker 8: there's a there's a labor, not cost, but there's a

773
00:37:51,920 --> 00:37:54,160
Speaker 8: problem here where you want to be very careful and

774
00:37:54,239 --> 00:37:57,000
Speaker 8: nuanced in how you treat this innovation because it can

775
00:37:57,040 --> 00:38:00,319
Speaker 8: be disruptive to culture, and so you want to really

776
00:38:00,440 --> 00:38:03,880
Speaker 8: have a great sense of what's durable, what's reliable, and

777
00:38:03,880 --> 00:38:06,960
Speaker 8: then what's transferable. And I think Salesforce is kind of

778
00:38:06,960 --> 00:38:09,600
Speaker 8: in the mix and in the middle of really driving

779
00:38:09,640 --> 00:38:12,560
Speaker 8: that massive innovation for these customers.

780
00:38:12,800 --> 00:38:16,160
Speaker 2: Let's talk about Salesforce's own labor quandary, because not only

781
00:38:16,200 --> 00:38:17,960
Speaker 2: they're having to get rid of some to put in

782
00:38:18,040 --> 00:38:21,600
Speaker 2: more AI talent, they're also having a real change of

783
00:38:21,640 --> 00:38:24,040
Speaker 2: ship in terms of the executive level. What do you

784
00:38:24,080 --> 00:38:25,120
Speaker 2: make of all the changes.

785
00:38:25,800 --> 00:38:29,000
Speaker 8: I think as companies get bigger and they evolve, it

786
00:38:29,080 --> 00:38:34,400
Speaker 8: creates the opportunity to attract new talent with different levels

787
00:38:34,400 --> 00:38:37,399
Speaker 8: of experience. I think Salesforce has done this probably better

788
00:38:37,440 --> 00:38:39,440
Speaker 8: than many other companies in the past. You've seen it

789
00:38:40,600 --> 00:38:44,319
Speaker 8: as they went through multiple very senior co CEOs like

790
00:38:44,400 --> 00:38:48,200
Speaker 8: Keith Block, like Brett Taylor injecting just the right amount

791
00:38:48,280 --> 00:38:51,319
Speaker 8: of stuff that the company needed at that time. I

792
00:38:51,320 --> 00:38:55,640
Speaker 8: think with the current change, I think Robin brings a

793
00:38:55,640 --> 00:38:58,640
Speaker 8: lot to the table. She really brings a lot of experience.

794
00:38:58,680 --> 00:39:02,120
Speaker 8: The new COFO as they call it, where she inhabits

795
00:39:02,280 --> 00:39:05,879
Speaker 8: both the COO and the CFO title. I think there's

796
00:39:05,880 --> 00:39:07,680
Speaker 8: a lot of opportunity with that change. I think it's

797
00:39:07,800 --> 00:39:10,960
Speaker 8: right for investors to understand that it's a little bit

798
00:39:11,000 --> 00:39:13,439
Speaker 8: riskier from an execution perspective, but they've got the right

799
00:39:13,560 --> 00:39:16,839
Speaker 8: set of hands on the controls to I think, get

800
00:39:16,840 --> 00:39:17,560
Speaker 8: you smooth sailing.

801
00:39:18,800 --> 00:39:23,719
Speaker 3: Alex Salesforce has been an evangelist for agents, and you know,

802
00:39:23,920 --> 00:39:27,520
Speaker 3: this is seen widely as like the next big application

803
00:39:27,719 --> 00:39:30,799
Speaker 3: that will actually justify just how much investment has gone

804
00:39:30,800 --> 00:39:32,960
Speaker 3: into the space, because it seemed to be useful like

805
00:39:33,000 --> 00:39:35,000
Speaker 3: things in customer service, you know, will be able to

806
00:39:35,000 --> 00:39:37,719
Speaker 3: be taken over by agents in the future. Are you

807
00:39:37,960 --> 00:39:41,520
Speaker 3: worried that what Salesforce said about it's demand for agent

808
00:39:41,600 --> 00:39:45,440
Speaker 3: force pretends something deeper about adoption going forward.

809
00:39:46,640 --> 00:39:49,160
Speaker 8: It's a great question, and I think that Salesforce is

810
00:39:49,200 --> 00:39:53,600
Speaker 8: not the first company to create a moniker around generator.

811
00:39:53,640 --> 00:39:56,200
Speaker 8: The utilization in the enterprise. I would say that goes

812
00:39:56,239 --> 00:39:59,120
Speaker 8: to Microsoft with Copilot, and I think Salesforce has a

813
00:39:59,160 --> 00:40:02,200
Speaker 8: real opportunity and they want to be very careful. They

814
00:40:02,200 --> 00:40:06,320
Speaker 8: want to go slow, they want to really double down.

815
00:40:06,120 --> 00:40:07,439
Speaker 2: On the successes that they're seeing.

816
00:40:07,480 --> 00:40:12,520
Speaker 8: And they talked about some pretty marquee large customers Singapore Airlines,

817
00:40:13,120 --> 00:40:17,200
Speaker 8: They talked about accenture. There were even examples with Open

818
00:40:17,239 --> 00:40:21,640
Speaker 8: Table and Sharkeningja where those companies actually discussed agent Force

819
00:40:21,719 --> 00:40:25,200
Speaker 8: on their own earnings calls. So I would view the

820
00:40:25,239 --> 00:40:28,359
Speaker 8: demand is off the charts, the fact that they went

821
00:40:28,440 --> 00:40:32,520
Speaker 8: from three hundred deals to three thousand deals in one quarter.

822
00:40:32,880 --> 00:40:34,399
Speaker 8: But I think you have to look at this over

823
00:40:34,440 --> 00:40:37,439
Speaker 8: a period of time where the amount of value that

824
00:40:37,520 --> 00:40:40,120
Speaker 8: these customers will be able to realize in their own

825
00:40:40,239 --> 00:40:42,640
Speaker 8: organizations and the amount that they will be willing to

826
00:40:42,680 --> 00:40:45,880
Speaker 8: pay to Salesforce versus the amount they currently pay, it

827
00:40:45,880 --> 00:40:47,960
Speaker 8: could be a meaningful multiple of that amount, but I

828
00:40:47,960 --> 00:40:49,080
Speaker 8: think it's going to take time.

829
00:40:49,760 --> 00:40:53,040
Speaker 3: Speaking of customers, Mark Benioff said that the Department of

830
00:40:53,080 --> 00:40:56,399
Speaker 3: Government Efficiency DOGE has actually been using slack for some.

831
00:40:56,360 --> 00:40:58,080
Speaker 2: Of its work. What did you make of that?

832
00:40:59,600 --> 00:41:02,839
Speaker 8: Sounds like they have a really good collaboration platform that

833
00:41:03,239 --> 00:41:06,920
Speaker 8: they acquired, and I think it part of the vision

834
00:41:07,160 --> 00:41:10,160
Speaker 8: for Salesforce. Part of the vision for Agent Force is

835
00:41:10,200 --> 00:41:13,800
Speaker 8: to have an ubiquitous communication platform because it has a

836
00:41:13,840 --> 00:41:16,480
Speaker 8: lot of data that's very relevant in a lot of workflows,

837
00:41:16,760 --> 00:41:21,600
Speaker 8: and the data model that Salesforce can effectively enrich by

838
00:41:21,640 --> 00:41:25,520
Speaker 8: having those conversations available directly in the application is going

839
00:41:25,560 --> 00:41:27,919
Speaker 8: to be important. So look, I look at this as

840
00:41:28,680 --> 00:41:33,120
Speaker 8: these people need to have relationships with everybody, and I

841
00:41:33,160 --> 00:41:36,200
Speaker 8: think that Mark talked a lot about how many administrations

842
00:41:36,400 --> 00:41:39,600
Speaker 8: he's worked with the company has worked with, so I

843
00:41:39,600 --> 00:41:41,480
Speaker 8: would view this as a positive for Salesforce.

844
00:41:45,560 --> 00:41:48,880
Speaker 3: Thanks Alex Zukan from Wolf Research. Appreciate you coming in

845
00:41:48,920 --> 00:41:51,640
Speaker 3: to unpack that for us. Turning to the entertainment sector,

846
00:41:51,719 --> 00:41:55,120
Speaker 3: Warner Brothers, Discovery and Paramount both at with their earnings.

847
00:41:55,560 --> 00:41:59,320
Speaker 3: Here to unpack them for us is Bloomberg's Hannah Miller. Hannah,

848
00:42:00,000 --> 00:42:01,680
Speaker 3: I think was a bright spot, which is something that

849
00:42:01,719 --> 00:42:03,960
Speaker 3: we haven't really heard that often when you look at

850
00:42:04,000 --> 00:42:06,200
Speaker 3: some of the streaming players out there in recent months.

851
00:42:06,200 --> 00:42:09,760
Speaker 3: What was driving the demand here and profits as well.

852
00:42:10,360 --> 00:42:13,520
Speaker 9: Yeah, So both Warner Brothers and Paramount focused on the

853
00:42:13,640 --> 00:42:16,440
Speaker 9: huge streaming gains that they had in the fourth quarter,

854
00:42:16,800 --> 00:42:18,160
Speaker 9: and they were kind of, you know, trying to draw

855
00:42:18,200 --> 00:42:20,800
Speaker 9: attention away from the fact that they missed on revenue

856
00:42:20,920 --> 00:42:24,200
Speaker 9: estimates and you know, are still struggling with their take

857
00:42:24,239 --> 00:42:28,279
Speaker 9: cable TV businesses. If you're looking at Warner Brothers with subscribers,

858
00:42:28,320 --> 00:42:31,839
Speaker 9: they did a huge international push early in twenty twenty four,

859
00:42:32,239 --> 00:42:35,040
Speaker 9: especially in Europe and Latin America, so that helped drive

860
00:42:35,080 --> 00:42:36,239
Speaker 9: subscriber gains for them.

861
00:42:36,719 --> 00:42:39,880
Speaker 2: It really was an international focus and subscribe as coming

862
00:42:39,920 --> 00:42:43,200
Speaker 2: up to one hundred and seventy million with the advertising

863
00:42:43,200 --> 00:42:46,279
Speaker 2: revenue really big void what then a Paramount because the

864
00:42:46,320 --> 00:42:49,239
Speaker 2: Paramount plus ads were good and better than expected, but

865
00:42:49,320 --> 00:42:50,440
Speaker 2: elsewhere fell Shure.

866
00:42:51,080 --> 00:42:54,319
Speaker 9: Yeah, I mean, Paramount really emphasized the fact that, you know,

867
00:42:54,360 --> 00:42:56,719
Speaker 9: their streaming business is growing, they are aiming to be

868
00:42:56,800 --> 00:42:59,439
Speaker 9: profitable by the end of this year, and they really

869
00:42:59,480 --> 00:43:01,920
Speaker 9: leaned on the that they have this wide range of content,

870
00:43:02,520 --> 00:43:06,200
Speaker 9: especially shows created by Taylor Sheridan, who is of Yellowstone

871
00:43:06,200 --> 00:43:09,080
Speaker 9: fame and has that hit success. So that's what they

872
00:43:09,120 --> 00:43:11,799
Speaker 9: really tried to push forward in their earnings, you know,

873
00:43:11,880 --> 00:43:14,879
Speaker 9: again drawing attention away from the fact that their TV

874
00:43:14,960 --> 00:43:18,600
Speaker 9: businesses are not doing as well as as they would hope.

875
00:43:19,040 --> 00:43:21,320
Speaker 3: And what did the company say about how it plans

876
00:43:21,360 --> 00:43:24,879
Speaker 3: to sustain some of that content generation because it's really

877
00:43:24,960 --> 00:43:27,920
Speaker 3: expensive to invest in and it takes time as well.

878
00:43:28,520 --> 00:43:31,040
Speaker 9: Yeah, I mean, Warner Brothers really emphasize this morning that

879
00:43:31,080 --> 00:43:33,279
Speaker 9: they have a diverse range of content. You know, they're

880
00:43:33,320 --> 00:43:37,239
Speaker 9: pulling from sports, They're doing scripted HBO shows. The White

881
00:43:37,239 --> 00:43:40,000
Speaker 9: Lotus came up. That's a big one. The Pit, a

882
00:43:40,040 --> 00:43:42,800
Speaker 9: new medical show, is also something that they're really pushing forward.

883
00:43:43,040 --> 00:43:45,000
Speaker 9: So they're really emphasizing the fact that they're willing to

884
00:43:45,040 --> 00:43:47,200
Speaker 9: invest in creative ideas and that this is how they're

885
00:43:47,200 --> 00:43:48,000
Speaker 9: gaining customers.

886
00:43:48,480 --> 00:43:52,399
Speaker 2: Annamella reappreciate it, thank you. Talking of creatives YouTube style,

887
00:43:52,480 --> 00:43:54,120
Speaker 2: mister Beast is seeking to raise a couple of one

888
00:43:54,200 --> 00:43:57,000
Speaker 2: hundred million dollars to expound his business in a funding

889
00:43:57,080 --> 00:43:59,400
Speaker 2: round that will value the company at about five billion dollars.

890
00:43:59,400 --> 00:44:02,440
Speaker 2: It's all according sources. Talk still in the early stages,

891
00:44:02,920 --> 00:44:06,319
Speaker 2: not yet clear who will invest. Coming up more on

892
00:44:06,360 --> 00:44:09,640
Speaker 2: Amazon's Alexa plus, It's Quantum computing chip announcement and more.

893
00:44:09,880 --> 00:44:22,239
Speaker 2: This is bluem Meg technology. So we kicked off this

894
00:44:22,320 --> 00:44:25,960
Speaker 2: show with Amazon CEO Andy Jasse joining on artificial intelligence.

895
00:44:26,200 --> 00:44:28,080
Speaker 2: And this is the company, of course, also just announced

896
00:44:28,080 --> 00:44:31,480
Speaker 2: its first quantum computing chip, will significant move, joining the

897
00:44:31,560 --> 00:44:33,880
Speaker 2: likes of Google and Microsoft, who also recently came out

898
00:44:33,920 --> 00:44:36,080
Speaker 2: with their own quantum hardware. Let's break it all down

899
00:44:36,080 --> 00:44:38,279
Speaker 2: on Bloomberg's mat day and first on the quantum chip.

900
00:44:38,440 --> 00:44:40,880
Speaker 2: They really are going for like efficiency once again, it's

901
00:44:40,960 --> 00:44:41,840
Speaker 2: kind of Amazon zmmo.

902
00:44:42,040 --> 00:44:43,920
Speaker 10: Oh, it's totally their playbook. They were talking about how

903
00:44:44,000 --> 00:44:46,120
Speaker 10: much they could reduce the overhead of building a quantum chip.

904
00:44:46,160 --> 00:44:48,000
Speaker 10: They were reminding us, hey, listen, if you actually build

905
00:44:48,040 --> 00:44:49,360
Speaker 10: one of these things in practice, might cost you a

906
00:44:49,360 --> 00:44:51,840
Speaker 10: billion dollars. So very wus playbook to say, listen, we

907
00:44:51,840 --> 00:44:53,520
Speaker 10: think we can build a cheaper mouse trap that might

908
00:44:53,520 --> 00:44:56,440
Speaker 10: get more more update, Matt, how much of.

909
00:44:56,400 --> 00:44:59,040
Speaker 3: This is just companies trying to plant a flag to

910
00:44:59,080 --> 00:45:01,640
Speaker 3: show that they're in the to computing game. Are we

911
00:45:01,680 --> 00:45:04,200
Speaker 3: actually expecting to see anything come out of this in

912
00:45:04,200 --> 00:45:05,160
Speaker 3: the short term?

913
00:45:05,280 --> 00:45:07,359
Speaker 10: Short term? I'm not so sure, but I think it's

914
00:45:07,440 --> 00:45:11,120
Speaker 10: notable talking about a ws's announcement this week that they said,

915
00:45:11,320 --> 00:45:14,040
Speaker 10: you know, a decade is maybe pretty aggressive, right, which

916
00:45:14,080 --> 00:45:16,560
Speaker 10: is a lot more sober than you had Microsoft a

917
00:45:16,560 --> 00:45:19,279
Speaker 10: few weeks back, saying years not decades. So there's there's

918
00:45:19,320 --> 00:45:21,239
Speaker 10: definitely a lot of positioning going on right now, but

919
00:45:21,480 --> 00:45:24,160
Speaker 10: you know, put abs down on more conservative sides, saying, listen,

920
00:45:24,160 --> 00:45:25,520
Speaker 10: there's still a whole lot of work to do. I

921
00:45:25,520 --> 00:45:27,680
Speaker 10: think the change that has happened is, you know, folks

922
00:45:27,719 --> 00:45:29,640
Speaker 10: are saying it's a win, not an if, and you're

923
00:45:29,680 --> 00:45:31,080
Speaker 10: hearing that really from around big tech.

924
00:45:31,800 --> 00:45:34,399
Speaker 2: They're not conservative when it comes to spending. And try

925
00:45:34,440 --> 00:45:37,000
Speaker 2: as I might, I tried to get Addie to spell

926
00:45:37,000 --> 00:45:39,800
Speaker 2: out what Lion's share of one hundred billion dollar capex

927
00:45:39,840 --> 00:45:42,160
Speaker 2: is on AI. Just take a listen to what he said.

928
00:45:43,120 --> 00:45:45,879
Speaker 2: You did say, basically, one hundred billion dollar run rate

929
00:45:46,520 --> 00:45:48,759
Speaker 2: for CAPEX expenditure. Can you give us even like a

930
00:45:48,760 --> 00:45:51,640
Speaker 2: percentage ratedown of how much that goes to distribution logistics

931
00:45:51,640 --> 00:45:53,760
Speaker 2: and how much goes to AI my shares?

932
00:45:54,000 --> 00:45:56,160
Speaker 5: You know most so you've boast of it, you know

933
00:45:56,280 --> 00:45:57,920
Speaker 5: most of it. You know the Lion's share is more

934
00:45:57,920 --> 00:45:58,680
Speaker 5: than fifty percent?

935
00:45:58,800 --> 00:45:59,040
Speaker 4: Yes?

936
00:45:59,160 --> 00:45:59,879
Speaker 2: Is it more than eighty?

937
00:46:01,960 --> 00:46:03,560
Speaker 4: We're playing the warmer and colder.

938
00:46:03,239 --> 00:46:07,520
Speaker 2: Goo, yes, exactly. Do we need more specifics?

939
00:46:07,840 --> 00:46:09,359
Speaker 4: I think we will, But he did make some news.

940
00:46:09,400 --> 00:46:12,000
Speaker 10: I think Amazon's been real careful about their general They franchise.

941
00:46:12,040 --> 00:46:14,359
Speaker 10: They've had multiple billions of dollars in revenue. I think

942
00:46:14,440 --> 00:46:18,560
Speaker 10: Andy told you many billions. So we're parsing adjectives here,

943
00:46:18,600 --> 00:46:20,680
Speaker 10: but I think they're getting a little bit moreptific and

944
00:46:20,680 --> 00:46:22,359
Speaker 10: they're gonna have to as this business grows for them.

945
00:46:23,640 --> 00:46:26,319
Speaker 3: Matt, what do you make of some of the competition.

946
00:46:26,640 --> 00:46:29,360
Speaker 3: Of course, you know you've been looking at quantum very closely.

947
00:46:29,680 --> 00:46:33,120
Speaker 3: Alexa is now really competing in that hardware space all

948
00:46:33,160 --> 00:46:35,760
Speaker 3: over again. But kind of shifting back to the quantum

949
00:46:35,800 --> 00:46:37,279
Speaker 3: piece for a little bit, I kind of want you

950
00:46:37,320 --> 00:46:40,560
Speaker 3: to break down if there are any differences in what

951
00:46:40,680 --> 00:46:43,799
Speaker 3: Jase said about how they're approaching it versus what Microsoft

952
00:46:43,800 --> 00:46:46,760
Speaker 3: and some other players have said.

953
00:46:46,560 --> 00:46:49,160
Speaker 10: Not particularly everybody says, you know, quantum is a really

954
00:46:49,200 --> 00:46:51,560
Speaker 10: hard problem to solve. Everybody says there are so many

955
00:46:51,760 --> 00:46:56,080
Speaker 10: errors inherent in quantum computing. I think again, the AWUS

956
00:46:56,120 --> 00:46:58,440
Speaker 10: approach here seems to be sort of simplicity and trying

957
00:46:58,480 --> 00:47:00,480
Speaker 10: to take out as much of that cost as they can. Right,

958
00:47:00,680 --> 00:47:03,279
Speaker 10: Microsoft's a little bit different boat technologically. You know, they're

959
00:47:03,320 --> 00:47:05,479
Speaker 10: they're talking about limitting states of matter. That's those aren't

960
00:47:05,480 --> 00:47:08,120
Speaker 10: claims you're gonna hear from from Google or Amazon for sure.

961
00:47:08,920 --> 00:47:11,960
Speaker 2: Very briefly, it seems that they're still committed to stripping

962
00:47:11,960 --> 00:47:13,960
Speaker 2: out the layers within the company though, and that's going well.

963
00:47:14,719 --> 00:47:17,040
Speaker 10: You know, it's not a crisis right like we've heard,

964
00:47:17,080 --> 00:47:18,680
Speaker 10: you know, retention issues like a lot of folks. He

965
00:47:18,880 --> 00:47:21,759
Speaker 10: people a little upset about urto but you know, for now,

966
00:47:21,840 --> 00:47:23,560
Speaker 10: no big layoffs in twenty twenty five.

967
00:47:23,560 --> 00:47:26,279
Speaker 2: Wilson that day, it's been a joy having you here

968
00:47:26,280 --> 00:47:28,800
Speaker 2: in New York as well. He's going to bid farewell

969
00:47:28,800 --> 00:47:30,759
Speaker 2: and jump on a plane to Seattle. But that does

970
00:47:30,800 --> 00:47:33,040
Speaker 2: it for this addition of Bloomberg Technology. Do not forget

971
00:47:33,080 --> 00:47:35,160
Speaker 2: to check out our podcasts. Find it on the terminal

972
00:47:35,160 --> 00:47:37,680
Speaker 2: as well as online on Apple, Spotify, and iHeart This

973
00:47:37,760 --> 00:47:43,840
Speaker 2: is Bloomberg Technology.