Speaker 1: Bloomberg Audio Studios, podcasts, radio news. Bloomberg Tech is alive
Speaker 1: from coast to coast with Caroline Hyde in New York
Speaker 1: and Eva though in San Francisco.
Speaker 2: This is Bloomberg Tech coming up. We go to AWS
Speaker 2: we Invent in Las Vegas to discuss the cloud companies,
Speaker 2: new chips, new models, and new AI agents. Becaus Michael
Speaker 2: Dell donates an unprecedented six billion dollars aimed at jump
Speaker 2: starting the investment accounts for twenty five million children in America,
Speaker 2: and Warner Brothers Discovery receives a new round of bids,
Speaker 2: with Netflix flashing mostly cash for its offer. We'll have
Speaker 2: the details, but first let's check in on these markets
Speaker 2: which are flashing green. We actually have a bit of
Speaker 2: a reprieve after yesterday's sell off. We're back into risk
Speaker 2: on mode tentatively. So across the benchmarks, we're looking at
Speaker 2: the NaSTA one hundred nineteen percent of course in video
Speaker 2: leading then in terms of points, but all of some
Speaker 2: of the mag seven really dominating.
Speaker 3: On the day.
Speaker 2: You're looking at bitcoin, even getting a bit yesterday it
Speaker 2: was woeful. Today we find some sort of stability where
Speaker 2: up more than five percent in fact, largely Crypto is
Speaker 2: in the green. We also turn our attention to some
Speaker 2: of the key mags seven that we want to look
Speaker 2: at in terms of their own events, their own announcements.
Speaker 2: And I'm looking at what's happening with Amazon. We're currently
Speaker 2: training up one point three percent. We're getting a little
Speaker 2: nudge higher on some new news coming out about its
Speaker 2: own large language models, about updates of course to its
Speaker 2: own AI agentic focus. And key has got to be
Speaker 2: Trainium three all about its chips.
Speaker 3: Let's get straight over to Ed Ludlow.
Speaker 2: You're in Las Vegas at the reinvent event.
Speaker 4: Yeah, it's probably the Trainium three headlines that move the
Speaker 4: needle right. This is a push forward acceleration of bringing
Speaker 4: the latest generation accelerator to market called Trainium, but useful
Speaker 4: in both the training and inference use case, and much
Speaker 4: as Amazon has done in prygation generations of Trainium, it's
Speaker 4: talking out the cost and performance metrics of it four
Speaker 4: x the prior generation. On price performance, it was interesting
Speaker 4: when the headline's hit, I mean, we're at one and
Speaker 4: a half percent on Amazon, a small move lower or
Speaker 4: pairing some of the gain on both Google and Nvidia.
Speaker 4: And this is the story right. You know, Amazon wants
Speaker 4: to expand the use of Trainium servers beyond one core customer,
Speaker 4: which is anthropic, and they're giving evidence in this release.
Speaker 4: We'll get to it later in the day when we
Speaker 4: speak to Matt Garmon in particular of the savings that
Speaker 4: those customers are made using it while also making sure
Speaker 4: they have capacity that is based in video GPUs and
Speaker 4: of course the open aideal, the AWS has thirty eight
Speaker 4: billion dollars of it is predicated on availability of Nvidia.
Speaker 2: I mean the eye the focus must be so trained
Speaker 2: on what's just been seemingly a positive thrust for Google
Speaker 2: when it all comes down to its own chips right now.
Speaker 4: Yeah, in recent weeks and months when there have been
Speaker 4: reports about Google TPU and the idea that Google Cloud
Speaker 4: will have a big third party use it, it's moved
Speaker 4: the needle on those shares. What universally right now, the
Speaker 4: hyperscalers are experience the supply constraints right comply supply constraints
Speaker 4: where they're basically saying, this is out there in the
Speaker 4: real on Trainium three. It is out there in the
Speaker 4: real world. By the way, general availability from today and
Speaker 4: they've also talked about the pipeline through the Trainium four.
Speaker 2: But you're right, it's all about TPU, it's all about chips.
Speaker 2: It's also about their own innovations when it comes to
Speaker 2: large language models lest we forget. Yes, they've got an
Speaker 2: integration of open AI and anthropic Claude, but they've also
Speaker 2: been movieving the needle on over two.
Speaker 4: Yeah, an over two and updated year on version of
Speaker 4: its first kind of in house foundation model, a variant
Speaker 4: of which OMNI can take inputs MTI model inputs of text, video,
Speaker 4: image responding kind. But that's going to be the question
Speaker 4: the story today. You know, AWS is number one in
Speaker 4: cloud and cloud computing through scale, through leveraging infrastructure, but
Speaker 4: when does it become number one in AI? You know,
Speaker 4: not just being a place that hosts others models, but
Speaker 4: has evidence that its own foundation model is resulting in
Speaker 4: something tangibly useful, particularly for enterprise customers. And I'm pretty
Speaker 4: sure that that's what those that have joined the show
Speaker 4: today want to talk about.
Speaker 2: Yeah, we've got so many conversations come up in this show,
Speaker 2: but you've got to be sticking around because we thank you, ed.
Speaker 2: We're coming back to you because Throughout the show we'll
Speaker 2: have interviews, but at the end we'll have a sit
Speaker 2: down interview with AWSCO Matt Garmon at three pm Eastern time. Meanwhile, look,
Speaker 2: this is all a story of infrastructure, about big tech
Speaker 2: companies such as Amazon, but also Alphabet, Meta and Microsoft
Speaker 2: spending heavily on AI with expected capital expenditure forever three
Speaker 2: round eighty billion dollars combined in their current fiscal years. Now,
Speaker 2: that's going against big tech's mantra for the past two decades.
Speaker 3: Let's call it.
Speaker 2: We are just more about delivering growth while keeping really
Speaker 2: tight little spending.
Speaker 3: It's a real flip reverse.
Speaker 2: Let's talk about Oblimbug's tech equity reporter Carmen ryani Key,
Speaker 2: and you've all been assessing how investor is tight. The
Speaker 2: sudden wild capital expenditure.
Speaker 5: Yeah, I mean, it has been the talking point and
Speaker 5: the thing that we've been focusing on the most with
Speaker 5: some of these big companies, and as you said, it
Speaker 5: really represents a change from how they've operated over the
Speaker 5: last two decades. They really had very capital light businesses
Speaker 5: and were able to be very profitable, grow exponentially in
Speaker 5: some ways because of that, and so now having this shift.
Speaker 5: We're seeing investors rewarded on summons and then really punish
Speaker 5: it on others. So, you know, Microsoft, we saw you
Speaker 5: jump after its latest starting support, but Meta sort of
Speaker 5: got hit because Zuckerberg, you know, didn't explain enough about
Speaker 5: the return on investment of this spending. The other thing
Speaker 5: that's interesting is that this capital expenditures is a portion
Speaker 5: of revenue have jumped, which to a level that's not
Speaker 5: normal for tech companies. So for Microsoft, it's capital expenditures
Speaker 5: are now twenty percent of its revenue. And in addition,
Speaker 5: you know, Alphabet and Amazon, these spending to sales ratios
Speaker 5: are some of the high in the market.
Speaker 2: Okay, so we now have to perhaps digest a period
Speaker 2: of higher capital expenditure. Were meanwhile worrying about some of
Speaker 2: the financing that goes on within it, some of the
Speaker 2: circular financing that's been the narrative. But today the market jumps.
Speaker 3: Why what are you hearing from the investors you're talking to?
Speaker 5: Yeah, I mean, I think that last week was very interesting.
Speaker 5: I think we're seeing a little bit of buying, some
Speaker 5: more optimism and enthusiasm coming back into the market. There's
Speaker 5: a lot you know, in videos CFO was speaking this morning.
Speaker 5: There's a there's just a lot of tech news sort
Speaker 5: of coming back into the market that people are getting
Speaker 5: excited about.
Speaker 3: Well, i'll see if it holds.
Speaker 2: Santa rally upon us potentially come and Ranicky, We so
Speaker 2: appreciate your time. Let's talk about the crypto markets, because
Speaker 2: they too are recovering today off that a heavy sell
Speaker 2: of yesterday when bitcoin still as much as eight percent.
Speaker 2: Let's take a look at strategy as well. The artist
Speaker 2: formerly known as MicroStrategy, heavy investor in bitcoin gaining some
Speaker 2: support after scrambling to calm its own investors, creating a
Speaker 2: one point four billion dollar reserve to fund dividend and
Speaker 2: interest payments rather than having to potentially sell bitcoin as
Speaker 2: a last resort. And if I've seen a digital finance editor,
Speaker 2: Anna Erera is joining us. What's more from London? Anna,
Speaker 2: why today the did buying.
Speaker 6: It's hard to know with crypto, as I'm sure you're
Speaker 6: aware of, and it's crazy to think that yesterday we
Speaker 6: were down eight percent and thinking of all the macro
Speaker 6: condition that might have been leading to that drop. So
Speaker 6: you know, we were speaking to traders today and investors,
Speaker 6: and it seemed that although the price is up, the
Speaker 6: sentiment is still a bit cautious, and volumes aren't as
Speaker 6: up as they were before. I think people are sort
Speaker 6: of assessing that crypto in reality has been on a
Speaker 6: downward spiral of bit since October twelfth, the eleventh, when
Speaker 6: the price crashed, And so while today we're a bit up,
Speaker 6: in reality, you know, we're still pretty lower than we
Speaker 6: were around a month ago when bitcoin reached its record highs.
Speaker 2: I mean, negative bitcoin funding rate is still an anxiety,
Speaker 2: extreme fear levels with coin market caps, fear and greed.
Speaker 2: There's still a lot of comfort needed to an investor
Speaker 2: base that's been beaten up, particularly the retail trade who
Speaker 2: have tried to gain exposure not just by owning crypto,
Speaker 2: but by owning crypto related assets such as what leveraged
Speaker 2: bets on MicroStrategy now called Strategy and it talked to
Speaker 2: us about how much retail of hurt here as well
Speaker 2: as institutional.
Speaker 6: Yes, obviously we know that people were trying to retail
Speaker 6: investor are trying to get exposure into bitcoin and crypto
Speaker 6: through buying ETFs. Thatt, we're supposed to strategy or strategy
Speaker 6: stock itself, and that's fallen dramatically over the past year,
Speaker 6: and so you know they've been hurting. But at the
Speaker 6: same time we've been trying to wait to see if
Speaker 6: more institutional buyers will come in and offset that. But
Speaker 6: it seems to be from what we're hearing, a sort
Speaker 6: of weight and see mode, partly waiting until the FED
Speaker 6: decision next week. So it's kind of in a way,
Speaker 6: same old with crypto. One day it goes ninety percent,
Speaker 6: the next thaying it's a five percent. The asset class
Speaker 6: seems to be maturing and there's more ways to invest
Speaker 6: in it, but maybe not much has changed.
Speaker 3: In Bergana or Era.
Speaker 2: Always great to have you, Thank you very much, and
Speaker 2: stay Withloomberg because there's a conversation coming up you won't
Speaker 2: want to miss if you're in crypto Fondly Strategy President
Speaker 2: CEO coming up in the next hour on Bloomberg Crypto.
Speaker 2: Elsewhere in that ecosystem, not all is gaining support. We're
Speaker 2: watching shares of American Bitcoin Corp. Look at that forty
Speaker 2: four percent at one point down fifty percent. A bitcoin
Speaker 2: minor which counts Eric Trump as a co founder and
Speaker 2: chief strategy officer, seeing multiple trading halts amid the volatility
Speaker 2: now coming up, we'll be joined by Colleen Aubrey, Senior
Speaker 2: and Vice President of Applied AI Solutions over at AWS.
Speaker 2: We are live from the Companies we Invent conference in
Speaker 2: Las Vegas.
Speaker 3: This is Bloomberg Tech.
Speaker 4: Good morning from Las Vegas. So let's talk about some
Speaker 4: of the announcements out from AWS. Colleen Aubrey is Senior
Speaker 4: vice president of AWS, Applied AI Solutions and clean You
Speaker 4: basically work with the full spectrum of the smallest startups
Speaker 4: to the biggest enterprise customers that AWS has and the
Speaker 4: public sector, and it's distilling it as far down as
Speaker 4: I can. You basically help them to take technology and
Speaker 4: innovate make whatever they do better.
Speaker 7: Yeah, the mission I'm on is really to put AI
Speaker 7: into the hands of the business on a day to
Speaker 7: day basis and really make it work for their business
Speaker 7: in production every day, helping them to deliver better experiences
Speaker 7: to their customers.
Speaker 4: We have a new generation of AWS Silicon and server design,
Speaker 4: We have a new generation of Nova model, and we
Speaker 4: have frontier agents. Right and I think you probably heard
Speaker 4: me at the top of the show, but I think
Speaker 4: the big question about AWS Reinvent is what is it
Speaker 4: in this year's offering that takes aws beyond being the
Speaker 4: sort of number one cloud computing platform for capacity to
Speaker 4: giving something tangible, useful that can improve a company's own technology.
Speaker 7: Yeah, two areas that I'd like to talk about specifically
Speaker 7: for me personally, one of my products is Amazon Connect
Speaker 7: and this started as a contact center application, but today
Speaker 7: you know, I see it really as an agentic product
Speaker 7: that's actually looking at whole customer experience. And so for me,
Speaker 7: this is where we're putting our infrastructure, our silicon, our models,
Speaker 7: and now today like bringing that all together in a
Speaker 7: product that can work for businesses. So we launched twenty
Speaker 7: nine new features on Sunday we announced that, and I
Speaker 7: would say there's four key gentic capabilities that come with that.
Speaker 7: The first is actually AI Voice and allowing customers to
Speaker 7: interact in a very natural way using Novasonic and having
Speaker 7: agents actually resolve issues for them on the behalf in
Speaker 7: the background. The second is actually putting AI to work
Speaker 7: as a teammate next to customer service representatives, helping them
Speaker 7: to actually get tasked on complete the paperwork the processes,
Speaker 7: provide recommendations, and help them really have a better view
Speaker 7: of the customer so that the conversation they have with
Speaker 7: customers is much much richer. The third area is actually
Speaker 7: combining what I call clickstream, which is the path that
Speaker 7: customers will take through websites and profiles, to be able
Speaker 7: to present a much more specific recommendation and what a
Speaker 7: next step won't be for a customer. And finally, you know,
Speaker 7: one of the big issues for companies is sort of
Speaker 7: confidently putting AI to work in their business. And in
Speaker 7: this case, we've added observability where you can expect, how
Speaker 7: inspect how an AI is reasoning, how it's thinking, in
Speaker 7: what tools it's using, so companies can really observe AI
Speaker 7: in the same way they would think about the people
Speaker 7: and their business working with customers.
Speaker 4: I want to go to point number two. You use
Speaker 4: the word teammates, yes, but you've in the past talked
Speaker 4: about a hybrid workforce, people and agents. A lot of
Speaker 4: what's come out since Sunday Night seems to reflect that
Speaker 4: you want to increase the number of useful agents. That also, internally,
Speaker 4: we can talk a little bit about what you're encouraging
Speaker 4: Amazon teams to do, but the idea is that that
Speaker 4: workforces will type should get comfortable working alongside agentic AI.
Speaker 8: Yeah.
Speaker 7: I see a future where actually everyone is managing a
Speaker 7: team of AI agents. And I think our frontier agents
Speaker 7: with software developments, sec ops and so DevOps and security
Speaker 7: is sort of one of our first moves in that direction.
Speaker 7: Where you actually have a teammate with a developer who's
Speaker 7: able to address complex problems, able to work over hours and.
Speaker 9: Days, be able to solve for whole.
Speaker 7: Objectives, and to scale with that person, that the role changes.
Speaker 7: I think we all are managing AI teammates, a team
Speaker 7: of people that are all of AI, people that are
Speaker 7: out able to we can delegate to, we can inspect
Speaker 7: what they're doing, we can iterate with them, provide feedback,
Speaker 7: and for me, that's where I think we end up going.
Speaker 7: I think we're clearly moving that way in the customer
Speaker 7: service direction, and I think the developer experience is also
Speaker 7: clearly moving that direction.
Speaker 4: You're in a leadership position at AWS, but you have
Speaker 4: been with Amazon broadly entering your twenty first year. You're
Speaker 4: part of the S team, the leadership team generally internally
Speaker 4: within Amazon's many arms. Is this like, particularly in the
Speaker 4: context of the technology you've released here Reinvent twenty twenty five,
Speaker 4: Is this at a stage where Amazon teams are dog
Speaker 4: fooding this or it's just inherent the use of technology.
Speaker 4: You want your own teams to be. I think AI native.
Speaker 7: Yeah, that's true, and I think what I observe within
Speaker 7: Amazon certainly we're all very keen to get our hands
Speaker 7: on our new frontier agents, and that is something we've
Speaker 7: had in beta internally, and I think teams are very
Speaker 7: excited to use that in production. We use connect within
Speaker 7: our own customer service teams, our seller support teams, our
Speaker 7: AWS support teams, for example. So we continue like to
Speaker 7: iterate and learn from that. And I would say broadly
Speaker 7: across Amazon, we've really tried to sort of embrace the chaos,
Speaker 7: to put AI in the hands of every person in
Speaker 7: the company and to see what they can do, how
Speaker 7: they can transform how they work, what they learn. And
Speaker 7: so you have a lot of teams sort of grassroots,
Speaker 7: sort of trying to solve for what is the new
Speaker 7: way of working using AI, and some of those experiments
Speaker 7: don't lead in newhere, and some lead and a place
Speaker 7: that's really meaningful. And then you have sort of this
Speaker 7: social contagion that happens that people learn from each other.
Speaker 4: Okay, aws number one in cloud computing and in the
Speaker 4: sense of scale infrastructure deployments, is it number one in AI?
Speaker 7: I think we have all the pieces in place and
Speaker 7: we're well on our way. We're very, very focused, and
Speaker 7: what I really like about our strategy is that we're
Speaker 7: working all the way, all the way, the full stack,
Speaker 7: you know, from clean energy, chips, data centers around the world,
Speaker 7: bedrock with real great selection, including our own models. And
Speaker 7: I think Roehet's making really fast progress on that. And
Speaker 7: I think for Swami and I really trying to put
Speaker 7: those all of those pieces to work where out of
Speaker 7: the box a business can get value.
Speaker 4: We've got a conversation with Swami coming up in a bit.
Speaker 4: Colleen Aubrey, SVP of Applied AI Solutions to AWS, Thank
Speaker 4: you so much, Carrot, what.
Speaker 2: A great conversation. Let's stick with Amazon as well, because
Speaker 2: the company, which is vast it plans to offer deliveries
Speaker 2: of hundreds of house items, including some fresh groceries or
Speaker 2: over the counter medicines within just thirty minutes and test program.
Speaker 2: But it's begun in Philadelphia, we stand will begin there
Speaker 2: and its home city of Seattle now coming up the
Speaker 2: Dells make an unprecedented six point twenty five billion dollar
Speaker 2: donation to the Kids of America or on that.
Speaker 3: Next, this is Bloomberg Tech.
Speaker 2: Michael and Susan Dell are donating six point twenty five
Speaker 2: billion dollars, gifting twenty five million children in America two
Speaker 2: hundred and fifty dollars each in an effort to jumpstart
Speaker 2: their investment accounts for the future. The proceeds build on
Speaker 2: the Invest America Initiative or Trump accounts as they're known,
Speaker 2: which we'll see one thousand dollars for every child born
Speaker 2: from twenty twenty five to twenty twenty eight. Let's talk
Speaker 2: about all of it with bost Tom Maloney and how
Speaker 2: unprecedented is this? This SI is a philanthropic gift.
Speaker 10: It's pretty unprecedtentded I mean, there've been big philanthropic gifts before,
Speaker 10: but something going to cover twenty five million children in
Speaker 10: the cover really is pretty unheard of. And a gift
Speaker 10: to go through the federal government. I mean, he's donating
Speaker 10: the money to the US Department of Treasury. That's pretty
Speaker 10: unusual too, So it's quite an unprecedented gift.
Speaker 2: Let's go back to what all of this is sort
Speaker 2: of sitting alongside, which is invest in America. We sort
Speaker 2: of saw that roundtable alongside other CEOs, a lot of
Speaker 2: them tech who have been thinking about how to get
Speaker 2: money into the hands of children to invest in the
Speaker 2: longer term.
Speaker 4: Tom, that's right.
Speaker 10: Yeah, those were created as part of the One Big
Speaker 10: Beautiful Bill, as you mentioned, one thousand dollars for kids
Speaker 10: born between twenty twenty five and twenty twenty eight. And
Speaker 10: what Della is doing is kind of covering the gap
Speaker 10: for children ten under who aren't covered under that program
Speaker 10: and giving them two hundred and fifty dollars to be
Speaker 10: used for things like college or startup, starting up their
Speaker 10: own business, or home deposit when they're eighteen or older.
Speaker 2: Now, Michael Dell and his family and he's the eleventh
Speaker 2: wealthiest person in the world, but it's other tech moneyed
Speaker 2: people who have been putting this initiative to work. And
Speaker 2: I think about really Brad Gerstner, who has been the
Speaker 2: driving force initially behind what is this sort of invest
Speaker 2: America outreach. He set it up back in twenty twenty three.
Speaker 2: Of course we know him from Ultimeter.
Speaker 10: Yeah, that's right. He's been working on this for a
Speaker 10: couple of years. As you mentioned it predates Trump obviously,
Speaker 10: you know, the name Trump Accounts certainly got his attention
Speaker 10: and I think helped put it into the One Big
Speaker 10: Beautiful Bill. But yeah, it's kind of an issue that
Speaker 10: Democrats and Republicans have been interested in something like this,
Speaker 10: a product like this that gets everyday Americans invested in
Speaker 10: the stock market from a very young age. It's kind
Speaker 10: of a bipartisan issue.
Speaker 2: Yeah, And Brad over at Altameter, he's been saying that
Speaker 2: this is a platform for every company in America to
Speaker 2: think about how they reward employee's own children.
Speaker 3: But it doesn't need to just be a company.
Speaker 2: It could be mums and dad's, churches, synagogue's. Many to
Speaker 2: be putting it aside in a sort of tax efficient way.
Speaker 9: Tom.
Speaker 3: What's interesting is, of.
Speaker 2: Course Dell Stock has moved on all of this, and
Speaker 2: this comes after a truth social post.
Speaker 3: Yeah, that's right.
Speaker 10: Dell stock was up about four percent last time I looked.
Speaker 10: Trump obviously singling out Michael and Susan Dell for their
Speaker 10: donation this morning, he was seemingly very happy about it.
Speaker 10: And you know, when Trump tweets about something, it tends
Speaker 10: to move stuff in the market. So we're kind of
Speaker 10: saying that I don't know if it's going to last,
Speaker 10: but there you go.
Speaker 2: And of course that contributes to the networth of the
Speaker 2: Dell family. On the back of that, Bloomberg's Tom Maloney,
Speaker 2: it's been fascinating talking to you, Thank you very much. Indeed,
Speaker 2: let's turn now to Warner Brothers Discovery. The company has
Speaker 2: received a new round of bids, with one from Netflix
Speaker 2: consisting of a mostly cash offers, according to sources. For more,
Speaker 2: Bloomberg's Michelle Davis, who covers M and A Immediate joins us.
Speaker 3: Now, so can we.
Speaker 2: Break down how these is starting to note because they're
Speaker 2: going to be sweetened.
Speaker 11: They've been sweetened, yes, so the bidding is heating up.
Speaker 11: Yesterday Warner Brothers had asked for sweetened offers from all
Speaker 11: of the companies, so we know they received offers from
Speaker 11: Netflix mostly cash. That was a big surprise because people
Speaker 11: were expecting it to be stock. You know, Netflix's stock
Speaker 11: has been doing pretty well. They have great currency, but
Speaker 11: they're also an investment grade company, so they can afford
Speaker 11: to raise a lot of money. We hear they're in
Speaker 11: the market talking to banks about tens of billions of
Speaker 11: dollars for a bridgeland. So there's Netflix, there's Comcast which
Speaker 11: has also bid it only wants to streaming, and the
Speaker 11: studios of Warner Brothers similar to Netflix. We're still trying
Speaker 11: to glean the details of that offer, but we have
Speaker 11: heard that it likely includes a little more stock than
Speaker 11: the cash offered by Netflix. And finally, Paramount, the one
Speaker 11: who kicked all of this off. They're the only bidders
Speaker 11: who have actually made a play for the whole company.
Speaker 11: We're hearing that their offers also is also completely cash.
Speaker 11: They have backing from Larry Ellison, David Ellison, you know,
Speaker 11: some of the rich, wealthiest people on Earth and Middle
Speaker 11: East earn money as well as Apollo er putting in
Speaker 11: some of the financing for their offer.
Speaker 2: And it feels as though that's been the narrative that
Speaker 2: the Edison bid might be one that is more approved
Speaker 2: of by the administration. But are there any blocks? Are
Speaker 2: there any issues from a regulatory perspective for Paramounts guide
Speaker 2: downs just getting any big O or any of these
Speaker 2: players getting any BIGA.
Speaker 11: Yes, So the Warner Brothers board is really I mean,
Speaker 11: they are in a position where they have lots to assess,
Speaker 11: but it's not apples to apples, because they're evaluating, you know,
Speaker 11: a bid for the whole company in cash, a bid
Speaker 11: that might include stock and cash but only for part
Speaker 11: and then you know other structures that are unclear for
Speaker 11: Paramount and comcasts. There's clearly lots of synergies that they
Speaker 11: could achieve by combining the companies, but there's a view
Speaker 11: that doing that, you know, to achieve those synergies, they
Speaker 11: would cut a lot of jobs. I mean, maybe thousands
Speaker 11: of jobs at the studios by combining these studios Netflix
Speaker 11: Their argument might be, we're not going to do something
Speaker 11: like that, and so it'll play better, you know, with
Speaker 11: labor unions and regulators. But Netflix also already has a
Speaker 11: lot of power. So it's a bit wildcard to see
Speaker 11: how the regulators are going to view that.
Speaker 2: Yea, many are going to say, is YouTube count being
Speaker 2: counted in the numbers? How we think about this from
Speaker 2: a regulatory perspective, from a state and federal perspective, timeline, any.
Speaker 3: Sort of idea.
Speaker 11: We're hearing that they want to get this sorted before
Speaker 11: the end of the year, and that makes some sense
Speaker 11: because for the banks who are underwriting the loans, they
Speaker 11: don't want the loans on their books at your end,
Speaker 11: because it's going to cost them a lot more money,
Speaker 11: which means the bidders won't be able to pay as
Speaker 11: much for these assets. So we've heard that there's a
Speaker 11: deadline of before the holidays. A decision could be made
Speaker 11: as early as this week. You know, the binding offers
Speaker 11: are in, so that means Warner Brothers could move quickly,
Speaker 11: but they're also giving themselves room to ask for more bids.
Speaker 11: You know, later on this month, CHERL.
Speaker 2: Davis will be across the story. We appreciate it.
Speaker 9: Now.
Speaker 3: Coming up, we're going to be going back to.
Speaker 2: AWS Reinvent the conferences on in Las Vegas. We're gonna
Speaker 2: sit down with Swami sieve us of Romanian, vice president
Speaker 2: of a Gentki for that company.
Speaker 3: This is pretty big tech. Welcome back to Bloomberg Tech.
Speaker 2: We check in on these markets that are losing a
Speaker 2: bit of their earlier esteem. We're still holding on to
Speaker 2: three ten percent higher, but remember we're up more than
Speaker 2: a percentage point in earlier trading. Is in video perhaps
Speaker 2: loses some of its edge in terms of points perspective.
Speaker 2: Apple leading the charge right now, Intel as well. I'm
Speaker 2: looking at Bitcoin though, still holding onto its games. Best
Speaker 2: day since May. We're now at the highest level and
Speaker 2: ninety nine since the end of November, so a few
Speaker 2: days we're up four point percent as we see a
Speaker 2: little bit of shifting in sentiment. Let's look at a
Speaker 2: key name that has shifted in sentiment. It was beaten
Speaker 2: up in November. Now we're still up two percent. Let's
Speaker 2: call it. We're rolling over somewhat. But Pan Andeer, in
Speaker 2: another AI names, have seen a bit of love today.
Speaker 2: It seems as though Pan Andeer could be a trillion
Speaker 2: dollar company. That's what Dan I've been saying on the day.
Speaker 2: But really he's looking at big Tech and MAG seven
Speaker 2: to add twenty to twenty five percent in terms of
Speaker 2: share growth for twenty twenty six.
Speaker 3: But for now, we return to one of.
Speaker 2: The key MAG seven in that pile, and it is
Speaker 2: Amazon and it's Aws. Even is upon us in Las
Speaker 2: Vegas and take it away.
Speaker 9: Yeah, thank you very much.
Speaker 4: Karas talk more about Amazon's agentic plans with Swami Siva Supermanian.
Speaker 4: He's vice president for a Genta ki at AWS and
Speaker 4: you've basically brought out and released three from what you
Speaker 4: call frontier agents.
Speaker 9: That's right, across.
Speaker 4: An autonomous agent security DevOps and considering where aw sits
Speaker 4: in the market and everyone that attends reinvent, probably the
Speaker 4: question most people would have is if I'm a large
Speaker 4: enterprise and I have multiple teams, multiple deaths, doing multiple things,
Speaker 4: how do I deploy three of these frontier agents?
Speaker 9: Yeah?
Speaker 8: Father MEAs out of it, saying here at daw As
Speaker 8: we are of building the foundation for billions of agents,
Speaker 8: and that's an understatement. So what do we launch with
Speaker 8: these frontier agents? Is essentially a new category of agents,
Speaker 8: because while so much our activity is happening in agents,
Speaker 8: there are historically being more assistance to humans. And while
Speaker 8: we deploy it, even with an Amazon Christen sew thousand
Speaker 8: set developers to help with software development, we were actually
Speaker 8: wanting to push the envelopement being able to actually do
Speaker 8: a lot more where they are actually autonomous, where you
Speaker 8: don't need humans to constantly steer them, and they are
Speaker 8: massively scalable and they can run along.
Speaker 4: To be autonomous, they need to have an end goal,
Speaker 4: that's right, How does that work? So it's a case
Speaker 4: of saying, by the way you use the term AI assistant, Yeah,
Speaker 4: what we're now really talking about is AI co worker.
Speaker 9: That's right, and that is the key thing here.
Speaker 8: It's just like what these frontier agents are doing is
Speaker 8: completely transforming how software is getting done in these teams.
Speaker 8: So much activity happens primarily in like software development, but
Speaker 8: now these agentic teammates they show up as another teammate
Speaker 8: for software development. They pull up actually jobs from like
Speaker 8: guitar task and start coding and clearing backlog. And if
Speaker 8: you're in the middle of the night actually getting page
Speaker 8: to deal with an issue happening with your website, this
Speaker 8: agent first takes the first page and says, oh, let
Speaker 8: me look into what's happening and unpack and then find
Speaker 8: out the root costs so that you can actually quickly
Speaker 8: resolve it and go back to bed, like I've been
Speaker 8: on call and I know I could use that help
Speaker 8: and be proactive so that those issues don't happen. And
Speaker 8: third is actually a security teammate, so it shows up again.
Speaker 8: And most of security has always been about afterthought. One
Speaker 8: of the things we are changing the game here is
Speaker 8: actually meeting developers even before they write a single line
Speaker 8: of code when they're designing software. We catch them right
Speaker 8: there and say here are the things you should be
Speaker 8: aware of. And when they write code, we say, oh,
Speaker 8: don't do that, do this and actually do penetration testing.
Speaker 9: All before shipping.
Speaker 8: So now you can view it as like you have
Speaker 8: the best in class developer, OPS and security engineers showing
Speaker 8: up as virtual teammates for every.
Speaker 4: Software you say best in class? What evidence does AWS
Speaker 4: have that in real world deployments? Running these three agents
Speaker 4: in parallel autonomously has a clear benefit. Yeah, their efficiency, productivity.
Speaker 4: What data can you share?
Speaker 9: Yeah, I'll give actually a couple of examples.
Speaker 8: One is in the DevOps agent that we launched, we
Speaker 8: ran it across thousands of escalations that happened this year alone,
Speaker 8: on incidents and so forth. These agents actually correctly identified
Speaker 8: the root cost eighty six percent of time.
Speaker 9: That is like really impresses eighty six eighty six eighty
Speaker 9: six percent.
Speaker 8: And the second one is Commonwealth Bank of Australia.
Speaker 9: They actually have a huge cloud.
Speaker 8: Infrastructure running across thousand, seven hundred accounts and they put
Speaker 8: this DevOps agent test to test and for a very
Speaker 8: complex networking stack to debug it. And what they said,
Speaker 8: what did to take them? Like our Diba this was
Speaker 8: able to do it in minutes and these are just
Speaker 8: few simple examples, same thing. What's going on at security agent.
Speaker 8: Smart Bug is a great photo company and there I'm
Speaker 8: a big customer, and they are completely automating their security
Speaker 8: operations altogether using like AWS Security Agent. And these are
Speaker 8: all the beginning of how this is going to change
Speaker 8: the game in.
Speaker 9: A big way.
Speaker 8: Because what do you want these agentic teammates to be
Speaker 8: is always be there and you delegates on the boring
Speaker 8: drudgery associated with like ops and security and backlog on
Speaker 8: developments so that developers are empowered to be extremely creative
Speaker 8: and you will start seeing fighter ten x improvement in
Speaker 8: productivity in a big way.
Speaker 4: To reach out its three agents, Kero is software development.
Speaker 4: You have the AWS Security Agent, the AWS DevOps agent.
Speaker 4: They are designed to run for hours autonomously. To sum
Speaker 4: that disconcerting, right, And I go back to my other question,
Speaker 4: how much concern is there in the last segment Clean
Speaker 4: talk to me about observability, understanding in real time what's doing.
Speaker 4: But that sounds to me like it's human supervision.
Speaker 9: It's a great question.
Speaker 8: I mean, this is the nuance and the art of balance.
Speaker 8: We had to do one. You want these agents to
Speaker 8: be autonomous and massively scalable, but you also want them
Speaker 8: to not go off the rails. So first we are
Speaker 8: built it with the right guard rails. And second even
Speaker 8: a spart a development workflow, these agents can go actually
Speaker 8: take a goal from a developer to say, hey, go
Speaker 8: work on upgrading.
Speaker 9: This piece of code to the latest systyk and then
Speaker 9: start upgrading.
Speaker 8: But then as a final step, it might send it
Speaker 8: for a code review to the human and say take
Speaker 8: a look and make sure I'm okay. And once they
Speaker 8: say I'm okay, I think it's fine, or they can
Speaker 8: even configure it to say if it pass us all
Speaker 8: these tests, you're good to ship it. So that you
Speaker 8: have built in s either through human or automated tests.
Speaker 8: And these are the kind of things now we are
Speaker 8: able to actually innovate with the customers as well. And
Speaker 8: even there we have done some pure innovation like introduced
Speaker 8: automated mathematically provable property based testing, so that means now
Speaker 8: developers can specify their goal and we can mathematically prove
Speaker 8: with things like kiro that whatever it is generating can
Speaker 8: be tested exactly that way and it's accurate. So that
Speaker 8: is like another game changer.
Speaker 4: SWAM we see the supermanian vice president for a gens
Speaker 4: Ki at aws three new Frontier agents carry We're talking
Speaker 4: about here in Las Vegas, back.
Speaker 2: To you, loving it back here in New York. Ed's
Speaker 2: time for talking tech. First up, Apple's head of AI
Speaker 2: John Jian Andrea, Well, he's coming down with mans to
Speaker 2: lead the company entirely in the spring. The move caps
Speaker 2: are pretty tumultuous tenure that included a fumbled entry into
Speaker 2: General's AI. Apple won't be directly replacing Jian Andrea, instead
Speaker 2: opting to break up the AIT plus Samsung It's unveiled
Speaker 2: its first trifle smartphone. It's called Galaxy Z Trifle and
Speaker 2: the device contains two hinges allow it to transform into
Speaker 2: a larger tablet like device. The phone is set to
Speaker 2: be released first in South Korea on December the twelfth,
Speaker 2: with a price of about four hundred and fifty dollars,
Speaker 2: and the US Commerce Department has agreed to invest as
Speaker 2: much as one hundred and fifty million dollars into x Light.
Speaker 2: It's a chip startup where former Intel CEO Pat Gelsinger
Speaker 2: serves as executive chairman. So the latest moved by the
Speaker 2: Trump administration to bring chip making capabilities back to the
Speaker 2: United States. Now coming up, guess while we go back
Speaker 2: to AWS in Vegas. This time it's a conversation.
Speaker 3: With Sanjay Back to Cone.
Speaker 2: Nas chief Product and Technology Officer is a blueber tech.
Speaker 2: Luma AI, known for its flagship creative product, dream Machine
Speaker 2: video generator, taking a step forward in global expansion with
Speaker 2: opening its first international office and it's in London. This
Speaker 2: follows its recent nine hundred million dollar Series C investment,
Speaker 2: which was led by Humane and Met Jane Is with
Speaker 2: US co founder CEO of Luma AI and so.
Speaker 3: Pleased to join you.
Speaker 2: I can't wait to get into reasoning video models, into
Speaker 2: the future of world models.
Speaker 3: But first am it? Why London?
Speaker 12: We have a huge pipeline. Actually, by the way, thanks
Speaker 12: for having me. I'm very excited to be here. We
Speaker 12: have a huge pipeline of researchers, engineers from Europe and
Speaker 12: also deep Mind that want to join luma And also
Speaker 12: London is the gateway for the business in Europe as
Speaker 12: well as Middle East, so it seems to be the
Speaker 12: right place to have our second office outside of Palo
Speaker 12: Alto and Bay Area. So yeah, today is our launch
Speaker 12: of the London office.
Speaker 2: I have a feeling demos hasibus over at deep Mind
Speaker 2: and the AI labs at Google we'll be having is
Speaker 2: is pricked by that, amit? So why would people currently
Speaker 2: working or having been trained at deep Mind and the
Speaker 2: like want a jump ship to help build Ray three
Speaker 2: your reasoning video model.
Speaker 12: Yeah, I think that's a great question. So Luma already
Speaker 12: has actually a deep bench of researchers from from n
Speaker 12: video from from deep Mind, from you know, schools like MIT,
Speaker 12: Stanford and Berkeley. And the reason that these incredibly exceptional
Speaker 12: people actually join Luma is because, one, while it is
Speaker 12: a very very well resourced AGI lab, we are only
Speaker 12: about one hundred and fifty people, so we get to
Speaker 12: do and get to have resources per person that, like,
Speaker 12: you know, it's unheard of in the rest of the
Speaker 12: industry actually. And second, Luma is so ultra aligned on
Speaker 12: this one goal, which is to build multi model AGI.
Speaker 12: There's actually no second There is no second project happening
Speaker 12: at Luma.
Speaker 9: This is what we do.
Speaker 12: So people researchers, engineers and product people who believe strongly
Speaker 12: in this mission, Luma is the best place in the
Speaker 12: world for them to be.
Speaker 2: Looking at some of the amazing video that you create
Speaker 2: I can see how it goes into the creative sphere,
Speaker 2: into advertising and the like, but it feels as though
Speaker 2: this model, these world models, has moved to perhaps more
Speaker 2: physical AI applications must open up different industries.
Speaker 12: Yeah so, I mean video and video is actually the
Speaker 12: path to AGI. And let me tell you just very
Speaker 12: briefly why that is the case. Language gives us reasoning,
Speaker 12: and language gives us the human abstraction that is necessary.
Speaker 12: Video shows us the entire universe. Right, you know how
Speaker 12: things behave, how water behaves, how the laws of physics work.
Speaker 12: Then you combine them together. Then video, audio and language
Speaker 12: together is basically a chance to build a universal simulator.
Speaker 12: So one application of that, as you point out, is
Speaker 12: obviously for entertainment and to generate video to automate or
Speaker 12: or to to make digital the act of creating video.
Speaker 12: But in addition to that, it is the gateway to
Speaker 12: be able to build actually general purpose robotics. That is
Speaker 12: the second area that we are very deeply focused on
Speaker 12: and now starting to build out a team and the
Speaker 12: research area of that, and we have if we want
Speaker 12: to have any shot at building general purpose robots, then
Speaker 12: the only way that happens is by giving them this
Speaker 12: level of general understanding of the universe so that they can,
Speaker 12: you know, reason in their head. They can actually simulate
Speaker 12: every scenario right in their head, like, Okay, what would
Speaker 12: happen if I do this? What would happen if I
Speaker 12: do something else? This level of learning and reasoning is essential,
Speaker 12: so video as it advances and as we scale these models,
Speaker 12: they will not only get better and better, they will
Speaker 12: get more accurate in simulating physics. And this is the
Speaker 12: path to building physical intelligence. And that's why Luma's model
Speaker 12: mission is to build multimodel agi that can generate, understand,
Speaker 12: and operate in the physical world. And that is the
Speaker 12: end goal.
Speaker 2: What is the biggest blocker to that or the thing
Speaker 2: that keeps you up Because at the moment, you've got
Speaker 2: the money, Boy, do you have the money nine hundred
Speaker 2: million raised, But we've also got promise of compute coming
Speaker 2: from Saudi Arabia.
Speaker 3: Is it about compute?
Speaker 2: Is it more about the talent that is what you
Speaker 2: need to push through to get to your mission.
Speaker 12: Yeah, So there are two really important things for LUMA.
Speaker 12: Over the last couple of years, we worked tirelessly to
Speaker 12: solve the research problem for like you know, really really
Speaker 12: great video. Now the next frontier for us are these
Speaker 12: omni models that are able to like you know, reason
Speaker 12: an audio, video, language text together. So the research is
Speaker 12: like you know, the first one that we pay mental
Speaker 12: amount of attention to now to solve the research of course,
Speaker 12: you know, people and really really brilliant people is one
Speaker 12: of those bottlencks. So we hire from some of the
Speaker 12: best places. See, we don't need thousands of people. We
Speaker 12: need like, you know, maybe two hundred or three hundred
Speaker 12: really really brilliant people to work on these problems. So yeah,
Speaker 12: that's that's the first one. The talent and great aligned people,
Speaker 12: that is the first one. Second is obviously compute. So
Speaker 12: alongside with the SERIOC announcement, we announced that we will
Speaker 12: build with Humane and collaboration with Humane, a two gigawat
Speaker 12: compute cluster that is the largest compute build out in
Speaker 12: our space of world models and video models and like
Speaker 12: you know, this kind of physical AI. And it is
Speaker 12: also one of the largest compute built out in AI period, right,
Speaker 12: So compute is one of the other things that is
Speaker 12: a big limitation. Ultimately, multi model AI will be a
Speaker 12: superset of llms, will be a superset of the AI
Speaker 12: we have today, it will require more compute than llms
Speaker 12: do right now. So compute is the second very important
Speaker 12: input to our business that, like you know, we are
Speaker 12: working to not only shore up but solve in a
Speaker 12: way we can serve these models economically to a lot
Speaker 12: of people.
Speaker 2: I mean, Jane, come back and tell us how you'll
Speaker 2: continuing on that mission.
Speaker 3: Go found a CEO of Luma AI.
Speaker 9: Thank you.
Speaker 2: Coming up, we're talking more about AI and infrastructure. We're
Speaker 2: going to aws's event in Vegas. Were a conversation with
Speaker 2: Sanjay Blackta Conde, NAS chief product and technology officer is
Speaker 2: a blue big.
Speaker 4: Tech Sanday back to Conde, NAS chief Product and Technology
Speaker 4: officer joins us from AWS reinvent in Las Vegas. You're
Speaker 4: kind of bucking a trend that we've been talking about
Speaker 4: throughout the year in the context of AI. Actually on
Speaker 4: prem has kind of been back when AI is being
Speaker 4: run at the edge. You're going the other way from
Speaker 4: on prem, relying heavily on AWS.
Speaker 9: The rationale, well.
Speaker 13: We are actually users of AI. We are not like
Speaker 13: some of these LLLM companies that are creating and training
Speaker 13: their own models. Although we have trained models in the past,
Speaker 13: but at a much smaller scale. So for us, investing
Speaker 13: in infrastructure and building out data centers for the size
Speaker 13: of our operation doesn't make sense.
Speaker 4: The work with AWS is focused on deli ring personalized content, right,
Speaker 4: And is that at the foundation model level you know
Speaker 4: AWS out with Nova to today, or it's just simply
Speaker 4: that you're leveraging their scale the multitude of data platforms
Speaker 4: they have.
Speaker 13: Yeah, for that particular use case, we're actually just leveraging
Speaker 13: their infrastructure and scale. We've built all the personalization models
Speaker 13: ourselves and we've trained them in house, and we've been
Speaker 13: doing that for the last probably three four years, long
Speaker 13: before LLMS became a thing. We've had our own data
Speaker 13: science team and we've been training models. So we use
Speaker 13: our own homegrown models for most of the personalization and
Speaker 13: recommendation workload.
Speaker 4: So here in lies the question of AWS reinvent AWS
Speaker 4: number one in cloud computing, but they want to do more,
Speaker 4: They want to be number one in AI. You know,
Speaker 4: their own foundation models, the agentic tools that they release today.
Speaker 4: What would it take from Amazon in terms of the
Speaker 4: utility of that technology for you to rely on them
Speaker 4: more heavily.
Speaker 13: Well, actually, for some of the generative use cases you
Speaker 13: know that are LLLM based. We are using Amazon Bedrock.
Speaker 13: You know, we have a contracts management, rights clearance system
Speaker 13: that we just launched. We are using Amazon's Bedrock capability
Speaker 13: for some of our moderation AI based moderation of user
Speaker 13: generated content. So we're looking more and more now to
Speaker 13: towards using out of the box capabilities that Amazon provides
Speaker 13: rather than build and train our own models, which we.
Speaker 9: Used to do in the past.
Speaker 13: I think the need for that is becoming less and less.
Speaker 4: Conde has a relationship with open AI. Condy was one
Speaker 4: of the first to make a deal with open Ai
Speaker 4: early days, it seems. But how is that progressing?
Speaker 9: That's going well.
Speaker 13: Actually, we're starting to use chat GPT quite widely within
Speaker 13: the enterprise internally, yes, and for external use case. We've
Speaker 13: actually launched an AI based recipe search on bond Appetite
Speaker 13: on our on our website, and also it's going to
Speaker 13: come out in our app which allows customers to go
Speaker 13: in and do natural language search and also be able
Speaker 13: to modify the it has peace according to their taste.
Speaker 13: So that's the first use case we are looking at
Speaker 13: others with opening I as well.
Speaker 4: The broad theme of the program today here at AWS
Speaker 4: has been about companies of all sizes moving from using
Speaker 4: AI assistance internally to what awso call the AI co worker,
Speaker 4: you know, a hybrid workforce of people and energentic AI.
Speaker 4: Conde has done layoffs in the past two years, financial years.
Speaker 4: How much has that been about AI tools changing productivity,
Speaker 4: eliminating certain roles, changing certain roles.
Speaker 13: Well, I don't think it's most of it has been
Speaker 13: about AI. Actually, some of it, you know, especially in tech.
Speaker 13: You know, we've had we use extensively, We use AI
Speaker 13: for our work work on a day to day basis,
Speaker 13: which eliminates the need for some roles. We can do
Speaker 13: more things with fewer people. But other than that, across
Speaker 13: the organization, we've not really had any AI based impacts.
Speaker 4: Got to ask in a different part of the Amazon universe.
Speaker 4: I've been experimenting at home with Alexa and Alexa plus.
Speaker 4: Do we get some kind of Conde nas Alexa integration.
Speaker 9: Well, that's work going on there.
Speaker 13: We have actually already integrated with Amazon Alexa.
Speaker 9: So how does that work available?
Speaker 13: So you know, you can query and you can get content,
Speaker 13: you know, read out to you from some of our
Speaker 13: publications not all so, but I think it's pretty cool.
Speaker 13: We should try it out.
Speaker 4: At the heart of that question is something a bit
Speaker 4: more existential. Conday sees itself more as maybe entertainment, and
Speaker 4: if you look at the revenue streams very different from
Speaker 4: saying you're a news organization. Just explain how you see
Speaker 4: this company transitioning right now?
Speaker 13: Yeah, I think they're definitely in the entertainment space because
Speaker 13: if you look at our brands, you know we mostly
Speaker 13: cover leisure, fashion, lifestyle. We're not a daily news outlet,
Speaker 13: so people don't come to us on an everyday basis.
Speaker 13: So we are competing with other entertainment outlets, whether it
Speaker 13: is you know, streaming media like Netflix or Hulu or
Speaker 13: Amazon Prime, or social media you know TikTok and Instagram
Speaker 13: and others. So people have limited spare time, so we
Speaker 13: are competing for a slice of that. So we definitely
Speaker 13: have to do way better in terms of our personalization
Speaker 13: and user experience and also our great journalism that we have,
Speaker 13: I think is what is going to take.
Speaker 4: Us forward, Sunjay, in the year ahead, what's the one
Speaker 4: big change you want to make on the technology side,
Speaker 4: the one thing you're still yet to do be AI
Speaker 4: or something else?
Speaker 13: Yes, I think it's mostly definitely around AI. We have
Speaker 13: a pretty solid data infrastructure that we've built on Amazon
Speaker 13: with data bricks, and our next task is really to
Speaker 13: figure out how do we vectorize all of our content
Speaker 13: and make it readily available in real time to lllams.
Speaker 13: I think that is probably our number one challenge.
Speaker 4: Sanjay Bakta Conde Nas, thank you so much for joining
Speaker 4: us here in Las Vegas.
Speaker 9: Carry back to you.
Speaker 2: Fascinating set of conversations across the gamut of all things
Speaker 2: AI and entertainment edge.
Speaker 3: We thank you.
Speaker 2: You got so much more coming up that does it
Speaker 2: this edition of Bloomberg Tech, But do stick around. It
Speaker 2: is going to sit down interview with AWS CEO Matt
Speaker 2: Garman's three pm Eastern twelve pm Pacific first right here
Speaker 2: on Boomog Television.
Speaker 3: And who all, don't forget to check out a podcast you're.
Speaker 2: Finding on the terminal as well as online on Apples, Spotify,
Speaker 2: and iHeart from New York from Las Vegas.
Speaker 3: This is a blue Bag Tech