WEBVTT - BI Weekend: Oracle's Money Making Moves, America's Hot Garbage Problem

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<v Speaker 1>Bloomberg Audio Studios, podcasts, radio news. This is Bloomberg Intelligence

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<v Speaker 1>with Paul Sweeney.

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<v Speaker 2>The real AP performance has been the US corporate high yield.

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<v Speaker 2>The market's telling me here's another AI play, Just bid

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<v Speaker 2>it by it. One person's cast is another person's animal spirits,

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<v Speaker 2>breaking market.

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<v Speaker 1>Headlines and corporate news from across the globe.

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<v Speaker 2>The semiconductor business is a really cyclical business.

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<v Speaker 3>These are two.

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<v Speaker 2>Big time blue chip companies, so people just too exuberant

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<v Speaker 2>out there.

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<v Speaker 1>Bloomberg Intelligence with Paul Sweeney on Bloomberg Radio, YouTube and

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<v Speaker 1>Bloomberg Originals.

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<v Speaker 2>On Today's Bloomberg Intelligence Show, we dig inside the big

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<v Speaker 2>business stories impacting Wall Street and the global markets. Each

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<v Speaker 2>and every week we provide in depth research and date

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<v Speaker 2>on some of the two thousand companies and one hundred

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<v Speaker 2>and thirty industries our animals cover worldwide. Today we'll look

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<v Speaker 2>at Oracle signing a cloud deal with thirty billion dollars

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<v Speaker 2>a year. Plus later on a big take story on

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<v Speaker 2>the Treasury Department's cybersecurity vulnerabilities. But first we begin with

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<v Speaker 2>an outlook into travel and leisure for the second half

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<v Speaker 2>of twenty twenty five. According to a bi US travel survey, tariffs, inflation,

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<v Speaker 2>and geopolitics could deter consumers from spending money on hotels

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<v Speaker 2>and flights. Jody Lourie, Bloomberg Intelligence Analysts breaks it down.

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<v Speaker 4>For a large part, the companies have been doing pretty well,

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<v Speaker 4>and from a credit perspective, we've seen pretty decent total

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<v Speaker 4>returns for the indices, and that's compared to high yield

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<v Speaker 4>and investment grade as a total. You know, we've seen

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<v Speaker 4>that for discretionary that these leisure related companies have actually

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<v Speaker 4>been doing better than most of discretionary and it makes

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<v Speaker 4>sense because other parts of discretionaries, such as retail, are

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<v Speaker 4>much more sensitive to know these tariffs and trade talks

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<v Speaker 4>that are really affecting a lot of our outlook.

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<v Speaker 5>Jody, I'm looking through your note where you talk about

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<v Speaker 5>the fact that there's a lot of uncertainties right now

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<v Speaker 5>that are a lot of these consumers are grappling with

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<v Speaker 5>as pertains to leisure traveling, with tariffs, inflation, China economy,

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<v Speaker 5>and geopolitics. Can you just give us a little bit

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<v Speaker 5>more of the backdrop right now? What is the consumer

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<v Speaker 5>thinking as it relates to travel right now during the summer.

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<v Speaker 4>So I think that consumers are still going along with

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<v Speaker 4>their plans for the most part, but maybe slightly tweaking it.

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<v Speaker 4>What we saw in our second half leisure survey that

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<v Speaker 4>we ran We run this every half a year, is

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<v Speaker 4>that consumers are not pulling back on experiences. They're not

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<v Speaker 4>pulling back on accommodations. What they might be pulling back

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<v Speaker 4>on is destination to do a cheaper destination if they

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<v Speaker 4>need to cut costs. But by and large, most consumers

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<v Speaker 4>are looking at spending on travel, spending on experiences as

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<v Speaker 4>a way to escape what's going on and sort of

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<v Speaker 4>the last party before maybe the chair gets pulled out

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<v Speaker 4>from under them.

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<v Speaker 2>How about my favorite, UH secrament, which is the casino business.

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<v Speaker 2>How does Zach perform in a time of maybe some

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<v Speaker 2>uncertainty out there?

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<v Speaker 4>So I think it's a question of what region we're

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<v Speaker 4>talking about. And so for Las Vegas, you're dealing with

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<v Speaker 4>the fact that we had really strong comps because we

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<v Speaker 4>had a couple of one time events such as the

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<v Speaker 4>Super Bowl, such as the first Step one that really

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<v Speaker 4>drove a lot of last year and the year before

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<v Speaker 4>it's performance. This year, we're not seeing that same momentum there,

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<v Speaker 4>So it's a little less exciting when you talk about regionals.

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<v Speaker 4>I mean, that's really my question. So a lot of

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<v Speaker 4>the companies like to talk about how regional casinos are

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<v Speaker 4>counter cyclical, meaning people will still go to regional casinos

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<v Speaker 4>to gamble even during a recession. But I think the

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<v Speaker 4>question I have is the last sort of data points

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<v Speaker 4>we have on that is before we had online gaming. Right.

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<v Speaker 4>Online gaming is definitely a game changer to the whole industry,

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<v Speaker 4>and my colleague Brian Egger, who covers on the equity side,

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<v Speaker 4>can talk at nauseum about online gaming, as you know.

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<v Speaker 4>But I think really the question is from more of

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<v Speaker 4>a macro standpoint, how that's going to affect these companies

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<v Speaker 4>as it really lates to their regional casinos. Now, when

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<v Speaker 4>we talk about Macau, there's a lot of sort of

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<v Speaker 4>questions about China and China's economy and how that might

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<v Speaker 4>trickle into the effects of a Macau. Never mind the

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<v Speaker 4>fact that we're now going to have competition in the

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<v Speaker 4>UAE with the Wind casino that's opening up in a

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<v Speaker 4>few years. You know, we're seeing Thailand has been not

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<v Speaker 4>so not so quick to get on the casino game,

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<v Speaker 4>but we've seen japan As starting to open up with MGM,

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<v Speaker 4>so there's a lot of competition globally that might change

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<v Speaker 4>the dynamics of casinos at large.

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<v Speaker 5>Judy, when you think of travel, I immediately think of airlines.

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<v Speaker 5>You know, how I'm I going to get from where

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<v Speaker 5>I need to go point A to point B. Able

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<v Speaker 5>we look at airlines, I'm looking at an index it's

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<v Speaker 5>not about eighteen percent. But then hotels you have to

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<v Speaker 5>need somewhere to stay. We're seeing them popping up about

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<v Speaker 5>nine percent so far this year. What's going on in

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<v Speaker 5>the hotel space right now?

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<v Speaker 4>So in the hotel space, they're still commanding these good

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<v Speaker 4>prices for the rooms, right and I think that's a

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<v Speaker 4>function of the fact that you're seeing business and conference

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<v Speaker 4>travel tick up. Now, the question is how are people traveling?

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<v Speaker 4>And are people doing more domestic travel? Are they driving

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<v Speaker 4>to places, are they taking the train, are they opting

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<v Speaker 4>out of airlines because it's just so uncomfortable, and are

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<v Speaker 4>they not doing international travel as much? And I think

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<v Speaker 4>that's really what's sort of playing out is is that

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<v Speaker 4>question of it is how are people getting to their destination?

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<v Speaker 4>What destination are they going to? You know, there's definitely

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<v Speaker 4>data points out there. I was just reading a report

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<v Speaker 4>this morning. I was talking about how July fourth is

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<v Speaker 4>going to be the busiest in terms of travel. But really,

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<v Speaker 4>I mean for July fourth, are we flying places? Are

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<v Speaker 4>we driving to barbecues? That's really the question. And I

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<v Speaker 4>think you know, with the sort of airline component, is

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<v Speaker 4>that rental car component, right? And so when you look

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<v Speaker 4>at what you know, the CPI, the Consumer Price Index

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<v Speaker 4>is for airlines what it is for rental cars. You know,

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<v Speaker 4>rental cars has shown a weakness of late, and I

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<v Speaker 4>think that's a function of the fact that you're seeing

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<v Speaker 4>consumers sort of not necessarily opting to rent a car,

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<v Speaker 4>especially when so many rental cars are tied to airlines.

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<v Speaker 2>I know you cover six Flags as in six Flags

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<v Speaker 2>Great Adventure in New Jersey. Haven't been since my junior

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<v Speaker 2>year in high school.

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<v Speaker 5>I went three years ago.

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<v Speaker 2>You did, great time, great time. It's awesome. How about

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<v Speaker 2>the theme park business, because a lot of listeners and

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<v Speaker 2>viewers are Disney shareholders, and that's the biggest part of

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<v Speaker 2>Disney's business. Are people still going to the high price

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<v Speaker 2>theme parks?

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<v Speaker 4>People are still going to theme parks, But I think

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<v Speaker 4>there's sort of a question of destination versus regional. Now

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<v Speaker 4>we've been sort of, you know, less constructive. I guess

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<v Speaker 4>on regional theme parks of late then say cruise lines,

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<v Speaker 4>And that's a function of the fact that I think

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<v Speaker 4>people were looking outside their general area. You know, somebody

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<v Speaker 4>in New Jersey isn't necessarily seeing six fives Great Adventure

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<v Speaker 4>as their big vacation. They're seeing, you know, the cruise

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<v Speaker 4>to the Hamas as their big vacation. But I think,

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<v Speaker 4>as you know, consumers, if and one consumers start really

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<v Speaker 4>feeling the straight on their wallet, we might see some

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<v Speaker 4>of them come back to theme parks. And we're still

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<v Speaker 4>trying to figure that out what that's going to look

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<v Speaker 4>like and what percentage. But for someone like United Parks,

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<v Speaker 4>which is formerly SeaWorld, you know, they're benefiting from the

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<v Speaker 4>fact that Universal is opening up a theme park in Florida.

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<v Speaker 4>You know, they have the large portion of their properties

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<v Speaker 4>are in Florida. You know, of course, they have the

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<v Speaker 4>bush gardens, they have the Sesame place, they have stuff

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<v Speaker 4>in San Diego. But a large percentage of their parks

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<v Speaker 4>and their revenue comes from Florida. And so when you

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<v Speaker 4>think about someone like a SeaWorld or United Parks, as

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<v Speaker 4>they go by. Now they are much more sensitive to

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<v Speaker 4>what's going on with Disney and Universal and if they're

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<v Speaker 4>building new parks, if they're getting people to come, they

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<v Speaker 4>might then accidentally also go to SeaWorld.

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<v Speaker 2>Oh thanks to Jody Lorie Bloomberg Intelligence Credit analysts, if

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<v Speaker 2>you choose to stay close to home this summer, no worries.

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<v Speaker 2>There are still plenty to do, like watching a movie

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<v Speaker 2>starring Brad Pitt on a Formula one racing track. That's

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<v Speaker 2>exactly what Apple wants you to do. Apple Original Film

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<v Speaker 2>f one. The movie is quickly becoming a some blockbuster

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<v Speaker 2>and could be the catalyst to supercharge bidding prospects for

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<v Speaker 2>Formula ones US TV rights. For more Onette Emli Grafeo

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<v Speaker 2>and I turned to geth It rang Anathan Bloomberg Intelligence

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<v Speaker 2>Senior US Media Analyst.

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<v Speaker 6>So this was obviously a big success story for Apple.

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<v Speaker 6>They've been dabbling in these theatrical films for quite a

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<v Speaker 6>bit now, but none of you know, none of their

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<v Speaker 6>movies have had this much of a success. So this

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<v Speaker 6>is really good news and I think it kind of

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<v Speaker 6>really emboldens them with respect to their strategy. So definitely,

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<v Speaker 6>movie theaters are happy. And the other point that I'd

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<v Speaker 6>like to make is, you know, more than twenty to

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<v Speaker 6>twenty five percent of the total box office actually came

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<v Speaker 6>in from Imax. So this is really good news for

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<v Speaker 6>the exhibiters because the premium large format, that whole thing

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<v Speaker 6>about going to the theater to experience the movie is

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<v Speaker 6>really working.

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<v Speaker 7>Okay, so your latest note is about how this F

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<v Speaker 7>one movie here from Apple is going to jolt you say,

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<v Speaker 7>lackluster lackluster bidding for the Formula one rights in the US.

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<v Speaker 7>Give us a little bit of context here the landscape

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<v Speaker 7>of rights for Formula one, Who currently has the rights,

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<v Speaker 7>when does that expire? And just put into context kind

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<v Speaker 7>of the current bidding right now?

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<v Speaker 6>Sure, Emily, so right now. So Formula one is, you know,

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<v Speaker 6>as a global sports, global media property in the US,

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<v Speaker 6>the rights to distribute Formula one content is owned by

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<v Speaker 6>Disney's ESPN, So they have rights that go through the

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<v Speaker 6>end of this year through the end of twenty twenty five.

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<v Speaker 6>They're currently paying about eighty five million dollars a year.

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<v Speaker 6>That's up from their last negotiation negotiation cycle when they

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<v Speaker 6>were paying only about five million dollars. So it's up

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<v Speaker 6>to eighty five million. But what F one is saying

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<v Speaker 6>is that this is such an interesting property, this is,

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<v Speaker 6>you know, a hot property, you should be paying up

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<v Speaker 6>for it. And they are really looking for something upwards

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<v Speaker 6>of about one hundred and fifty two hundred and sixty million,

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<v Speaker 6>and I'm not so sure ESPN wants to pay that

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<v Speaker 6>that much money. So it's really price is really a

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<v Speaker 6>sticking point here, and it looks like we've hit a

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<v Speaker 6>little bit of a stalemate. By the way, this problem,

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<v Speaker 6>you know, F one really kind of shot into the

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<v Speaker 6>limelight in the US with the Netflix drive to survive series. Now,

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<v Speaker 6>Netflix has been hugely actually instrumental in kind of driving

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<v Speaker 6>this Surgeon popularity. So everybody was kind of wondering whether

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<v Speaker 6>Netflix or you know, maybe another streamer like an Amazon

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<v Speaker 6>would kind of come in and bid for the rights.

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<v Speaker 6>But I think what we're seeing with a lot of

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<v Speaker 6>these streaming platforms is that they want global rights. These

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<v Speaker 6>are all global streaming platforms. They want rights to distribute

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<v Speaker 6>this content and all markets, and they're not going to

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<v Speaker 6>be able to get that right.

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<v Speaker 2>Now because Formula one, who's their European over is that

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<v Speaker 2>Warner Brothers Discovery, who distributes.

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<v Speaker 6>Ski Ski actually distributes them in most markets, so you know, Ireland, UK, Germany,

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<v Speaker 6>Italy again, France, Spain, they all have a little bit

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<v Speaker 6>different you know, distributors, but ski is a is a

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<v Speaker 6>very big one across most of Europe.

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<v Speaker 7>Wouldn't Apple be the obvious choice to partner up and

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<v Speaker 7>you know, get the rights to Formula one because they

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<v Speaker 7>just made this a blockbuster hit about Formula one.

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<v Speaker 6>You would think so, you know, but it's been a

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<v Speaker 6>little bit of you know, again, it's hard to actually

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<v Speaker 6>figure out what Apple is thinking here. One thing that

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<v Speaker 6>Apple doesn't have, which both Amazon and Netflix have, is scale.

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<v Speaker 6>So Netflix has well over three hundred million global subscribers.

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<v Speaker 6>Amazon probably has closed about three hundred million as well

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<v Speaker 6>on their video streaming service. Apple, on the other hand,

0:11:30.640 --> 0:11:33.640
<v Speaker 6>has probably less than fifteen million, so they don't necessarily

0:11:33.720 --> 0:11:35.880
<v Speaker 6>have the scale to support it. And remember there are

0:11:35.880 --> 0:11:37.959
<v Speaker 6>a few other things with the Formula one property. You

0:11:38.000 --> 0:11:41.400
<v Speaker 6>don't have a lot of advertising inventory necessarily, So again

0:11:41.440 --> 0:11:44.640
<v Speaker 6>that's something that doesn't necessarily appeal to streamers, especially because

0:11:44.640 --> 0:11:47.080
<v Speaker 6>all of these different streaming platforms are really trying to

0:11:47.120 --> 0:11:50.240
<v Speaker 6>build out their ad business. A Formula one doesn't necessarily

0:11:50.320 --> 0:11:53.400
<v Speaker 6>lend itself to that, but you're absolutely right. Apple could

0:11:53.480 --> 0:11:55.560
<v Speaker 6>be a very interested party down the road.

0:11:56.080 --> 0:11:59.800
<v Speaker 2>And for those who care, one can actually invest directly in.

0:12:00.000 --> 0:12:04.040
<v Speaker 2>Formula one is a public traded company FWNK. I like

0:12:04.160 --> 0:12:07.800
<v Speaker 2>Formula one K, it's owned by John Malone and Liberty Media.

0:12:07.880 --> 0:12:11.560
<v Speaker 2>There's a million different share classes out there, but Formula one, Keith,

0:12:11.720 --> 0:12:14.360
<v Speaker 2>I mean, under John Malone's leadership, they've done a good

0:12:14.440 --> 0:12:18.080
<v Speaker 2>job of increasing rights, sporting rights and sponsorships and all

0:12:18.120 --> 0:12:20.880
<v Speaker 2>that kind of stuff, making it actually profitable.

0:12:20.480 --> 0:12:23.560
<v Speaker 6>Very profitable, Paul, And they've they've done a fantastic job

0:12:23.559 --> 0:12:26.000
<v Speaker 6>with the media rights. Again, they've really capitalized on this

0:12:26.240 --> 0:12:29.240
<v Speaker 6>huge surgeon popularity because remember F one was really more

0:12:29.280 --> 0:12:32.760
<v Speaker 6>of a European really not so big in America, but

0:12:33.120 --> 0:12:37.360
<v Speaker 6>they've really kind of capitalized on this huge momentum in

0:12:37.400 --> 0:12:40.160
<v Speaker 6>the United States. And you're absolutely right. They've added a

0:12:40.160 --> 0:12:42.480
<v Speaker 6>whole lot of races, made it a year round calendar,

0:12:42.559 --> 0:12:45.200
<v Speaker 6>lots of sponsorship money. So they've done a very good

0:12:45.240 --> 0:12:47.520
<v Speaker 6>job with this new Liberty Media management team.

0:12:47.800 --> 0:12:50.520
<v Speaker 2>Oh thanks to the Keith ron Ganathan Bloomberg Intelligence senior

0:12:50.600 --> 0:12:53.600
<v Speaker 2>US media analyst, coming up a tech breakdown as we

0:12:53.640 --> 0:12:57.920
<v Speaker 2>talk Tesla sales, Oracle and Apple outsourcing some AI assistants.

0:12:58.280 --> 0:13:01.319
<v Speaker 2>You're listening to Bloomberg Intelligence on Bloomberg Radio, providing in

0:13:01.679 --> 0:13:04.120
<v Speaker 2>research and data on two thousand companies and one hundred

0:13:04.120 --> 0:13:07.559
<v Speaker 2>and thirty industries. You can access Bloomberg Intelligence via bi

0:13:07.600 --> 0:13:11.000
<v Speaker 2>go on the terminal. I'm Paul Sweeney. This is Bloomberg.

0:13:15.800 --> 0:13:21.040
<v Speaker 1>You're listening to Bloomberg Intelligence with Paul Sweeney on Bloomberg Radio.

0:13:21.840 --> 0:13:25.040
<v Speaker 2>This is the Bloomberg Intelligence Show. I'm Paul Sweeney. Tesla

0:13:25.120 --> 0:13:27.960
<v Speaker 2>this past week reported second quarter deliveries on its vehicles

0:13:28.080 --> 0:13:30.360
<v Speaker 2>and it was not good. Tesla now finds itself in

0:13:30.400 --> 0:13:33.000
<v Speaker 2>a deep hole to dig out of to avoid consecutive

0:13:33.080 --> 0:13:36.080
<v Speaker 2>annual declines. To help break down the numbers normally, Linda

0:13:36.120 --> 0:13:39.800
<v Speaker 2>Nice Book to Pierre Ferubu, head of Global Technology Infrastructure

0:13:39.800 --> 0:13:41.200
<v Speaker 2>at New Street Research.

0:13:41.000 --> 0:13:43.760
<v Speaker 3>There is a bit of a positive surprise, like people

0:13:43.800 --> 0:13:48.080
<v Speaker 3>tracking very precisely deliveries in various markets by expecting slightly

0:13:48.120 --> 0:13:52.319
<v Speaker 3>lower numbers. The surprise comes from the US. The US

0:13:52.360 --> 0:13:54.480
<v Speaker 3>did is a place where it's the most difficult to

0:13:54.520 --> 0:13:57.360
<v Speaker 3>track the number of Tesla being delivered, and the US

0:13:57.440 --> 0:14:01.800
<v Speaker 3>beat beat expectations that model while coming in doing actree

0:14:01.880 --> 0:14:05.080
<v Speaker 3>quite well, that's good. But then the at the end

0:14:05.080 --> 0:14:06.960
<v Speaker 3>of the day, you have to remember the big picture.

0:14:07.360 --> 0:14:10.800
<v Speaker 3>We are down thirteen persons here on air. So we

0:14:11.520 --> 0:14:14.800
<v Speaker 3>are facing a situation where Tesla is struggling to sell cars.

0:14:15.360 --> 0:14:19.840
<v Speaker 3>A gross margin is in the latins. To me, Tesla

0:14:19.880 --> 0:14:22.320
<v Speaker 3>facing good demons should be able to defend like mid

0:14:22.560 --> 0:14:25.960
<v Speaker 3>mid twenties gross margin. So we have like we are

0:14:26.000 --> 0:14:28.320
<v Speaker 3>facing like a core business and not a business that

0:14:28.440 --> 0:14:30.280
<v Speaker 3>is really at a very low point that is struggling.

0:14:31.320 --> 0:14:34.479
<v Speaker 3>And so that's the difficulty. You have, like one structural

0:14:34.520 --> 0:14:38.400
<v Speaker 3>difficulty that is relatively that we understand relatively well. It's

0:14:38.440 --> 0:14:42.120
<v Speaker 3>that with their current product, Tesla has kind of saturated

0:14:42.120 --> 0:14:46.600
<v Speaker 3>its opportunity. Tesla needs lower high points to keep growing

0:14:47.080 --> 0:14:49.680
<v Speaker 3>and that's in the plan they're working on it. And

0:14:49.720 --> 0:14:51.920
<v Speaker 3>then you have a number of other issues. You know,

0:14:52.040 --> 0:14:54.840
<v Speaker 3>electric cars are less fashionable than they were a couple

0:14:54.920 --> 0:14:59.720
<v Speaker 3>of years ago. The Tesla brand has suffered, particularly in

0:14:59.800 --> 0:15:02.680
<v Speaker 3>New Rope where numbers are down like almost forty percent

0:15:02.960 --> 0:15:08.160
<v Speaker 3>on air, and so it is definitely it's difficult to quantify,

0:15:08.400 --> 0:15:13.040
<v Speaker 3>but it is a significant headwind as well. And overall,

0:15:13.080 --> 0:15:15.960
<v Speaker 3>you know, the economy is not right, the best you

0:15:15.960 --> 0:15:18.640
<v Speaker 3>can imagine for auto dim Yeah.

0:15:18.640 --> 0:15:20.840
<v Speaker 5>I mean when we look at the mag seven stocks,

0:15:20.840 --> 0:15:23.760
<v Speaker 5>we see Tesla as the primary laggard this year, down

0:15:23.800 --> 0:15:26.720
<v Speaker 5>about twenty three percent. And of course we know that

0:15:26.720 --> 0:15:29.760
<v Speaker 5>investors have really been vying for Musk's attention as he's

0:15:29.800 --> 0:15:32.880
<v Speaker 5>been really politically involved. So as we're seeing these numbers

0:15:32.960 --> 0:15:36.520
<v Speaker 5>come through, what do things like moving forward? Are these

0:15:36.600 --> 0:15:40.400
<v Speaker 5>numbers a massive impact or are the Tesla loyalists still

0:15:40.400 --> 0:15:44.120
<v Speaker 5>out there and is there some further positivity to come.

0:15:44.320 --> 0:15:47.720
<v Speaker 3>Yes, you the Tesla stock has been on a royal cost.

0:15:48.440 --> 0:15:50.440
<v Speaker 3>It's like a very low performer this year, but it

0:15:50.600 --> 0:15:53.600
<v Speaker 3>was like a clear out performer last year last year.

0:15:53.640 --> 0:15:57.000
<v Speaker 3>And as you said, you know, it's following, it's following,

0:15:57.040 --> 0:15:59.600
<v Speaker 3>you know, the political carrier, if I may say, of

0:15:59.680 --> 0:16:06.000
<v Speaker 3>the sea in a Musk and like this has created

0:16:06.040 --> 0:16:09.680
<v Speaker 3>this situation. Now if you look at the stock, you know,

0:16:09.800 --> 0:16:13.720
<v Speaker 3>since you know, like April first, what you see that

0:16:13.880 --> 0:16:16.720
<v Speaker 3>what tends to really move the stock is actually the

0:16:16.760 --> 0:16:20.560
<v Speaker 3>news flow around how the company is now focused on

0:16:20.600 --> 0:16:25.200
<v Speaker 3>deploying fleets of robot taxes. They've just started that in

0:16:25.840 --> 0:16:29.240
<v Speaker 3>a couple of weeks ago, like late late last months

0:16:29.720 --> 0:16:31.720
<v Speaker 3>and I think that's going to be the primary driver

0:16:32.360 --> 0:16:35.840
<v Speaker 3>of the stock going forward. Of course, there is a

0:16:35.880 --> 0:16:38.880
<v Speaker 3>lot of uncertainty on you know, how fast THETA is

0:16:38.920 --> 0:16:41.280
<v Speaker 3>going to be able to deploy robotaxy or even make

0:16:41.320 --> 0:16:43.920
<v Speaker 3>a profits, like generate the profits out of the robot

0:16:43.920 --> 0:16:48.000
<v Speaker 3>taxi fleet. But the size of the price is so

0:16:48.200 --> 0:16:50.760
<v Speaker 3>gigantic and so much more than the ATOL business that

0:16:51.000 --> 0:16:53.400
<v Speaker 3>this is probably what drives the stock going forward.

0:16:53.760 --> 0:16:57.560
<v Speaker 2>Are thanks to Pierre Fair ahead of Global Technology Infrastructure

0:16:57.600 --> 0:17:01.720
<v Speaker 2>at New Street Research with tech Oracle this past week

0:17:01.840 --> 0:17:04.600
<v Speaker 2>said it had signed a single cloud deal worth thirty

0:17:04.640 --> 0:17:07.520
<v Speaker 2>billion dollars in annual revenue. It's more than the current

0:17:07.520 --> 0:17:11.080
<v Speaker 2>size of its entire cloud infrastructure business. For more on

0:17:11.119 --> 0:17:13.920
<v Speaker 2>this deal and what this means for the computer software company,

0:17:13.960 --> 0:17:17.240
<v Speaker 2>we turned to Anorak Rana, Bloomberg Intelligence technology analyst.

0:17:17.880 --> 0:17:20.199
<v Speaker 8>We think this is part of the Stargate contract. This

0:17:20.320 --> 0:17:23.280
<v Speaker 8>is something that's going to flow from open aie, you know,

0:17:23.320 --> 0:17:27.040
<v Speaker 8>the combination between soft Bank, Uticle and open AI. So

0:17:27.080 --> 0:17:29.679
<v Speaker 8>if you remember there was a big deal, you know,

0:17:29.840 --> 0:17:32.000
<v Speaker 8>just I think a day or two after the president

0:17:32.040 --> 0:17:34.840
<v Speaker 8>took office, where Laddie Allison and you know got on

0:17:35.160 --> 0:17:37.760
<v Speaker 8>TV and talked about it. I you know, we think

0:17:37.800 --> 0:17:39.600
<v Speaker 8>this is a byproduct of that.

0:17:41.080 --> 0:17:44.479
<v Speaker 5>How is Oracle matching up with its competitors? I mean,

0:17:44.520 --> 0:17:47.600
<v Speaker 5>I know it's gained traction for renting out computing power

0:17:47.640 --> 0:17:49.679
<v Speaker 5>over the Internet, and of course it's been targeting a

0:17:49.680 --> 0:17:52.880
<v Speaker 5>lot of its clients that are focused on AI there.

0:17:53.040 --> 0:17:55.719
<v Speaker 5>But how does it look in comparison to peers?

0:17:56.480 --> 0:17:58.800
<v Speaker 8>Yeah, I think you know, it was really I go

0:17:58.960 --> 0:18:01.159
<v Speaker 8>back a few years. It was, you know, to be honest,

0:18:01.200 --> 0:18:04.320
<v Speaker 8>non existent about three years ago. So the revenue was

0:18:04.400 --> 0:18:06.879
<v Speaker 8>you know, just a handful of billion dollars or so,

0:18:07.200 --> 0:18:09.960
<v Speaker 8>compared to you know, somebody like an AWS which is

0:18:10.040 --> 0:18:12.520
<v Speaker 8>now running at a rundred of over one hundred billion dollars. So,

0:18:12.960 --> 0:18:15.960
<v Speaker 8>but this, if you look at it, in last year alone,

0:18:16.760 --> 0:18:19.719
<v Speaker 8>oracles infrastructure as a service business, which is what we

0:18:19.760 --> 0:18:22.840
<v Speaker 8>look as the proxy for their cloud infrastructure business, had

0:18:22.880 --> 0:18:26.240
<v Speaker 8>revenues of about ten billion dollars. So and then here

0:18:26.320 --> 0:18:29.320
<v Speaker 8>comes a contract that in three years and you know,

0:18:29.400 --> 0:18:32.720
<v Speaker 8>they will have thirty billion dollars annually from one just

0:18:32.800 --> 0:18:35.960
<v Speaker 8>one customer. So you could see just the overall what's

0:18:36.000 --> 0:18:39.399
<v Speaker 8>happening with AI? What is really need so much of

0:18:39.440 --> 0:18:42.919
<v Speaker 8>computing power to run these models, and this is you

0:18:42.960 --> 0:18:45.960
<v Speaker 8>know again they are going everywhere, but Oracle is you know,

0:18:45.960 --> 0:18:47.760
<v Speaker 8>one of the bigger beneficiaries over here.

0:18:48.520 --> 0:18:52.240
<v Speaker 2>Rich go rich, the world's richest people. Larry Ellison of

0:18:52.400 --> 0:18:55.680
<v Speaker 2>Oracle clocks in at number four, two hundred and twenty

0:18:55.760 --> 0:19:00.600
<v Speaker 2>nine billion dollars, up thirty seven billion dollars year to date.

0:19:01.520 --> 0:19:03.879
<v Speaker 2>The stock is up fifty two week high on a

0:19:03.960 --> 0:19:08.560
<v Speaker 2>rockets at an all time high. What's the bookcase for Oracle?

0:19:08.600 --> 0:19:14.120
<v Speaker 2>Here's just just another way to play cloud slash AI.

0:19:14.880 --> 0:19:17.879
<v Speaker 8>Yeah, so that's the bookcase. Definitely on that end, you

0:19:17.880 --> 0:19:20.239
<v Speaker 8>could see their growth rates are going to pick up

0:19:20.280 --> 0:19:22.440
<v Speaker 8>so much more than any of the other cloud providers,

0:19:22.560 --> 0:19:25.440
<v Speaker 8>and partially because they're you know, the numbers are too small.

0:19:25.480 --> 0:19:27.720
<v Speaker 8>As I said, They're only at about ten billion run

0:19:27.840 --> 0:19:29.840
<v Speaker 8>rate or so in this case at this point. So

0:19:30.320 --> 0:19:32.439
<v Speaker 8>that's one. But on the other side, you know, they

0:19:32.480 --> 0:19:34.800
<v Speaker 8>will have to spend a lot on capex right now,

0:19:35.040 --> 0:19:37.840
<v Speaker 8>so that capex number is going to go up. Margins

0:19:37.880 --> 0:19:40.520
<v Speaker 8>are going to most likely take a hit. But frankly speaking,

0:19:40.560 --> 0:19:43.399
<v Speaker 8>in this market right now, it's all about market share

0:19:43.440 --> 0:19:46.879
<v Speaker 8>gains and which of the companies can actually benefit from

0:19:46.920 --> 0:19:51.040
<v Speaker 8>all these large language model training or inference basically, you know,

0:19:51.119 --> 0:19:53.000
<v Speaker 8>they are you know, they're going everywhere. I mean look

0:19:53.000 --> 0:19:56.000
<v Speaker 8>at for example, code WEEP their growth rate. The SAME's

0:19:56.040 --> 0:19:59.600
<v Speaker 8>the case with Microsoft, Azure or EWS. I mean, everybody

0:19:59.600 --> 0:20:02.280
<v Speaker 8>in this particular ecosystem is going to make lots of money.

0:20:03.000 --> 0:20:05.240
<v Speaker 5>We know, expectations remain high for a lot of these

0:20:05.240 --> 0:20:08.359
<v Speaker 5>tech firms, especially as we think about the AI push.

0:20:08.400 --> 0:20:10.280
<v Speaker 5>What do investors want to see right now? What's the

0:20:10.320 --> 0:20:11.640
<v Speaker 5>next step for Oracle?

0:20:12.840 --> 0:20:15.000
<v Speaker 8>I think a lot of this would become to execution

0:20:15.119 --> 0:20:17.199
<v Speaker 8>in this case, because you know, this is we are

0:20:17.240 --> 0:20:21.399
<v Speaker 8>assuming flawless execution in terms of data centered expansion. But

0:20:21.440 --> 0:20:23.160
<v Speaker 8>what if they are not able to get enough power

0:20:23.200 --> 0:20:25.280
<v Speaker 8>in there out there? I mean, what if we get

0:20:25.280 --> 0:20:27.240
<v Speaker 8>into a shortage in that area. So there's going to

0:20:27.240 --> 0:20:29.360
<v Speaker 8>be a lot to you know, I would say ups

0:20:29.400 --> 0:20:32.000
<v Speaker 8>and downs, not just for article, but everybody in the

0:20:32.040 --> 0:20:35.960
<v Speaker 8>equation where maybe the project gets delayed some funding issues.

0:20:36.359 --> 0:20:38.879
<v Speaker 8>Right now, everything is fine when it comes to funding

0:20:38.920 --> 0:20:41.720
<v Speaker 8>for these particular projects, but you know, those are the

0:20:41.760 --> 0:20:44.000
<v Speaker 8>things that we would watch for. But other than that,

0:20:44.119 --> 0:20:46.240
<v Speaker 8>I think the the you know, future is really bright

0:20:46.320 --> 0:20:49.520
<v Speaker 8>for all the cloud providers because of the workloads that

0:20:49.560 --> 0:20:50.160
<v Speaker 8>are coming.

0:20:49.960 --> 0:20:53.800
<v Speaker 2>In our thanks to anaag Rana Bloomberg Intelligence technology analysts.

0:20:54.359 --> 0:20:57.000
<v Speaker 2>Closing out our tech segment is a story this week

0:20:57.040 --> 0:21:00.440
<v Speaker 2>from Apple. The tech giant shocked investors when our Mark

0:21:00.480 --> 0:21:03.840
<v Speaker 2>German announced that the company was considering using artificial intelligence

0:21:03.840 --> 0:21:07.480
<v Speaker 2>technology from Anthropic or open AI to power a new

0:21:07.600 --> 0:21:11.520
<v Speaker 2>version of Siri, potentially sidelining its own in house models.

0:21:11.760 --> 0:21:15.080
<v Speaker 2>Man Deep Seeing, Bloomberg Intelligence senior tech oust breaks it down.

0:21:15.480 --> 0:21:19.359
<v Speaker 9>Yeah, I mean, if you remember at WWDC, all they

0:21:19.400 --> 0:21:23.560
<v Speaker 9>showcase was that new liquid glass interface. There was no

0:21:23.720 --> 0:21:27.440
<v Speaker 9>mention of AI, so it was pretty obvious that they

0:21:27.480 --> 0:21:31.840
<v Speaker 9>had nothing new to showcase from an LLM perspective. And look,

0:21:32.320 --> 0:21:36.840
<v Speaker 9>given the astronomical rise of chat GPT and how it's

0:21:37.080 --> 0:21:43.000
<v Speaker 9>taken the user and engagement share, I mean everyone is

0:21:43.040 --> 0:21:47.120
<v Speaker 9>looking to use that kind of functionality on the apps

0:21:47.920 --> 0:21:51.320
<v Speaker 9>that live within the Apple ecosystem, whether it's your email,

0:21:51.520 --> 0:21:56.000
<v Speaker 9>your calendar, your contacts, like the photos that are stored

0:21:56.040 --> 0:21:59.480
<v Speaker 9>on iCloud. You have to ask to yourself, why can't

0:21:59.640 --> 0:22:03.760
<v Speaker 9>Apple will deploy AI in a similar fashion where I

0:22:03.800 --> 0:22:07.280
<v Speaker 9>can engage in a chatchipt type format. And so that's

0:22:07.359 --> 0:22:12.239
<v Speaker 9>the use case here. Obviously, Apple's own LM efforts have

0:22:12.359 --> 0:22:16.080
<v Speaker 9>gone nowhere because they have, frankly speaking, underinvested. I mean,

0:22:16.160 --> 0:22:19.160
<v Speaker 9>look at their capex versus all the other hyperskillers. They're

0:22:19.200 --> 0:22:23.080
<v Speaker 9>spending eighty billion dollars. Apple is spending ten billion dollars.

0:22:23.119 --> 0:22:26.440
<v Speaker 9>So it's just not the same level of investment, and

0:22:26.480 --> 0:22:32.560
<v Speaker 9>they underappreciated how transformational this generative AI LLLM wave is

0:22:32.640 --> 0:22:35.040
<v Speaker 9>going to be. And now they are partnering with an

0:22:35.160 --> 0:22:39.000
<v Speaker 9>Entropic or open Ai. I think Entropic makes more sense

0:22:39.040 --> 0:22:42.520
<v Speaker 9>to me because OpenAI has clearly said they have their

0:22:42.520 --> 0:22:46.639
<v Speaker 9>own hardware ambitions, and to my mind, Entropic is an

0:22:46.800 --> 0:22:50.560
<v Speaker 9>enterprise focused player. They have already partnered with Amazon and

0:22:50.680 --> 0:22:53.760
<v Speaker 9>in this case they probably will partner with Apple as well.

0:22:54.200 --> 0:22:57.760
<v Speaker 7>As Paul mentioned the stock market, it wasn't disappointed in

0:22:57.840 --> 0:23:01.560
<v Speaker 7>this snooze. The stock was up yesterday when Bloomberg's Markerman

0:23:01.720 --> 0:23:03.439
<v Speaker 7>you know wrote the story, which I do think it

0:23:03.480 --> 0:23:06.560
<v Speaker 7>came out he breaks yes, he does break everything. I

0:23:06.600 --> 0:23:09.000
<v Speaker 7>think the story came after the close, but still the

0:23:09.040 --> 0:23:13.960
<v Speaker 7>stock is hired today, so this is good. I mean,

0:23:14.240 --> 0:23:18.040
<v Speaker 7>talk a little bit more about the partnerships, because if

0:23:18.080 --> 0:23:23.080
<v Speaker 7>Anthropic is partnering with Amazon as well, Like, this isn't

0:23:23.119 --> 0:23:26.440
<v Speaker 7>really an exclusive deal that they're doing. Apple is just

0:23:26.480 --> 0:23:28.800
<v Speaker 7>going to have the same AI as all the other times.

0:23:28.920 --> 0:23:33.800
<v Speaker 9>Yeah, but Apple controls the distribution across their iOS devices,

0:23:33.840 --> 0:23:38.000
<v Speaker 9>and whether it's your tablet or your smartphone or macpcs,

0:23:38.359 --> 0:23:42.879
<v Speaker 9>it's the Apple iOS ecosystem. So if Ententropics LLM is

0:23:42.960 --> 0:23:46.280
<v Speaker 9>natively integrated, I mean, look at how much Microsoft has

0:23:46.359 --> 0:23:51.240
<v Speaker 9>benefited from open AI's partnership. Microsoft doesn't have their own LLLM.

0:23:51.520 --> 0:23:54.679
<v Speaker 9>The fact that they have risen so much is because

0:23:54.720 --> 0:23:57.800
<v Speaker 9>of the open Ai partnership. So partnership isn't a bad

0:23:57.840 --> 0:24:02.560
<v Speaker 9>thing for Apple, and in this case, clearly Entropic has

0:24:02.600 --> 0:24:06.280
<v Speaker 9>a very good LLM. On the tech side, maybe you

0:24:06.320 --> 0:24:10.560
<v Speaker 9>could argue in terms of multi modality open Ai and

0:24:10.600 --> 0:24:16.040
<v Speaker 9>Google are ahead, But for a text LLM, Entropics performance

0:24:16.160 --> 0:24:19.200
<v Speaker 9>is comparable at part with the frontier models. And that's

0:24:19.240 --> 0:24:22.600
<v Speaker 9>where it makes a ton of sense that they use Anthropic.

0:24:22.160 --> 0:24:25.080
<v Speaker 2>Thirty seconds, Can I think about this potent This announcement

0:24:25.440 --> 0:24:29.240
<v Speaker 2>similar to Apple saying we're going to use Google for search.

0:24:30.040 --> 0:24:32.600
<v Speaker 9>Yeah, And part of the reason why there is no

0:24:32.760 --> 0:24:36.359
<v Speaker 9>mention of Google here is because of that anti trust

0:24:36.520 --> 0:24:40.640
<v Speaker 9>case that's pending. So clearly what Apple wants to signal

0:24:40.800 --> 0:24:43.400
<v Speaker 9>is they don't want to do anything with Google right now,

0:24:43.480 --> 0:24:47.240
<v Speaker 9>given that monopoly lawsuit and the twenty plus billion dollar

0:24:47.280 --> 0:24:50.119
<v Speaker 9>of payment from Google to Apple, and right now they

0:24:50.160 --> 0:24:54.800
<v Speaker 9>are really diversifying their exposure to these LLM players. They

0:24:54.800 --> 0:24:57.320
<v Speaker 9>could have very well used in LLLM, and I wouldn't

0:24:57.320 --> 0:25:00.879
<v Speaker 9>be surprised down the line once this ad BODA cases

0:25:00.960 --> 0:25:05.000
<v Speaker 9>resolved and if it's if it works out fine, they

0:25:05.119 --> 0:25:08.960
<v Speaker 9>may end up using Google's LM as well. Apple's main

0:25:09.040 --> 0:25:12.840
<v Speaker 9>goal here is to have as many LLLM partners and

0:25:13.359 --> 0:25:17.119
<v Speaker 9>really not depend on just one, whether it's opening oranthropic.

0:25:17.240 --> 0:25:19.440
<v Speaker 9>They want five players, and I think they would be

0:25:19.480 --> 0:25:21.320
<v Speaker 9>willing to use anyone.

0:25:20.960 --> 0:25:23.400
<v Speaker 2>Our Thanks to Man Deep saying, Bloomberg Intelligence senior tech

0:25:23.440 --> 0:25:26.280
<v Speaker 2>industry analyst coming up on the program A Trio Big

0:25:26.320 --> 0:25:28.760
<v Speaker 2>Takes stories from this week you do not want to miss.

0:25:28.960 --> 0:25:31.760
<v Speaker 2>You're listening to Bloomberg Intelligence on Bloomberg Radio, providing in

0:25:31.800 --> 0:25:34.639
<v Speaker 2>depth research and data on two thousand companies in one

0:25:34.720 --> 0:25:37.600
<v Speaker 2>hundred and thirty industries. You can access Bloomberg Intelligence via

0:25:37.720 --> 0:25:41.760
<v Speaker 2>Bigo on the terminal. I'm Paul Sweeney, and this is Bloomberg.

0:25:47.600 --> 0:25:47.840
<v Speaker 10>Now.

0:25:48.560 --> 0:25:53.800
<v Speaker 1>You're listening to Bloomberg Intelligence with Paul Sweeney on Bloomberg Radio.

0:25:54.440 --> 0:25:56.200
<v Speaker 2>We wrap up the show with a trio big takes

0:25:56.240 --> 0:25:59.000
<v Speaker 2>stories from this past week worth highlighting. First up as

0:25:59.040 --> 0:26:01.800
<v Speaker 2>a story on why the US Treasury keeps getting hacked.

0:26:01.960 --> 0:26:04.399
<v Speaker 2>For more, Emily Grafe and I spoke to Jordan robertson

0:26:04.400 --> 0:26:06.880
<v Speaker 2>Bloomberg News cybersecurity reporter.

0:26:07.280 --> 0:26:09.919
<v Speaker 10>So yeah, our Big Take, our Bloomberg Big Take investigation

0:26:10.359 --> 0:26:14.800
<v Speaker 10>is about a series of really impactful cybersecurity attacks at

0:26:14.840 --> 0:26:17.720
<v Speaker 10>the US Treasury Department. There was a major attack in

0:26:17.880 --> 0:26:22.080
<v Speaker 10>twenty twenty, major attack in December, a major attack that

0:26:22.160 --> 0:26:24.800
<v Speaker 10>was disclosed earlier this year, which news that was broken

0:26:24.840 --> 0:26:28.399
<v Speaker 10>by our some of our Bloomberg colleagues. And the question

0:26:28.480 --> 0:26:30.600
<v Speaker 10>we set out to answer was why does the US

0:26:30.640 --> 0:26:33.360
<v Speaker 10>Treasury Department keep getting hacked? And why does it keep

0:26:33.359 --> 0:26:37.880
<v Speaker 10>getting hacked so badly? Every organization faces attempted hacking attacks.

0:26:38.320 --> 0:26:42.639
<v Speaker 10>Many organizations experience successful hacking attacks. It's always about the

0:26:42.760 --> 0:26:46.200
<v Speaker 10>depth though, of the intrusion. How far did the hackers

0:26:46.240 --> 0:26:48.880
<v Speaker 10>get and what did they get where they wanted to go?

0:26:49.160 --> 0:26:51.800
<v Speaker 10>And in each of these three attacks, the hackers got

0:26:51.840 --> 0:26:54.959
<v Speaker 10>about as far deep into the organization as you could imagine,

0:26:55.640 --> 0:26:57.480
<v Speaker 10>and what we set out to answer was how is

0:26:57.520 --> 0:27:00.399
<v Speaker 10>that happening? And one of the answers we came up

0:27:00.440 --> 0:27:03.480
<v Speaker 10>with is that, you know, the Treasury Department is one agency,

0:27:03.600 --> 0:27:07.440
<v Speaker 10>but with the cybersecurity, the cybersecurity of it is run

0:27:07.480 --> 0:27:10.840
<v Speaker 10>effectively as a series of like a half dozen different countries.

0:27:10.880 --> 0:27:15.080
<v Speaker 10>Almost these are subdivisions of the Treasury Department that have

0:27:15.160 --> 0:27:19.080
<v Speaker 10>their own cybersecurity budget allocated by Congress, they have their

0:27:19.119 --> 0:27:23.080
<v Speaker 10>own cybersecurity management, they have essentially of their own IT infrastructure.

0:27:23.400 --> 0:27:25.800
<v Speaker 10>And so what that means is some of these divisions

0:27:25.800 --> 0:27:27.959
<v Speaker 10>have really good security. Some of these divisions don't have

0:27:28.000 --> 0:27:31.119
<v Speaker 10>such good security. And you know, this is an organization

0:27:31.240 --> 0:27:33.680
<v Speaker 10>that I think a lot of people focus on because

0:27:33.680 --> 0:27:36.439
<v Speaker 10>of the financial aspect of what Treasury does. But it

0:27:36.480 --> 0:27:40.119
<v Speaker 10>does so much more than that. Investigates sanctions, it investigates

0:27:40.200 --> 0:27:43.520
<v Speaker 10>terrorists financing. It does so much more than just kind

0:27:43.560 --> 0:27:47.119
<v Speaker 10>of collect tax revenue, you know, and issue treasury bonds.

0:27:47.440 --> 0:27:52.440
<v Speaker 7>What is the reporting show about who's actually committing these

0:27:52.480 --> 0:27:56.760
<v Speaker 7>hacks and what exactly are the hacks on the Treasury.

0:27:57.040 --> 0:28:00.520
<v Speaker 10>So these are primarily nation state attack. So these are

0:28:00.560 --> 0:28:03.639
<v Speaker 10>foreign governments attacking the US Treasury Department. Again, there are

0:28:03.680 --> 0:28:06.720
<v Speaker 10>so many different types of cyber attacks that organizations face.

0:28:07.000 --> 0:28:08.639
<v Speaker 10>A lot of them are very low level and kind

0:28:08.680 --> 0:28:12.639
<v Speaker 10>of easily deflected. Increasingly nowadays we're seeing criminal groups, ransomware

0:28:12.680 --> 0:28:18.080
<v Speaker 10>groups affecting, hijacking networks, and disrupting networks that way. That's

0:28:18.160 --> 0:28:20.080
<v Speaker 10>not what we're talking about here with Treasury. We're talking

0:28:20.080 --> 0:28:23.879
<v Speaker 10>about espionage. We're talking about kind of large, long range

0:28:24.000 --> 0:28:28.480
<v Speaker 10>cyber espionage where these are foreign government backed actors whose

0:28:28.520 --> 0:28:31.200
<v Speaker 10>purpose is spying on data. So in the latest breach,

0:28:31.480 --> 0:28:34.120
<v Speaker 10>the Office of the Comptroller of the Currency that's the

0:28:34.160 --> 0:28:38.360
<v Speaker 10>regulator of America's national banks, had its email system hacked

0:28:38.440 --> 0:28:41.800
<v Speaker 10>for almost two years. So for almost two years, a

0:28:41.840 --> 0:28:44.760
<v Speaker 10>cyber attack group which hasn't been identified yet, you know,

0:28:44.760 --> 0:28:48.560
<v Speaker 10>it was conducting very advanced cyber espionage on the emails

0:28:48.560 --> 0:28:52.440
<v Speaker 10>and the communications of America's national bank regulator. That's not

0:28:52.480 --> 0:28:55.600
<v Speaker 10>supposed to happen. It led to this really extraordinary series

0:28:55.640 --> 0:28:59.360
<v Speaker 10>of events where several of the biggest US banks JP, Morgan,

0:28:59.440 --> 0:29:04.160
<v Speaker 10>bny ME and others severed there temporarily paused their electronic

0:29:04.240 --> 0:29:07.720
<v Speaker 10>sharing of communicate of data with their regulator as a

0:29:07.760 --> 0:29:10.680
<v Speaker 10>result of this breach. That's really extraordinary to have a

0:29:10.720 --> 0:29:14.920
<v Speaker 10>regulated entity tell their regulator your network is not safe

0:29:15.000 --> 0:29:17.719
<v Speaker 10>enough for me to transmit data to That was the

0:29:17.720 --> 0:29:19.960
<v Speaker 10>incident that really compelled us to take a deeper look

0:29:19.960 --> 0:29:21.760
<v Speaker 10>at this and try to figure out what's going on

0:29:21.800 --> 0:29:24.120
<v Speaker 10>at Treasury. And I might add as well, this is

0:29:24.160 --> 0:29:26.959
<v Speaker 10>at a time that you know, Congress has allocated hundreds

0:29:27.000 --> 0:29:31.560
<v Speaker 10>of millions of additional dollars to Treasury to enhance their cybersecurity,

0:29:31.840 --> 0:29:34.640
<v Speaker 10>and they've spent that money. They have done things, but

0:29:34.680 --> 0:29:38.640
<v Speaker 10>they have still not been effective fully in preventing these attacks.

0:29:38.880 --> 0:29:42.600
<v Speaker 2>I noticing your reporting, Jordan, there's been a lot of

0:29:42.920 --> 0:29:47.080
<v Speaker 2>I guess turnover or departures by cybersecurity people within the

0:29:47.160 --> 0:29:49.160
<v Speaker 2>Treasury Department. Did that have any role in this?

0:29:49.200 --> 0:29:49.360
<v Speaker 11>Do?

0:29:49.360 --> 0:29:51.880
<v Speaker 10>We think that's right? So another interesting aspect of the

0:29:51.960 --> 0:29:55.600
<v Speaker 10>reporting is that you know, Treasury senior most cybersecurity officials,

0:29:55.640 --> 0:29:58.560
<v Speaker 10>from the Chief Technology Officer and the Chief Information Officer

0:29:58.600 --> 0:30:00.840
<v Speaker 10>and all their deputies, there have been you know, more

0:30:00.880 --> 0:30:03.600
<v Speaker 10>than a half dozen of these individuals who have left

0:30:03.640 --> 0:30:08.040
<v Speaker 10>Treasury since the Trump administration took office. A lot of

0:30:08.080 --> 0:30:11.080
<v Speaker 10>the attention with Elon Musk and the Doge group has

0:30:11.120 --> 0:30:14.280
<v Speaker 10>been focused you know, understandably on the layoffs. This is

0:30:14.320 --> 0:30:16.400
<v Speaker 10>not a case of layoffs. This is primarily a case

0:30:16.440 --> 0:30:19.720
<v Speaker 10>of buyouts. So when the Doge group, you know, has

0:30:19.800 --> 0:30:23.920
<v Speaker 10>offered buyouts to large numbers of government employees, what's happened

0:30:23.960 --> 0:30:27.360
<v Speaker 10>at Treasury is almost all of the senior most cybersecurity

0:30:27.400 --> 0:30:30.440
<v Speaker 10>officials have taken the buyout. And what we've been told

0:30:30.520 --> 0:30:32.600
<v Speaker 10>is that, in fact, some of those individuals may have

0:30:32.680 --> 0:30:36.120
<v Speaker 10>even supported the Doge effort and the idea that you know,

0:30:36.280 --> 0:30:40.640
<v Speaker 10>consolidating Treasury's IT infrastructure would help improve security. But all

0:30:40.680 --> 0:30:43.280
<v Speaker 10>of those folks are gone. So the cybersecurity leadership at

0:30:43.320 --> 0:30:46.920
<v Speaker 10>Treasury is almost entirely gone, you know, at a time

0:30:46.960 --> 0:30:50.240
<v Speaker 10>where it's facing kind of unprecedented levels of cyber attacks

0:30:50.280 --> 0:30:51.840
<v Speaker 10>and successful cyber attacks.

0:30:52.080 --> 0:30:56.440
<v Speaker 2>Our thanks to Jordan robertson Bloomberg News cybersecurity reporter. The

0:30:56.480 --> 0:31:00.800
<v Speaker 2>next Big Takes stories entitled Electronic Warfare Crashes Global Shipping's

0:31:00.880 --> 0:31:04.360
<v Speaker 2>navigation systems. It highlights how the Iran Israel war exposed

0:31:04.360 --> 0:31:06.920
<v Speaker 2>a critical flaw in the satellite based systems that makes

0:31:07.280 --> 0:31:10.600
<v Speaker 2>the industry hauling eighty percent of global trade vulnerable the

0:31:10.720 --> 0:31:14.120
<v Speaker 2>mass gymming. Jack Whittles is Bloomberg News Oil and Shipping reporter.

0:31:14.480 --> 0:31:18.640
<v Speaker 11>So we looked at shipping data around the Persian Gulf,

0:31:18.840 --> 0:31:22.280
<v Speaker 11>so obviously relevant to the israel around war, but also

0:31:22.640 --> 0:31:26.920
<v Speaker 11>the Red Sea, the Baltic and the Black Sea, and

0:31:26.960 --> 0:31:30.440
<v Speaker 11>we basically saw a big spike in the number of

0:31:30.840 --> 0:31:34.520
<v Speaker 11>strange signals from ships. And what I mean by strange

0:31:34.560 --> 0:31:38.920
<v Speaker 11>signals from ships is ships showing that they are in

0:31:39.000 --> 0:31:42.480
<v Speaker 11>impossible positions. So, for instance, we had a ship in

0:31:42.720 --> 0:31:45.440
<v Speaker 11>the Persian Gulf saying that it was on the edge

0:31:45.440 --> 0:31:49.080
<v Speaker 11>of a camel racetrack. In the UAE, we had a

0:31:49.120 --> 0:31:52.320
<v Speaker 11>ship jumping from off the coast of Saudi Arabia, which

0:31:52.400 --> 0:31:54.200
<v Speaker 11>is on the western side of the Persian Gulf, all

0:31:54.200 --> 0:31:56.840
<v Speaker 11>the way to Iran and then back again in one day,

0:31:57.400 --> 0:32:00.520
<v Speaker 11>which is obviously impossible, especially as the j to Iran

0:32:00.720 --> 0:32:02.200
<v Speaker 11>was on land in Iran.

0:32:02.680 --> 0:32:06.720
<v Speaker 5>Jack. Have we seen this type of signal interferences within

0:32:06.880 --> 0:32:09.400
<v Speaker 5>any other sort of geopolitical crises.

0:32:10.360 --> 0:32:14.600
<v Speaker 11>We have seen it before, but the number when we've

0:32:14.640 --> 0:32:17.760
<v Speaker 11>done our analysis, the number that we've done is massively

0:32:17.960 --> 0:32:20.840
<v Speaker 11>increased for ships appearing on land. In June, there was

0:32:20.880 --> 0:32:23.960
<v Speaker 11>a really huge spike for ships appearing on land in

0:32:24.000 --> 0:32:26.280
<v Speaker 11>the areas that we looked at. So that was again

0:32:26.400 --> 0:32:28.800
<v Speaker 11>the Red Sea, Black Sea, Baltic and push it off.

0:32:29.360 --> 0:32:32.920
<v Speaker 2>So Jack, is this just the standard performance of this

0:32:33.320 --> 0:32:36.479
<v Speaker 2>satellite technology, i e. It's not great? Or is it

0:32:36.520 --> 0:32:40.760
<v Speaker 2>in fact the subject of some type of electronic warfare maybe?

0:32:40.760 --> 0:32:41.080
<v Speaker 2>Do we know?

0:32:41.680 --> 0:32:46.080
<v Speaker 11>Yeah? So's there's two ways that this equipment can be

0:32:46.120 --> 0:32:50.080
<v Speaker 11>interfered with. There's what's called jamming, where the signals are

0:32:50.160 --> 0:32:54.520
<v Speaker 11>essentially overwhelmed, and there's what's called spoofing, where ships are

0:32:54.560 --> 0:32:57.960
<v Speaker 11>fed a false signal, so they're specifically told that there's

0:32:58.000 --> 0:33:00.440
<v Speaker 11>somewhere that they're not. So went on to about these

0:33:00.440 --> 0:33:03.520
<v Speaker 11>satellite navigation systems. They're using GPS, so you know, the

0:33:03.520 --> 0:33:05.080
<v Speaker 11>same sort of thing that's on your Google Maps. So

0:33:05.080 --> 0:33:06.800
<v Speaker 11>it'd be like if the blue dot on your Google

0:33:06.840 --> 0:33:09.040
<v Speaker 11>Maps that tells you where you are just suddenly told

0:33:09.080 --> 0:33:12.360
<v Speaker 11>you that you were somewhere you weren't. So that's obviously

0:33:12.880 --> 0:33:15.880
<v Speaker 11>quite a big problem when you consider that if you're

0:33:15.880 --> 0:33:18.560
<v Speaker 11>in charge of an oil tanker and there are lots

0:33:18.600 --> 0:33:20.680
<v Speaker 11>of oil tankers around you, and it can take you

0:33:20.840 --> 0:33:24.120
<v Speaker 11>kilometers to stop, and you're not sure where all the

0:33:24.120 --> 0:33:27.120
<v Speaker 11>other ships are. That can be a massive, massive problem.

0:33:27.360 --> 0:33:29.400
<v Speaker 5>I see in your story that alarm bells are also

0:33:29.560 --> 0:33:32.000
<v Speaker 5>starting to ring in the insurance industry.

0:33:32.840 --> 0:33:37.680
<v Speaker 11>Yes, you know, it's a real big problem. If it

0:33:37.720 --> 0:33:41.720
<v Speaker 11>wouldn't necessarily invalidate your insurance is my understanding. If you

0:33:41.760 --> 0:33:44.440
<v Speaker 11>know your ship, you know, god forbid, had to crash

0:33:45.200 --> 0:33:48.480
<v Speaker 11>as a result of jamming. But if the crew, if

0:33:48.520 --> 0:33:53.000
<v Speaker 11>their navigation system was jammed and they didn't do anything

0:33:53.040 --> 0:33:56.400
<v Speaker 11>about it, and then something happened, then I think that

0:33:56.400 --> 0:33:58.880
<v Speaker 11>that could cause problems from an insurance point of view.

0:33:59.320 --> 0:34:01.880
<v Speaker 2>Thanks to Jack Those, Bloomberg News Oil and Shipping reporter,

0:34:02.280 --> 0:34:05.640
<v Speaker 2>our final Big Takes story talks about America's hot garbage

0:34:05.680 --> 0:34:08.800
<v Speaker 2>problem and how overheating landfills across the country are spewing

0:34:08.880 --> 0:34:12.320
<v Speaker 2>toxic gases and geysers or trash juice. Yeah. Lar Bliss

0:34:12.360 --> 0:34:14.359
<v Speaker 2>is an editor for Bloomberg Business Week.

0:34:14.560 --> 0:34:16.400
<v Speaker 12>Maybe I'll just start with a little bit of background

0:34:16.480 --> 0:34:19.120
<v Speaker 12>about how I came across this story. I found some

0:34:19.239 --> 0:34:23.719
<v Speaker 12>data on LinkedIn sometime last year that suggested fires at

0:34:23.760 --> 0:34:27.720
<v Speaker 12>recycling facilities. We're skyrocketing, and we've probably all heard about

0:34:27.719 --> 0:34:31.279
<v Speaker 12>this as we all throw bait pens and electric toothbrushes

0:34:31.440 --> 0:34:34.160
<v Speaker 12>and even smartphones, you know, some of us into our

0:34:34.160 --> 0:34:37.120
<v Speaker 12>recycling bins or trash cans, and that can cause real

0:34:37.160 --> 0:34:40.640
<v Speaker 12>problems because of the lithium batteries. And that really made

0:34:40.680 --> 0:34:43.400
<v Speaker 12>me wonder what was happening in kind of the final

0:34:43.480 --> 0:34:46.960
<v Speaker 12>resting place for so much of our trash, which are landfills.

0:34:47.200 --> 0:34:51.080
<v Speaker 12>And it turns out a lot and as you mentioned,

0:34:51.239 --> 0:34:53.720
<v Speaker 12>my colleague Rachel and I really took a deep dive

0:34:53.880 --> 0:34:57.879
<v Speaker 12>into some of the problems that can arise as we

0:34:58.080 --> 0:35:01.239
<v Speaker 12>pile up our waist higher and deeper burb and this

0:35:01.360 --> 0:35:05.200
<v Speaker 12>landfill in Los Angeles County is called Chiquita Canyon, and

0:35:05.280 --> 0:35:09.720
<v Speaker 12>since twenty twenty two, temperatures have been climbing to above

0:35:09.920 --> 0:35:13.960
<v Speaker 12>two hundred degrees in pockets of waste. That's like forty

0:35:13.960 --> 0:35:17.880
<v Speaker 12>percent above the EPA safety standard. And this is a

0:35:17.880 --> 0:35:21.160
<v Speaker 12>big problem because what that's doing is the trash breaks

0:35:21.200 --> 0:35:25.359
<v Speaker 12>down deep below the surface at these really scorching temperatures.

0:35:25.400 --> 0:35:29.960
<v Speaker 12>It's releasing toxic gases, it's releasing geysers of trash juice

0:35:30.920 --> 0:35:34.120
<v Speaker 12>and these really noxious fumes, and it's making people sick

0:35:34.600 --> 0:35:35.840
<v Speaker 12>in the nearby community.

0:35:36.000 --> 0:35:36.480
<v Speaker 8>And what I.

0:35:36.480 --> 0:35:40.520
<v Speaker 12>Discovered is that there's debate about what is actually going

0:35:40.560 --> 0:35:43.279
<v Speaker 12>on and even kind of how to describe what I

0:35:43.440 --> 0:35:47.319
<v Speaker 12>just shared with you, the kind of basic facts. Regulators

0:35:47.320 --> 0:35:51.920
<v Speaker 12>in California suspect that the landfill is smoldering due to

0:35:52.080 --> 0:35:55.600
<v Speaker 12>the operator letting too much oxygen in, and this is

0:35:55.600 --> 0:35:58.360
<v Speaker 12>a problem that's known to start fires, which goes against

0:35:58.400 --> 0:36:02.399
<v Speaker 12>federal regulations. And the operator disputes that and says nothing

0:36:02.480 --> 0:36:04.960
<v Speaker 12>is on fire and says that this is an example

0:36:05.080 --> 0:36:07.640
<v Speaker 12>of a phenomenon the industry has seen a lot of

0:36:07.719 --> 0:36:11.560
<v Speaker 12>in the last twenty years, these elevated temperature landfills.

0:36:12.400 --> 0:36:15.000
<v Speaker 5>Or a really interesting story, what when you were doing

0:36:15.000 --> 0:36:18.040
<v Speaker 5>your reporting, what did you find out about what residents

0:36:18.080 --> 0:36:22.120
<v Speaker 5>are doing to rectify this issue? Who's to blame in

0:36:22.160 --> 0:36:22.840
<v Speaker 5>this situation?

0:36:23.480 --> 0:36:25.279
<v Speaker 12>Yeah, I mean, I think that is where a lot

0:36:25.320 --> 0:36:29.920
<v Speaker 12>of the debate comes down. You know, the waste industry

0:36:30.040 --> 0:36:32.600
<v Speaker 12>will say that, you know, these landfills that have overheated,

0:36:33.400 --> 0:36:37.000
<v Speaker 12>in some cases, they've been tied to you know, specific

0:36:37.600 --> 0:36:42.040
<v Speaker 12>reactive waste streams, right like aluminum dross, which is a

0:36:42.080 --> 0:36:45.000
<v Speaker 12>byproduct of smelting, you know, twenty years later or years

0:36:45.080 --> 0:36:49.320
<v Speaker 12>later reacting under the surface. You know, in other cases

0:36:49.360 --> 0:36:52.200
<v Speaker 12>like in Chikida Canyon. The regulators at the at the

0:36:52.239 --> 0:36:54.800
<v Speaker 12>state are saying, no, this is or they suspect I

0:36:54.840 --> 0:36:57.239
<v Speaker 12>should say that this is because of you know, the

0:36:57.280 --> 0:37:01.800
<v Speaker 12>operator basically mismanaging the gas collection system and their landfill.

0:37:02.320 --> 0:37:04.960
<v Speaker 12>And so this back and forth I think actually makes

0:37:05.520 --> 0:37:09.719
<v Speaker 12>you know, accountability somewhat challenging. But I will say in California,

0:37:10.040 --> 0:37:12.760
<v Speaker 12>you know, the state is is uh, you know, issuing

0:37:12.880 --> 0:37:16.160
<v Speaker 12>violations uh, you know, on a regular basis to this operator.

0:37:17.040 --> 0:37:20.040
<v Speaker 12>But for residents, you know, they're really kind of stuck

0:37:20.160 --> 0:37:23.400
<v Speaker 12>in their homes, you know, breathing in these these toxic

0:37:23.480 --> 0:37:27.320
<v Speaker 12>fumes and and these noxious odors, and they feel like

0:37:27.360 --> 0:37:31.120
<v Speaker 12>they can't sell their homes because of the financial barriers

0:37:31.239 --> 0:37:34.200
<v Speaker 12>and and you know even ethical kind of questions about

0:37:34.239 --> 0:37:37.160
<v Speaker 12>putting another family in the same situation, and so they

0:37:37.200 --> 0:37:41.840
<v Speaker 12>feel kind of stuck and and at a loss for

0:37:41.840 --> 0:37:43.040
<v Speaker 12>for kind of how to move forward.

0:37:43.239 --> 0:37:46.399
<v Speaker 2>Laura, who owns landfills across the US. Are these all

0:37:46.480 --> 0:37:47.600
<v Speaker 2>privately owned?

0:37:48.239 --> 0:37:51.640
<v Speaker 12>Not all of them are, but but many are. The

0:37:51.760 --> 0:37:54.719
<v Speaker 12>landfill I focused on in Los Angeles County is is

0:37:55.000 --> 0:37:59.000
<v Speaker 12>owned and managed by Waste Connections. There's certainly other you know,

0:37:59.080 --> 0:38:03.440
<v Speaker 12>large players in the industry Republic Services waste management, but

0:38:03.520 --> 0:38:06.960
<v Speaker 12>some of the affected landfalls I looked at were municipally

0:38:06.960 --> 0:38:11.520
<v Speaker 12>owned to Bristol Landfill in Virginia has been problematic in

0:38:11.560 --> 0:38:13.680
<v Speaker 12>the last several years, a lot of the same kind

0:38:13.719 --> 0:38:17.279
<v Speaker 12>of symptoms I've been describing affecting communities out there.

0:38:17.560 --> 0:38:20.160
<v Speaker 2>Our thanks to Laura Bliss, Bloomberg BusinessWeek editor, you can

0:38:20.239 --> 0:38:22.000
<v Speaker 2>check out all of the Big Takes stories by going

0:38:22.000 --> 0:38:24.879
<v Speaker 2>to Bloomberg dot com slash Big Take. That's this week's

0:38:25.000 --> 0:38:27.759
<v Speaker 2>edition of Bloomberg Intelligence on Bloomberg Radio, providing in depth

0:38:27.800 --> 0:38:30.080
<v Speaker 2>research and data on two thousand companies and one hundred

0:38:30.080 --> 0:38:33.040
<v Speaker 2>and thirty industries. And remember you can access Bloomberg Intelligence

0:38:33.120 --> 0:38:36.120
<v Speaker 2>via Big on the terminal. I'm Paul Sweeney. Stay with us.

0:38:36.120 --> 0:38:38.839
<v Speaker 2>Today's top stories and global business headlines are coming up

0:38:39.120 --> 0:38:41.920
<v Speaker 2>right now.