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Speaker 1: Bloomberg Audio Studios, podcasts, radio news. You're listening to the

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Speaker 1: Bloomberg Intelligence Podcast. Catch us live weekdays at ten am

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Speaker 1: Eastern on Effo card Playing and broyd Otto with the

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Speaker 1: Bloomberg Business App. Listen on demand wherever you get your podcasts,

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Speaker 1: or watch us live on YouTube.

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Speaker 2: The Bloomberg Dollar Index is that the highs of the

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Speaker 2: year so far. You're a dollar is one oh seven.

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Speaker 2: You have, Yes, the year is a little bit stronger

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Speaker 2: against the dollar. But man, it was a really tough

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Speaker 2: week over the last week with the turmoil in French politics.

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Speaker 2: Luckily we have an expert with us. Marcus Ashworth is

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Speaker 2: joining us. He is from Bloomberg Opinion. I haven't talked

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Speaker 2: to you Marcus in I don't know ten months.

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Speaker 3: Yeah, it's been ages too long, too long.

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Speaker 2: It is so good to hear your voice. Okay. We

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Speaker 2: love about you is because you have opinions. What do

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Speaker 2: you make of what's unfolding in France right now?

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Speaker 3: Such a shy retiring title on it.

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Speaker 4: How what do I make of it?

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Speaker 3: I mean, look, it's not a crisis yet anyway. I

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Speaker 3: think it's a problem which was three years out in

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Speaker 3: the future in twenty seven. Whoever's going to replace mac Rol,

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Speaker 3: he's just rolled the dice and brought it forward by

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Speaker 3: three years. It's trying to solve for probably a bigger

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Speaker 3: problem now earlier and getting a better result, perhaps he hopes.

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Speaker 3: What it has highlighted is that there's been a long,

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Speaker 3: deep seated, ever growing fiscal problem in France where they've

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Speaker 3: they've hidden essentially, I mean, not how to get away

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Speaker 3: with it for ages and ages. First, we had a

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Speaker 3: Fitch down grade in October, we got a S and

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Speaker 3: P down grade in the end of May, and we've

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Speaker 3: got Moodies now having a sort of little think about

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Speaker 3: really do do they genuinely think France is worth a

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Speaker 3: double A two? So that's because the fiscal deaths in

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Speaker 3: France has risen to five point five percent of GDP,

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Speaker 3: and more importantly, it's debt g UP is starting to rise.

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Speaker 5: It again.

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Speaker 3: They had this been great hope of this downward glide

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Speaker 3: path of both France and Italy. That's not happening. It

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Speaker 3: hadn't done happen at all last year when quite the

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Speaker 3: other way, and doesn't look like it's going to get

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Speaker 3: better for least down for this twenty twenty seventh period.

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Speaker 3: So no one thinks that even the current situation would

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Speaker 3: own seen any physical improvement with potential of a non

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Speaker 3: Macron sort of controlled prime minister and government. That means

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Speaker 3: that quite the reverse is going to get even worse,

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Speaker 3: and that isn't great use for France, isn't great use

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Speaker 3: to the European Union. They hate political volitility. They get

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Speaker 3: very spooky, particularly of a potentially eurosceptic or you know,

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Speaker 3: pro leaving the European Unions it once worked party might

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Speaker 3: get into some form of power. They get very antsy.

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Speaker 3: So that's why you're best to sell or get that

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Speaker 3: or stay out of France until it settles down. June

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Speaker 3: seventh will get the June July seventh, Sorry, we'll get

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Speaker 3: the second round final results the parliamentary elections. Macron's staying

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Speaker 3: around with other three years.

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Speaker 6: I love the whole snap election thing. I like because

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Speaker 6: we're over here in the US, We're going month after

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Speaker 6: month year just to get to November. So I kind

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Speaker 6: of like this whole snap election thing here. But what's

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Speaker 6: behind Marcus? Do you think that the rise of Marine

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Speaker 6: le pen and the far right? Is it what we're

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Speaker 6: seeing just around the world. Is it political, is it economical?

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Speaker 7: What's kind of really dru.

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Speaker 3: I mean, I don't think you can call her far right.

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Speaker 3: To my mind, she's a socialist. She's pretty hard left, okay,

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Speaker 3: and the fact that she's a national so called champion,

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Speaker 3: and that's what she wants to push, you know, French

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Speaker 3: pension rights, welfare rights, she's very pro union. So in

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Speaker 3: some senses, I know it's easy to label them far right.

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Speaker 3: But the point here is is that you know what

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Speaker 3: clearly she's standing for. It is a sense of enough

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Speaker 3: already from the French people on mass immigrant This is

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Speaker 3: happening in Italy, this has definitely happened in the UK,

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Speaker 3: It's happening ever in Europe, and it's happening in the US.

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Speaker 3: So look, this is a global problem. Isn't going to

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Speaker 3: get solved anytime soon, but you know you're going to

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Speaker 3: get Look what's happened in the UK. We're getting Richie

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Speaker 3: Sinak going to get bounced out because he's failed to

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Speaker 3: live up to anything he said he would do. But

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Speaker 3: we're having similar across the European elections, where the results

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Speaker 3: tended to favor the more should we say, anti immigration

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Speaker 3: parties whether some of them are left or right is

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Speaker 3: a subjective point. But look, it's this is just bad

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Speaker 3: fiscal situations getting worse combined with you know, that awful

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Speaker 3: thing that European politics really doesn't like is that fear

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Speaker 3: that the European Union, that euro project might come under question.

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Speaker 3: And that's when investors, which you believe very much in

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Speaker 3: this whole France German bedrock and that eving has been

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Speaker 3: calmed down. We've got the EU isshing bonds by the

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Speaker 3: gazillion in the middle, lots of pandemic programs spraying money everywhere,

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Speaker 3: and yet it isn't enough. And that's a little bit

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Speaker 3: of a worry. I personally, I see it as a

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Speaker 3: little reality check and maybe in the long run this

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Speaker 3: might be better for Europe if they can get their

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Speaker 3: act together. I don't see it as a proper euro

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Speaker 3: crisis or anything like it.

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Speaker 2: Have you noticed or are you hearing flows coming out

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Speaker 2: of Europe into the US because of the political issues there.

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Speaker 2: I mean, we have our own mess.

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Speaker 3: But what we do have is Convidiot, Alex, you've got

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Speaker 3: it all already. What more do you want? You can't

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Speaker 3: want more of our money?

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Speaker 2: Yes I do, I want all of your money.

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Speaker 3: Everyone in Europe is already already over the way in

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Speaker 3: the US. Look I mean, I would say it's more

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Speaker 3: like the US investors who might have been tempted to

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Speaker 3: get out of the US and diversified long last, coming

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Speaker 3: up to your elections, may have been tempted to sort

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Speaker 3: of go into Europe and have a little sniff, particularly

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Speaker 3: around banks and things like that. That's why the worst

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Speaker 3: performance so far being French banks. They're being able to

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Speaker 3: He's spanked. For the reason why I've been spank is

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Speaker 3: because I think there's a very popular situation for US

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Speaker 3: investors looking to play the old rebound there, and that

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Speaker 3: I think is what we've seen. We've seen some fast

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Speaker 3: money exit stays left. I don't think European investors are

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Speaker 3: going to go anywhere. I think Japanese had already long

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Speaker 3: thought very carefully about the so called budden plus strategy,

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Speaker 3: where you bought French bonds, you locked him like with Germany,

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Speaker 3: you've got in an extra bit of yield that works

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Speaker 3: a few years ago, not so much anymore, but yeah,

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Speaker 3: there may be a little bit. And so I was saying,

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Speaker 3: is I just don't think any new money is going

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Speaker 3: to come in until July seventh. Why would it. It's

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Speaker 3: crazy to take more risks you need to, and you've

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Speaker 3: got no visibility on the outcome. There's likely to be

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Speaker 3: one or two more bumps in the road before we

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Speaker 3: have a clear idea of the way the French system works.

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Speaker 3: You have this first round on June the thirtieth, and

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Speaker 3: then and only then you get it clear out clarity

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Speaker 3: of what who goes forward into the second round and

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Speaker 3: you can work out which personalities are going to be

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Speaker 3: doing probably better or worse with more accurate polling. But

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Speaker 3: that will come clearer as it days go by. I

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Speaker 3: know that this afternoon actually France has thunder a little

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Speaker 3: bit better against Germany. French yels have actually gone nowhere

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Speaker 3: in the last week of a bit. It's just the

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Speaker 3: German yields have fallen hard because they're following, Yes, you've

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Speaker 3: got Alex, they're following the US deals lower. It's all

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Speaker 3: about the US.

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Speaker 7: Seem told you told you, hey, Marcus.

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Speaker 6: It was just a few weeks ago when mister maccron

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Speaker 6: hosted a basically come back to France conference where David

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Speaker 6: Solomon Goldman Sachs was there and mister moynihand.

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Speaker 5: From Bank of America.

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Speaker 7: I mean, is France open for business? Are people investing in?

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Speaker 3: They're still mark the spot. This is where Jamie Diamond stood.

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Speaker 3: Now we have a little competition. Funnily off, the first

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Speaker 3: thing that a labor government, almost certain in the UK,

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Speaker 3: are going to do is good, do exactly this. Come

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Speaker 3: to the UK. Everything's brilliant, come back to your business.

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Speaker 3: So that part has been very good at this and

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Speaker 3: definitely there's been some signs that not so much that

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Speaker 3: the city's losing jobs, but that France is attracting more

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Speaker 3: financial jobs. It's quite great tax breaks to go there.

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Speaker 3: At the same time, clearly they want to promote all

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Speaker 3: foreign direct investment and arguably financial big movers you know, Silhadel,

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Speaker 3: JP Morgan, Back of American et cetera. Are responding a

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Speaker 3: little bit to the challenge. And one interesting thing is

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Speaker 3: I think that Macromo is going to relax a bit

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Speaker 3: on the how much that severance pay has to be

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Speaker 3: in France. Whi's one of the big things that the

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Speaker 3: banks don't like is that the cost of actually losing

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Speaker 3: people and they change their minds on their expansion plans.

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Speaker 3: But for the moment, Yeah, I think they've done a

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Speaker 3: good job in France and probably outside of London. Paris

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Speaker 3: is the logical place for the most financial companies and

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Speaker 3: banks are particularly to go. But you know, again they

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Speaker 3: don't need this att of published It's not very good

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Speaker 3: for them.

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Speaker 2: Mark's always a pleasure. It was so good to chat

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Speaker 2: with you. Definitely miss all your commentary. Marcus Ashworth of

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Speaker 2: Bloomberg Opinion, And I have to say my Father's Day

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Speaker 2: dinner last night, for some reason, doing business in France

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Speaker 2: came up in the conversation and about unions and I

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Speaker 2: was like, what does this mean? Like are are we

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Speaker 2: a peak union? Like what is the significance of regular

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Speaker 2: people on the upper West side talking about.

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Speaker 6: Yeah, I mean again, we had that conference, you know,

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Speaker 6: in Paris or in France a few weeks ago, and

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Speaker 6: again all the big heavyweight from Wall Street Global Wall

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Speaker 6: Street were there and it just said basically we were

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Speaker 6: open for business. And you know a lot of the

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Speaker 6: big financial firms have moved some jobs out of London

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Speaker 6: into Paris in additions to other European capitals. But you

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Speaker 6: just think about the taxes and some of the social

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Speaker 6: programs and is it really open for business, and can

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Speaker 6: they attract significant foreign global investment into that country?

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Speaker 3: So?

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Speaker 2: Or is it like the open more open? It's going

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Speaker 2: to be versus other countries, right, like the cleaner shirt.

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Speaker 7: And I'm saying now it's everything's on hold until July.

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Speaker 5: Yeah, we get that vote.

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Speaker 1: Listening to the Bloomberg Intelligence Podcast catch us live weekdays

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Speaker 1: at ten am Eastern on applecar Play and Android Auto

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Speaker 1: with the Bloomberg Business. You can also listen live on

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Speaker 1: Amazon Alexa from our flagship New York station, Just say

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Speaker 1: Alexa play Bloomberg. Eleven thirty.

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Speaker 2: One stock that's doing some stuff is Micron. It got

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Speaker 2: some price targets raised, it's going to report earnings next week,

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Speaker 2: and it is just having an awesome day and an

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Speaker 2: awesome ride. Let's get to take care from Kim Forrest.

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Speaker 2: She is founder in CIO Book of Capital Partners. She

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Speaker 2: joins us, Now, hey, Kim, Micron, what do you think

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Speaker 2: about it?

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Speaker 8: I absolutely love it, but maybe not at an entry

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Speaker 8: point right now. It goes up and it goes down.

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Speaker 8: This is a very volatile stock, but it's certainly one

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Speaker 8: to keep your eye on. And you can ask me

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Speaker 8: why why. I have two letters for you.

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Speaker 2: AI okay, but why like to tell me more? Tell

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Speaker 2: me more?

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Speaker 4: Because of AI? This company makes the device is that

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Speaker 4: build out data center memory? Okay? Or you know where

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Speaker 4: data lives.

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Speaker 8: And if there's one thing I know about AI, it's

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Speaker 8: that it eats data like you wouldn't believe. So if

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Speaker 8: you believe in AI, you should believe in the makers

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Speaker 8: of nand and de ram memory devices.

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Speaker 4: So there you go. That's why I like it, he kim.

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Speaker 6: At a cocktail party, so many comes up to you

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Speaker 6: and says, how do I invest in AI?

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Speaker 7: Where do you steer them?

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Speaker 2: Or you're at the wrong cocktail party? But go ahead?

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Speaker 8: Yes, actually you know I try to go incognito at

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Speaker 8: cocktail parties.

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Speaker 4: But that's okay.

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Speaker 8: Well, I always say invest carefully and I have a

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Speaker 8: reasonable timeline. And I think those are the two things

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Speaker 8: that people right now are probably forgetting by I don't know,

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Speaker 8: making in video go up by thirty percent since the split?

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Speaker 4: Does that seem right to you? I'm thinking no? But whatever.

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Speaker 8: So what you really have to look for is the

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Speaker 8: chain of areas that AI touches. And again, one of

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Speaker 8: them is in Nvidia the tip that drives the models,

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Speaker 8: and that's certainly important, but there's going to be a

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Speaker 8: whole lot more infrastructure around it, and even things like

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Speaker 8: I know this could be a big irol, but Telecom

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Speaker 8: is probably going to have to markedly increase its capacity

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Speaker 8: for wireless consumers because we're going to be consuming a

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Speaker 8: lot more data, storing a lot more data, and these models,

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Speaker 8: as I say, use a ton of data. So anything

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Speaker 8: in that chain is fair game right now for investing

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Speaker 8: in AI.

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Speaker 2: We would never irol you for saying Telecom, but based

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Speaker 2: on the fact that you say, you know Micron can

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Speaker 2: be really volatile, you don't want to buy at these levels.

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Speaker 2: You want to buy on dips. Are you noticing a

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Speaker 2: lack of dips a our dips becoming less frequent at

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Speaker 2: this point?

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Speaker 4: Yes?

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Speaker 8: And I think it's because you know, we're what are

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Speaker 8: we thirty six months into discovering chat or not even

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Speaker 8: that long, eighteen months into discovering chat, GPT, something like that,

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Speaker 8: So people are really still looking for how do I

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Speaker 8: how do I.

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Speaker 4: Invest in that? You can't buy open AI.

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Speaker 8: You can buy in video, but that feels a little stretched,

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Speaker 8: So where else do you look? And I say, and

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Speaker 8: AMD is also fair for this because they're going to

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Speaker 8: not only be a competitor for Nvidia, but also make

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Speaker 8: some of the products that go on an end device.

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Speaker 8: We keep forgetting, like the user has to be able

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Speaker 8: to connect to these models, and that's really important in

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Speaker 8: your search for where the outsized growth may be.

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Speaker 6: So, Kim, what is NetApp and why do you like it?

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Speaker 6: Other than the fact that it's up forty one percent

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Speaker 6: year to date.

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Speaker 8: Well, I mean that's really helpful, right, but all joshing aside,

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Speaker 8: you know, the nerdiest. I mean, it's almost like a

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Speaker 8: math joke, right, like a finance joke.

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Speaker 4: But I digress. No, seriously, it's back to storage, storage

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Speaker 4: of data. Now.

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Speaker 8: Net app makes enterprise storage devices, and I think the

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Speaker 8: enterprise is going to have to store a whole lot

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Speaker 8: more data to be made to make AI work for it.

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Speaker 8: So that's why we really like net app, and just

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Speaker 8: the trends in the world becoming more digitized. Businesses need

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Speaker 8: to have stable, safe and reliable storage appliances and that's

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Speaker 8: what net app provides.

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Speaker 2: Kim, what else do you like aside from the AI trend? Like,

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Speaker 2: if that's a nice trend, you got the momentum, you know,

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Speaker 2: you got to find your levels et cetera. Aside from that,

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Speaker 2: if I wanted to buy stuff.

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Speaker 4: Where would it be, buy stuff in tech or not?

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Speaker 2: No, outside of tech.

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Speaker 8: Outside of tech, well, I'm kind of loving because I

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Speaker 8: like to buy low and sell high. I'm looking at

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Speaker 8: energy and I like Exxon Mobile because it has just

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Speaker 8: bought some land in the Permian base through its recent acquisition,

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Speaker 8: so that's good. And I'm somebody that believes in giving

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Speaker 8: yourself some margin, some room for error.

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Speaker 4: And we might like.

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Speaker 8: Ev cars, but it's unclear that, you know, automobiles and

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Speaker 8: trucks are going to go away immediately, so I think

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Speaker 8: the timeline for energy is much longer. And the big

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Speaker 8: energy companies are also investing heavily in alternative energy as well.

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Speaker 8: So we're going to always need energy. We like our

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Speaker 8: things that use it. Yeah, so I like to invest

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Speaker 8: in that as well.

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Speaker 2: Yeah, And you have the gross yield three point five percent,

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Speaker 2: so you're still getting something there, Kim. I'm wondering, though,

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Speaker 2: in energy, do you feel like you can own more

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Speaker 2: than one stock, because in talking to people on the street,

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Speaker 2: it feels like part of the reason behind all the

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Speaker 2: consolidation that's not fundamental is that portfolio managers just can

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Speaker 2: on a lot of them. So those companies need to

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Speaker 2: make themselves very attractive people like you to be like,

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Speaker 2: I'm gonna pull the trigger on this guy right now.

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Speaker 8: I don't feel like I want to have a huge

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Speaker 8: overweight to it. We run a sector neutral model for

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Speaker 8: our flagship product, and what we do is we have

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Speaker 8: one energy pick because I like concentrated positions, so we

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Speaker 8: enter a position around three percent. And that's why I

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Speaker 8: always try to go for best in class because this

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Speaker 8: is a commodity. You're not going to be able to

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Speaker 8: catch the wave on buying low and selling high because

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Speaker 8: you know oil is doing whatever it's doing. So I

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Speaker 8: just try to go for the very best company with

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Speaker 8: the widest range of products. And that to me is

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Speaker 8: excellent because it takes everything from getting it out of

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Speaker 8: the ground into your truck, into your car. But also

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Speaker 8: they do chemicals as well, so they have a very

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Speaker 8: large product suite that addresses a lot of needs.

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Speaker 4: That's why I like it.

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Speaker 6: Kim, how do you feel about just valuation kind of

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Speaker 6: across the market here? I mean a lot of folks

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Speaker 6: are saying this is the market's rally really hard over

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Speaker 6: the last you know, call it nine twelve months, we've

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Speaker 6: seen good earnings growths, you know, certainly, but has the

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Speaker 6: earnings growth has been good enough to kind of keep

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Speaker 6: pace with where we are?

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Speaker 7: So how do you think about valuation?

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Speaker 4: Well, I think the valuation.

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Speaker 8: You can talk yourself into things being barely or even

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Speaker 8: a little bit below valuation if you believe, and this

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Speaker 8: is a big if the Feed is going to cut rates.

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Speaker 8: And this is the math part of the segment here.

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Speaker 8: Once we have lower rates, we get higher multiples. It's

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Speaker 8: just how it works because we discount those cash flows

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Speaker 8: back at a lower interest rate, not a higher interest rate,

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Speaker 8: and you have to accept higher multiples.

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Speaker 4: And I think that's part of.

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Speaker 8: This game in this market right now is just about

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Speaker 8: every last person, retail investor and institutional investors are all

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Speaker 8: assuming the fed's going to cut sooner rather than later.

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Speaker 2: When the FED cuts, what then looks interesting in a

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Speaker 2: way that it doesn't look now like is that when

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Speaker 2: small caps finally get some action.

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Speaker 4: I hope so.

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Speaker 8: I love small caps, and I think you should be

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Speaker 8: invested in small caps regardless of what the FED is doing.

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Speaker 8: It was awfully hard when the FED was raising rates

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Speaker 8: and being into small caps, but good things happen to small, highly.

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Speaker 4: High quality companies.

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Speaker 8: And what I mean by that is they either grow

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Speaker 8: into big companies because they have what it takes to

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Speaker 8: satisfy customers and grow, or they get bought by larger companies.

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Speaker 8: And both of those things are going to happen when

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Speaker 8: rates decrease. That is, companies being more willing to buy

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Speaker 8: to acquire product life or companies that they want to

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Speaker 8: add to their portfolio, or just growth in general should

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Speaker 8: start going once that rate cut happened. So all good

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Speaker 8: things come from rate cuts, apparently.

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Speaker 6: Kim Farrest, founder and chief investment officer, Capital Partners, located

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Speaker 6: in Pittsburgh. Kim Forest, Founder, chief investment officer there. So, uh,

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Speaker 6: there's another investor loving the AI trade. M And you know,

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Speaker 6: I guess it's not just the chips. You can go

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Speaker 6: software places, whether it's Microsoft or somebody else.

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Speaker 2: You know, some of the sele exactly we seed.

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Speaker 7: Some hardware companies call it out.

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Speaker 2: So the telecom angle that you had, the energy angle, which.

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Speaker 6: We have the energy angle on utilities and in the

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Speaker 6: power trade, it just seems like you can bend this

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Speaker 6: thing any way you like to.

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Speaker 7: Support where you are.

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Speaker 2: And I feel like The theory is that you know,

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Speaker 2: at some point we'll come back down to earth. But

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Speaker 2: then you have Julian and Manual all upgrading. His forecast

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Speaker 2: is six thousand, being like the A I trade. It's

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Speaker 2: just it's it's too sticky. Yep, and that I feel

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Speaker 2: like you're finally seeing that analyst capitulation at the end

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Speaker 2: of the day to the broader market angle.

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Speaker 3: Yep.

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Speaker 6: Absolutely, And we look at the markets today for Lisa

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Speaker 6: Bromwo's listening.

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Speaker 7: Who hates this term punched on the SMP five hundred.

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Speaker 6: Nothing happening near the Dallas AF fifty nine points, nastas

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Speaker 6: off one point.

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Speaker 7: Not a lot of happening out there on the e greyfront,

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Speaker 7: but that's okay.

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Speaker 1: You're listening to the Bloomberg Intelligence Podcast. Catch us live

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Speaker 1: weekdays at ten am Eastern on Focarplay and Android Auto

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Speaker 1: with the Bloomberg Business app. Listen on demand wherever you

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Speaker 1: get your podcasts, or watch us live on YouTube.

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Speaker 7: We're just talking about AI. Let's siguius.

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Speaker 6: Tom Keen would say right to some more AI discussioner

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Speaker 6: Mark Bergan. He is a technology reporter for Bloomberg News,

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Speaker 6: joining us from zoom from London. Which is a technology

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Speaker 6: how we all know. Mark, thanks so much for joining

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Speaker 6: us here Google Ai. What's their strategy?

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Speaker 9: Thanks for having me. I think you know the good

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Speaker 9: way put their their strategy in some ways is they're

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Speaker 9: trying to longer be in their back foot, right. I

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Speaker 9: think that with the past two years, and that our

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Speaker 9: story this morning looks at how Google and deep Mind

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Speaker 9: really set the infrastructure and then the base layer for

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Speaker 9: this sort of AI boom that we've had, and then

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Speaker 9: Chat Gebt kind of took all the glory in some ways,

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Speaker 9: and so in their playing ketchup in you'd say, not

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Speaker 9: necessarily on the technical side, but there's certainly now you know,

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Speaker 9: Chat Schebt and all iterations from the different companies building

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Speaker 9: language models like Anthropic and cohere, they're all sort of

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Speaker 9: threatening Google Search in a way that really hasn't happened

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Speaker 9: in almost two decades. And so their their strategy is

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Speaker 9: I would say defensive at this point.

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Speaker 2: How does it get on the offense? What does it

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Speaker 2: need to do to sort of change that narrative?

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Speaker 9: Yeah, I think you know, the story we looked at

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Speaker 9: today was a lot about this mergers that they've Google

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Speaker 9: put in place a year ago. So they've had out

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Speaker 9: here in London is deep Mind, which can widely consider

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Speaker 9: like the world's leading AI lab and has for the

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Speaker 9: past decade effectively been the best funded university running in

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Speaker 9: the world. They basically been a research lab. They put

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Speaker 9: out some great breakthroughs like alpha Go alpha fold around

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Speaker 9: protein folding, but they're not and it haven't been deeply

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Speaker 9: integrated and connected with kind of Google's commercial and profit center,

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Speaker 9: Google Brain, which was the competing AI lab or that

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Speaker 9: they also had in California that was a little bit

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Speaker 9: more tied to a lot of the popular Google services,

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Speaker 9: and they've been merged that for the past year under

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Speaker 9: Demosacipus here who runs all of Google AI. It's had

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Speaker 9: kind of a bumby road so far, but I think

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Speaker 9: their their plan is to continue to ship things like

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Speaker 9: Gemini their big foundational model, tweak that and start kind

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Speaker 9: of integrating a lot of this research directly into commercial services.

439
00:22:53,119 --> 00:22:56,399
Speaker 6: Mark What does Google say about that chat GPT and

440
00:22:57,119 --> 00:23:01,280
Speaker 6: just as as a fundamental all threat to the core

441
00:23:01,720 --> 00:23:04,280
Speaker 6: Google search business, what do they how do they respond

442
00:23:04,320 --> 00:23:04,480
Speaker 6: to that?

443
00:23:05,440 --> 00:23:05,640
Speaker 3: Yeah?

444
00:23:05,680 --> 00:23:08,320
Speaker 9: I mean, you know, Google publicly is is great about

445
00:23:08,440 --> 00:23:14,119
Speaker 9: never is talking about their rivals by name. I said anyways,

446
00:23:14,119 --> 00:23:15,840
Speaker 9: they say nothing, and I think I think that that's

447
00:23:15,840 --> 00:23:17,480
Speaker 9: something they've talked about for a long time. Is that

448
00:23:17,640 --> 00:23:19,840
Speaker 9: sort of their their token phrase that soon the butcha

449
00:23:20,000 --> 00:23:22,960
Speaker 9: uses that the search is the last kind of biggest

450
00:23:23,000 --> 00:23:26,119
Speaker 9: moonshot for Google. I think they are thinking, and you know,

451
00:23:26,160 --> 00:23:29,200
Speaker 9: they're thinking a lot about what that search interface looks like.

452
00:23:30,280 --> 00:23:32,919
Speaker 9: You know, how they're going to adapt to if consumers

453
00:23:33,040 --> 00:23:36,440
Speaker 9: move to things like chat, GPT and and Gemini, what

454
00:23:36,600 --> 00:23:40,000
Speaker 9: is in what does that mean for Google Search ads business,

455
00:23:40,040 --> 00:23:43,720
Speaker 9: which is still the line's share of its revenue. They've

456
00:23:43,760 --> 00:23:49,000
Speaker 9: had some some clear mishaps, the pretty ugly snaff foosh

457
00:23:49,080 --> 00:23:51,600
Speaker 9: and since the launch of of Gemini this year, right

458
00:23:51,680 --> 00:23:53,359
Speaker 9: like there was that kind of famous incidents where they

459
00:23:53,359 --> 00:23:56,480
Speaker 9: were some of the responses were encouraging people to put

460
00:23:56,560 --> 00:24:00,520
Speaker 9: glue on pizza, right, there were these They described this

461
00:24:00,600 --> 00:24:02,879
Speaker 9: as sort of like this is kind of early stage

462
00:24:02,880 --> 00:24:07,200
Speaker 9: in this technology and some some some stumbles that they've had,

463
00:24:07,280 --> 00:24:10,240
Speaker 9: but you know, they are the world's leaders in search,

464
00:24:10,960 --> 00:24:12,600
Speaker 9: and this is something where you know, they have a

465
00:24:12,680 --> 00:24:15,119
Speaker 9: lot of deep they have a lot of deep responsibility

466
00:24:15,119 --> 00:24:17,399
Speaker 9: to get this right, not just for their business but

467
00:24:17,520 --> 00:24:20,040
Speaker 9: for people's trust in using Google.

468
00:24:20,200 --> 00:24:21,960
Speaker 2: Well, that's what's so difficult, right, It's like all the

469
00:24:22,040 --> 00:24:24,960
Speaker 2: technology is changing so fast, but you still need to

470
00:24:25,080 --> 00:24:27,040
Speaker 2: like do it. So it's it's you're like we're watching

471
00:24:27,040 --> 00:24:29,240
Speaker 2: it in real time. Paul and I were just talking

472
00:24:29,240 --> 00:24:31,520
Speaker 2: about a Washington Post article that was on the weekend

473
00:24:31,600 --> 00:24:34,879
Speaker 2: and talked about how all the AI models cannot answer

474
00:24:35,560 --> 00:24:37,680
Speaker 2: it who won the presidential election in the US in

475
00:24:37,720 --> 00:24:42,000
Speaker 2: twenty twenty, And I'm just wondering, like how these advanced

476
00:24:42,080 --> 00:24:45,879
Speaker 2: technologies solve for problems that they're using these large language models,

477
00:24:45,920 --> 00:24:47,880
Speaker 2: which is basically like, you know, me and Paul talking

478
00:24:47,960 --> 00:24:51,320
Speaker 2: are regular people talking? Does that also mess them up?

479
00:24:53,680 --> 00:24:53,880
Speaker 4: Yeah?

480
00:24:53,920 --> 00:24:55,520
Speaker 9: I think you know this is it reminds me a

481
00:24:55,520 --> 00:24:58,320
Speaker 9: little bit of It's a slightly different technology obviously, but

482
00:24:58,440 --> 00:25:01,800
Speaker 9: you know, they're in twenty sixteen, have this big mess

483
00:25:01,920 --> 00:25:04,160
Speaker 9: where if there was there was a popular or there's

484
00:25:04,200 --> 00:25:06,320
Speaker 9: a blog or this kind of fringe blog that said

485
00:25:06,400 --> 00:25:09,600
Speaker 9: that if I remember this correctly, it's been a long time,

486
00:25:09,680 --> 00:25:13,200
Speaker 9: but it was that that Hillary Clinton won the election

487
00:25:13,320 --> 00:25:15,000
Speaker 9: in twenty sixteen, right, and that was at the top

488
00:25:15,040 --> 00:25:17,600
Speaker 9: of for briefly and momentarily top of Google News results.

489
00:25:17,640 --> 00:25:20,360
Speaker 9: And they've dealt with this sort of problem around misinformation,

490
00:25:20,920 --> 00:25:25,040
Speaker 9: around totally not credible sources being at the top of

491
00:25:25,359 --> 00:25:28,040
Speaker 9: Google Search. You're singing problems that are now dealing with.

492
00:25:28,119 --> 00:25:30,639
Speaker 9: I saw a story today about Google images and like

493
00:25:31,280 --> 00:25:33,560
Speaker 9: consensual porn. I mean, these these problems I think are

494
00:25:33,600 --> 00:25:36,399
Speaker 9: being multiplied because with these tools of that generative a

495
00:25:36,480 --> 00:25:39,200
Speaker 9: I do, which Google talks a lot of as being revolutionary,

496
00:25:39,240 --> 00:25:42,720
Speaker 9: it also just makes content production so much easier. And

497
00:25:42,800 --> 00:25:46,159
Speaker 9: so there's this multitude of content now and and Google

498
00:25:46,359 --> 00:25:49,560
Speaker 9: has been this sort of their primary services to organize this,

499
00:25:50,640 --> 00:25:54,000
Speaker 9: and that has a lot of messy problems, especially when

500
00:25:54,080 --> 00:25:56,600
Speaker 9: open Ai has kind of forced in Microsoft. This forced

501
00:25:56,640 --> 00:25:58,359
Speaker 9: Google is to move a lot faster than they have

502
00:25:58,480 --> 00:26:00,960
Speaker 9: been in years past, and we've seen some clear stumbles

503
00:26:01,000 --> 00:26:01,159
Speaker 9: from that.

504
00:26:01,840 --> 00:26:05,199
Speaker 6: So mark that that does Google feel like they can

505
00:26:05,320 --> 00:26:09,800
Speaker 6: just solve this problem or makeup ground simply by spending more,

506
00:26:09,920 --> 00:26:12,359
Speaker 6: because certainly they have plenty of cash to spend.

507
00:26:13,720 --> 00:26:14,359
Speaker 4: I think that's right.

508
00:26:14,440 --> 00:26:16,760
Speaker 9: I think, you know, I would say that they have

509
00:26:17,000 --> 00:26:18,639
Speaker 9: the capax to be able to do that. I mean,

510
00:26:18,680 --> 00:26:21,440
Speaker 9: so so does Microsoft. I think you know, Google's logic

511
00:26:21,480 --> 00:26:24,879
Speaker 9: here is twofold, right, they have They clearly have a

512
00:26:24,960 --> 00:26:27,080
Speaker 9: lot of engineering talent and and a lot of experience

513
00:26:27,160 --> 00:26:30,240
Speaker 9: on this, right, Like they there I said earlier that

514
00:26:30,320 --> 00:26:33,560
Speaker 9: they have to launch this paper. They wrote this paper

515
00:26:33,800 --> 00:26:40,200
Speaker 9: that launched this entire generative AI boom. They have decades

516
00:26:40,320 --> 00:26:44,840
Speaker 9: of experience of actually like doing cutting a JI and

517
00:26:45,119 --> 00:26:47,800
Speaker 9: and I think they also have proprietary data that a

518
00:26:47,840 --> 00:26:50,359
Speaker 9: lot of companies don't have, right, Like they have not

519
00:26:50,560 --> 00:26:56,000
Speaker 9: just the main services you know, Google, Maps, YouTube, search, Gmail, Right,

520
00:26:56,119 --> 00:26:58,600
Speaker 9: just like that corpus of data they have that's able

521
00:26:58,680 --> 00:27:03,400
Speaker 9: to sort of train AI services. That's something that really

522
00:27:03,480 --> 00:27:05,640
Speaker 9: know other company has. I think the question has always

523
00:27:05,680 --> 00:27:07,960
Speaker 9: been for them, you can they translate that into something

524
00:27:08,080 --> 00:27:10,800
Speaker 9: like for their cloud business right where they're in third place? Now,

525
00:27:11,600 --> 00:27:15,480
Speaker 9: this that actual that data set advantages that translate into

526
00:27:15,960 --> 00:27:19,400
Speaker 9: commercial sales not necessarily clear, but I think that's sort

527
00:27:19,400 --> 00:27:21,480
Speaker 9: of what they always point to, is is we have

528
00:27:21,600 --> 00:27:24,720
Speaker 9: the talent and we have the sort of the big

529
00:27:24,960 --> 00:27:27,760
Speaker 9: this infrastructure in place that's been in there for decades.

530
00:27:27,960 --> 00:27:29,399
Speaker 2: Well, it's a really good piece. You guys should all

531
00:27:29,480 --> 00:27:31,920
Speaker 2: check it out. It was in Bloomberg BusinessWeek today. What

532
00:27:32,200 --> 00:27:33,400
Speaker 2: are you working on next? Now?

533
00:27:35,480 --> 00:27:40,359
Speaker 9: Well it's summer here in Europe, so nothing to say that,

534
00:27:42,160 --> 00:27:44,080
Speaker 9: I'll tell the story for tomorrow. I think there's, you know,

535
00:27:44,160 --> 00:27:47,119
Speaker 9: one thing that was we mentioned briefly in this this story.

536
00:27:47,400 --> 00:27:50,200
Speaker 9: There's I think it's really interesting is a lot of

537
00:27:50,240 --> 00:27:53,119
Speaker 9: applications in AI are moving not just from kind of

538
00:27:53,200 --> 00:27:57,200
Speaker 9: generating images and texts and chatbots, but into the material sciences.

539
00:27:57,800 --> 00:27:59,919
Speaker 9: That's something that the DeepMind is working on a lot.

540
00:28:00,000 --> 00:28:01,320
Speaker 9: I think there's a tension we talk about in the

541
00:28:01,359 --> 00:28:03,960
Speaker 9: story today between you know, whether or not the company

542
00:28:04,000 --> 00:28:07,119
Speaker 9: should be how much time that allocates to working on

543
00:28:07,240 --> 00:28:10,280
Speaker 9: Gemini competing with open AI versus working on something that

544
00:28:10,320 --> 00:28:14,160
Speaker 9: would kind of push the envelope and working to say

545
00:28:14,200 --> 00:28:19,320
Speaker 9: that biology or pharmaceutical industry and Deep mind Googles shifted

546
00:28:19,359 --> 00:28:22,040
Speaker 9: more research towards towards the sort of open AI competition.

547
00:28:22,119 --> 00:28:24,600
Speaker 9: I think that's created this way for a lot of

548
00:28:24,680 --> 00:28:28,200
Speaker 9: new companies moving into biology and chemistry and applying AI

549
00:28:28,320 --> 00:28:30,919
Speaker 9: to the lab. I think that's really interesting.

550
00:28:31,119 --> 00:28:31,320
Speaker 10: Yeah.

551
00:28:31,480 --> 00:28:34,280
Speaker 2: I think we saw that in cancer research too, Like

552
00:28:34,359 --> 00:28:36,480
Speaker 2: you're basically can be copilots. So you still need doctors,

553
00:28:36,520 --> 00:28:38,600
Speaker 2: you still need all the researchers, but they can be copilots.

554
00:28:38,640 --> 00:28:41,560
Speaker 2: And that idea of thinking about that was quite interesting. Hey, Mark,

555
00:28:41,560 --> 00:28:45,880
Speaker 2: really appreciate it. Look forward tomorrow's article as well. Mark Bergan,

556
00:28:46,240 --> 00:28:49,640
Speaker 2: Bloomberg Technology reporter joining us from the UK.

557
00:28:50,720 --> 00:28:51,080
Speaker 4: I don't know.

558
00:28:51,280 --> 00:28:52,040
Speaker 2: I still don't get it.

559
00:28:52,640 --> 00:28:55,640
Speaker 6: I mean, just to ask a person what practical application

560
00:28:55,720 --> 00:28:57,840
Speaker 6: of AI, and I don't get a nice.

561
00:28:57,720 --> 00:29:00,880
Speaker 2: Consistent It's just that's a cool thing about it all

562
00:29:00,920 --> 00:29:02,880
Speaker 2: developing at once, but it doesn't make it easier for

563
00:29:02,880 --> 00:29:04,680
Speaker 2: people like Layman's like us to understand.

564
00:29:05,200 --> 00:29:07,800
Speaker 6: Again, if you just roll back three, four or five

565
00:29:07,880 --> 00:29:10,360
Speaker 6: years ago, I think this was big data. We called

566
00:29:10,360 --> 00:29:13,400
Speaker 6: it big data, and to me, this is just the

567
00:29:13,520 --> 00:29:19,120
Speaker 6: next iteration of making smarter, smarter analysis of all the data,

568
00:29:19,160 --> 00:29:21,760
Speaker 6: structured data and unstructured data. You think the Internet, all

569
00:29:21,800 --> 00:29:25,560
Speaker 6: that unstructured data, chats you know, you know, all those

570
00:29:25,600 --> 00:29:27,600
Speaker 6: types of emails and all that kind of stuff, and

571
00:29:27,760 --> 00:29:29,800
Speaker 6: what is that data? How can you use that data

572
00:29:29,800 --> 00:29:30,600
Speaker 6: to become more efficient?

573
00:29:30,920 --> 00:29:31,280
Speaker 7: I don't know.

574
00:29:31,360 --> 00:29:33,640
Speaker 6: That's a long way of answering. If you can't do

575
00:29:33,720 --> 00:29:35,560
Speaker 6: it in like twenty words or less, you don't understand it.

576
00:29:35,640 --> 00:29:36,520
Speaker 7: Right, I'm in that camp.

577
00:29:39,080 --> 00:29:42,920
Speaker 1: You're listening to the Bloomberg Intelligence podcast. Catch us live

578
00:29:43,040 --> 00:29:46,560
Speaker 1: weekdays at ten am Eastern on Applecard Play and Android

579
00:29:46,600 --> 00:29:49,720
Speaker 1: Auto with the Bloomberg Business. You can also listen live

580
00:29:49,840 --> 00:29:53,000
Speaker 1: on Amazon Alexa from our flagship New York station Just

581
00:29:53,080 --> 00:29:55,600
Speaker 1: Say Alexa playing Bloomberg eleven.

582
00:29:55,400 --> 00:29:59,680
Speaker 2: Thirty AM Alex Deal alongside Paul Sweeney is a Boomberg

583
00:29:59,760 --> 00:30:01,360
Speaker 2: and Tell Just Radio. We bring you all the top

584
00:30:01,440 --> 00:30:03,200
Speaker 2: news and business and finance through our lens of our

585
00:30:03,200 --> 00:30:06,120
Speaker 2: Bloomberg Intelligence analysts. They cover two thousand companies in one

586
00:30:06,240 --> 00:30:09,320
Speaker 2: hundred and thirty industries worldwide. I also get to bring

587
00:30:09,400 --> 00:30:11,360
Speaker 2: in some of my oil CEOs and I get to,

588
00:30:11,800 --> 00:30:14,320
Speaker 2: you know, ale explain to Paul like oil stuff, which

589
00:30:14,320 --> 00:30:16,480
Speaker 2: I always appreciate, and joining us in the studio. I

590
00:30:16,520 --> 00:30:18,520
Speaker 2: have a very special guest for us. It's president and

591
00:30:18,640 --> 00:30:23,280
Speaker 2: CEO of Weatherford Greech Salagram. Weatherford is an oil services company.

592
00:30:23,840 --> 00:30:26,600
Speaker 2: It does international, it does domestic, It does onshore, it

593
00:30:26,680 --> 00:30:29,760
Speaker 2: does offshore. It also has a leg in the energy transition.

594
00:30:30,080 --> 00:30:32,840
Speaker 2: What makes this company unique is that it went bankrupt

595
00:30:32,920 --> 00:30:36,400
Speaker 2: in twenty nineteen. Greiche took over in twenty twenty, and

596
00:30:36,560 --> 00:30:39,120
Speaker 2: the stock has crushed this year. It's up by the

597
00:30:39,200 --> 00:30:41,360
Speaker 2: whole over the last year. It's up ninety percent. It's

598
00:30:41,360 --> 00:30:44,360
Speaker 2: beaten all of its peers, it's beaten the Oil Services Index,

599
00:30:45,000 --> 00:30:47,200
Speaker 2: and even one analyst over at City said that the

600
00:30:47,240 --> 00:30:51,600
Speaker 2: turnaround at Weatherford post pandemic has been nothing short of remarkable.

601
00:30:51,840 --> 00:30:54,040
Speaker 2: And these analysts don't hand out that kind of compliment

602
00:30:54,600 --> 00:30:57,040
Speaker 2: very often. Greece. It's so good to see you. Thank

603
00:30:57,080 --> 00:30:57,840
Speaker 2: you for stopping by.

604
00:30:58,400 --> 00:31:01,120
Speaker 10: Alex, great to see you again, and Paul is great

605
00:31:01,160 --> 00:31:02,520
Speaker 10: to meet you. Thank you so much for having me.

606
00:31:02,960 --> 00:31:03,960
Speaker 2: So how's it going?

607
00:31:04,120 --> 00:31:04,320
Speaker 5: Like what?

608
00:31:04,600 --> 00:31:08,120
Speaker 2: So, it's been quite a four years for you. You

609
00:31:08,200 --> 00:31:10,400
Speaker 2: came in the bankruptcy, Yeah, to turn it around. Where

610
00:31:10,480 --> 00:31:12,680
Speaker 2: are you in this turnaround? What more do you think

611
00:31:12,720 --> 00:31:13,480
Speaker 2: you still have to go?

612
00:31:14,560 --> 00:31:14,760
Speaker 4: Etc?

613
00:31:15,400 --> 00:31:18,200
Speaker 10: No, A great question. Look, it's been a terrific four years.

614
00:31:18,240 --> 00:31:20,920
Speaker 10: The team's done an incredible job. I think very few

615
00:31:20,960 --> 00:31:23,800
Speaker 10: people could have dreamt where it would be today and

616
00:31:24,160 --> 00:31:25,520
Speaker 10: what was possible.

617
00:31:25,880 --> 00:31:26,000
Speaker 3: You know.

618
00:31:26,120 --> 00:31:28,800
Speaker 10: The way I think about it is, the turnaround's mostly done.

619
00:31:28,880 --> 00:31:30,920
Speaker 10: You know, we've gotten the company out of the ditch,

620
00:31:31,000 --> 00:31:35,040
Speaker 10: we have stabilized everything, we've fixed the balance sheet. So

621
00:31:35,400 --> 00:31:38,040
Speaker 10: the journey so far has been from broken to good.

622
00:31:38,520 --> 00:31:40,320
Speaker 10: The next phase of the journey is really the good

623
00:31:40,360 --> 00:31:42,640
Speaker 10: to great journey, and that's what I'm actually very excited

624
00:31:42,640 --> 00:31:44,760
Speaker 10: about because if we've been able to do all of

625
00:31:44,880 --> 00:31:46,800
Speaker 10: the things that we've done over the past four years

626
00:31:47,040 --> 00:31:49,320
Speaker 10: with a lot of constraints, a lot of shackles, you know,

627
00:31:49,960 --> 00:31:52,400
Speaker 10: the exciting part is what we can do without that.

628
00:31:52,920 --> 00:31:55,760
Speaker 2: So when you go from good to great, does that

629
00:31:55,880 --> 00:31:58,480
Speaker 2: mean like a lot of buybacks and dividends?

630
00:31:58,640 --> 00:31:59,200
Speaker 4: Does that mean?

631
00:31:59,280 --> 00:31:59,440
Speaker 3: Yeah?

632
00:31:59,440 --> 00:31:59,800
Speaker 11: What is that?

633
00:32:00,440 --> 00:32:03,040
Speaker 10: Look, it's a lot of different things, but ultimately it

634
00:32:03,200 --> 00:32:06,480
Speaker 10: is creation of value, and it's creational value for our customers,

635
00:32:06,840 --> 00:32:09,520
Speaker 10: for our employees, and most of all for our shareholders.

636
00:32:09,600 --> 00:32:13,240
Speaker 10: But it's doing that with continued focus on greater cash generation,

637
00:32:13,600 --> 00:32:16,440
Speaker 10: which comes from better margins, better improvement in the way

638
00:32:16,520 --> 00:32:21,280
Speaker 10: we manage our networking capital, but also ultimately better investments.

639
00:32:21,400 --> 00:32:23,560
Speaker 10: So our real goal is to make sure that we've

640
00:32:23,640 --> 00:32:26,000
Speaker 10: got world classes that are done on invested capital.

641
00:32:26,960 --> 00:32:30,920
Speaker 6: Now that I see as an outsider to the energy industry,

642
00:32:30,960 --> 00:32:33,000
Speaker 6: I see a lot of M and A activity there,

643
00:32:33,040 --> 00:32:34,840
Speaker 6: and being a former banker myself, that's what hits my

644
00:32:34,960 --> 00:32:38,160
Speaker 6: radar screen. How do you guys think about M and

645
00:32:38,240 --> 00:32:41,000
Speaker 6: A for your business now that you are on maybe

646
00:32:41,080 --> 00:32:42,320
Speaker 6: firmer footing correct?

647
00:32:42,360 --> 00:32:44,800
Speaker 10: You know, for the first three years, MNA was a

648
00:32:44,840 --> 00:32:46,960
Speaker 10: bad word. You know, Weatherford actually grew up on a

649
00:32:47,400 --> 00:32:49,840
Speaker 10: built up on a series of acquisitions and a lot

650
00:32:49,920 --> 00:32:52,360
Speaker 10: of issues with that, especially around the lack of integration.

651
00:32:52,560 --> 00:32:54,600
Speaker 10: So the first three years that I've been in the role,

652
00:32:54,720 --> 00:32:57,680
Speaker 10: we really focused on the organic capabilities of the company,

653
00:32:57,720 --> 00:33:01,480
Speaker 10: building out the portfolio, making sure fix the operating intensity

654
00:33:01,520 --> 00:33:03,520
Speaker 10: and the rigor around the company. But we have now

655
00:33:03,560 --> 00:33:05,720
Speaker 10: gotten to a point where M and A has become

656
00:33:05,840 --> 00:33:09,280
Speaker 10: a very important salient topic. We actually just exercise that

657
00:33:09,400 --> 00:33:12,680
Speaker 10: muscle for the first time. We announced three small acquisitions

658
00:33:13,000 --> 00:33:16,760
Speaker 10: back in February, so two in the wireline technology space,

659
00:33:16,880 --> 00:33:19,920
Speaker 10: one in a very exciting space, and Intervention, which really

660
00:33:19,960 --> 00:33:23,280
Speaker 10: gives us capability in slaughter recovery and plug an abandonment,

661
00:33:23,360 --> 00:33:26,200
Speaker 10: which is a very key part of that energy transition.

662
00:33:26,280 --> 00:33:28,160
Speaker 10: So we have started to do that and I think

663
00:33:28,200 --> 00:33:30,120
Speaker 10: there will be more to come because we've now got

664
00:33:30,160 --> 00:33:31,920
Speaker 10: a balance sheet that allows us to do that, and

665
00:33:32,000 --> 00:33:35,560
Speaker 10: more importantly, a team that understands the importance of integration

666
00:33:35,680 --> 00:33:37,800
Speaker 10: and is learning how to build that into the opening

667
00:33:37,840 --> 00:33:38,680
Speaker 10: cadence of the company.

668
00:33:39,120 --> 00:33:43,120
Speaker 2: And just to give our listeners a sense, your services

669
00:33:43,240 --> 00:33:45,840
Speaker 2: are the life site, like, how do your services differ

670
00:33:46,000 --> 00:33:49,720
Speaker 2: than say, one of your competitors, and how do you

671
00:33:49,800 --> 00:33:53,000
Speaker 2: sort of invest for the life cycle of a welfare customer.

672
00:33:53,240 --> 00:33:55,920
Speaker 10: Sure, so in oil field services, there's a lot of

673
00:33:56,000 --> 00:33:58,680
Speaker 10: companies that do a lot of things similarly. So we've

674
00:33:58,720 --> 00:34:02,600
Speaker 10: got what ferentiates us. We've got a portfolio that provides

675
00:34:02,800 --> 00:34:07,160
Speaker 10: core ofs services, so everything from drilling services to wireline

676
00:34:07,360 --> 00:34:10,040
Speaker 10: et cetera. But we're also able to complement that with

677
00:34:10,200 --> 00:34:13,320
Speaker 10: what we call specialty services, things like managed pressure drilling,

678
00:34:13,719 --> 00:34:17,759
Speaker 10: tubular running services, intervention services, et cetera that very few,

679
00:34:17,880 --> 00:34:22,000
Speaker 10: if anyone, has. So that combination of broad based services

680
00:34:22,040 --> 00:34:23,600
Speaker 10: that allow us to go toe to toe with the

681
00:34:23,680 --> 00:34:26,200
Speaker 10: larger peers in the sector as well as then these

682
00:34:26,239 --> 00:34:30,080
Speaker 10: specialty products and specialty services give us that differentiation and

683
00:34:30,200 --> 00:34:31,840
Speaker 10: also allow us to have higher margins.

684
00:34:32,160 --> 00:34:34,239
Speaker 6: You know, I keep joking to alex with oil at

685
00:34:34,280 --> 00:34:36,239
Speaker 6: eighty dollars a barrel, I'm going to drive down to

686
00:34:36,280 --> 00:34:39,000
Speaker 6: Texas and start drilling some holes. I mean, isn't the

687
00:34:39,120 --> 00:34:41,920
Speaker 6: cost like forty bucks in eighty dollars. I can make

688
00:34:41,960 --> 00:34:43,560
Speaker 6: some money there, but I don't see a whole lot

689
00:34:43,560 --> 00:34:45,440
Speaker 6: of drilling activity. What's going to take it for the

690
00:34:45,520 --> 00:34:47,960
Speaker 6: industry to take advantage of these prices here.

691
00:34:48,040 --> 00:34:51,960
Speaker 10: Look, I think the industry has really really embraced this

692
00:34:52,160 --> 00:34:55,480
Speaker 10: concept of delivering returns for shareholders, and so I think

693
00:34:55,520 --> 00:34:58,759
Speaker 10: there's a lot of discipline, especially around managing capital within

694
00:34:58,840 --> 00:35:01,840
Speaker 10: the industry's it's further exacerbated by the wave of M

695
00:35:01,880 --> 00:35:04,040
Speaker 10: and A that's happening, which again goes back to driving

696
00:35:04,120 --> 00:35:06,919
Speaker 10: higher returns. So I don't think in the US there's

697
00:35:06,920 --> 00:35:10,520
Speaker 10: going to be necessarily a sea change at the range

698
00:35:10,560 --> 00:35:12,399
Speaker 10: of oil prices that we are seeing right now, which

699
00:35:12,640 --> 00:35:14,680
Speaker 10: I think in the long term is actually good for

700
00:35:14,920 --> 00:35:18,840
Speaker 10: our sector, especially it creates a balance versus the seesaw

701
00:35:18,880 --> 00:35:21,200
Speaker 10: effect that you see in the cyclicality that we've seen

702
00:35:21,239 --> 00:35:24,480
Speaker 10: in the past. We also have a very robust international market.

703
00:35:24,560 --> 00:35:27,280
Speaker 10: So for Weatherford, less than twenty percent of our revenues

704
00:35:27,320 --> 00:35:29,719
Speaker 10: come from North America. The bulk of it is really

705
00:35:29,760 --> 00:35:33,839
Speaker 10: an international orientation, international leverage. So we see a very

706
00:35:33,880 --> 00:35:36,200
Speaker 10: healthy market. Now the US is still the largest market

707
00:35:36,239 --> 00:35:38,480
Speaker 10: in the world. We see a lot of activity, but

708
00:35:38,760 --> 00:35:41,400
Speaker 10: it is something that is driven by capital discipline by

709
00:35:41,440 --> 00:35:42,640
Speaker 10: our customers, which is a good thing.

710
00:35:42,760 --> 00:35:44,600
Speaker 2: And we have M and A too. Does that eventually

711
00:35:44,719 --> 00:35:48,080
Speaker 2: lead into less business for oral services companies because in theory,

712
00:35:48,239 --> 00:35:50,960
Speaker 2: maybe an Exxon pioneer going to drill ten wells rather

713
00:35:51,000 --> 00:35:51,359
Speaker 2: than twenty.

714
00:35:51,719 --> 00:35:53,360
Speaker 10: Yeah. I think, look, we are seeing a lot of

715
00:35:53,480 --> 00:35:56,480
Speaker 10: drilling efficiencies, we are seeing the recount go down. But

716
00:35:56,600 --> 00:35:58,799
Speaker 10: I think it all comes down to differentiation. As long

717
00:35:58,840 --> 00:36:02,400
Speaker 10: as companies can differentiate and deliver value to allow our

718
00:36:02,520 --> 00:36:06,200
Speaker 10: customers to make greater headway on their efficiencies to generate

719
00:36:06,320 --> 00:36:08,000
Speaker 10: higher returns, I think they'll always be business.

720
00:36:08,040 --> 00:36:08,239
Speaker 4: Again.

721
00:36:08,320 --> 00:36:09,719
Speaker 10: It is the largest market still.

722
00:36:10,200 --> 00:36:12,680
Speaker 6: I mean I'm looking at your income savent I mean

723
00:36:12,920 --> 00:36:17,560
Speaker 6: roughly half your revenue Eastern Hemisphere, half Western Hemisphere. It

724
00:36:17,640 --> 00:36:20,280
Speaker 6: gives the economics of both of those, your domestic markets

725
00:36:20,360 --> 00:36:21,480
Speaker 6: versus your international Yeah.

726
00:36:21,480 --> 00:36:25,880
Speaker 10: You know, historically North America was a very profitably challenged

727
00:36:25,920 --> 00:36:30,200
Speaker 10: or challenged market for us on a profitability basis. Yeah, right,

728
00:36:30,719 --> 00:36:33,240
Speaker 10: So our team's done a fabulous job over the past

729
00:36:33,680 --> 00:36:36,839
Speaker 10: few years really changing the way we run the North

730
00:36:36,880 --> 00:36:40,560
Speaker 10: America business. So today the profitability across all of our geographies,

731
00:36:40,600 --> 00:36:43,719
Speaker 10: all of our regions is pretty much imbalance. So and

732
00:36:43,800 --> 00:36:45,799
Speaker 10: I think, you know, I've always said the litmus test

733
00:36:45,880 --> 00:36:47,799
Speaker 10: of our turnaround has been what's happened in the North

734
00:36:47,840 --> 00:36:51,560
Speaker 10: America market. Over the past year, we've seen revenues decline

735
00:36:51,600 --> 00:36:54,120
Speaker 10: in North America, but the profitability has actually gone up.

736
00:36:54,480 --> 00:36:57,560
Speaker 10: So that's a real testament to what we've been able

737
00:36:57,600 --> 00:37:00,279
Speaker 10: to do at Weatherford and the opening rigor the opening

738
00:37:00,360 --> 00:37:02,320
Speaker 10: intensity that the team is put in.

739
00:37:02,800 --> 00:37:05,879
Speaker 2: What are you doing on the energy transition space? Where

740
00:37:05,960 --> 00:37:06,680
Speaker 2: do you play in that?

741
00:37:07,160 --> 00:37:09,400
Speaker 10: Yeah? So, first of all, Alex, for US, it starts

742
00:37:09,440 --> 00:37:12,600
Speaker 10: with this whole space of plug in abandonment. We think

743
00:37:12,640 --> 00:37:14,359
Speaker 10: that's going to be what does that actually mean? Yeah,

744
00:37:14,400 --> 00:37:17,800
Speaker 10: so what that is is the responsible decommissioning of mature

745
00:37:17,840 --> 00:37:20,320
Speaker 10: oil and gas well So as oil and gas fields

746
00:37:20,320 --> 00:37:23,440
Speaker 10: stop producing, customers want to make sure that those wells

747
00:37:23,480 --> 00:37:26,200
Speaker 10: are plugged properly so that you don't have any risk

748
00:37:26,280 --> 00:37:29,000
Speaker 10: of leaks from them and you don't have any environmental damage.

749
00:37:29,040 --> 00:37:31,080
Speaker 10: So we play a big role in that, and we've

750
00:37:31,160 --> 00:37:33,920
Speaker 10: both sterted our portfolio with the acquisition that I just

751
00:37:34,000 --> 00:37:37,160
Speaker 10: talked about earlier this year. So that's a huge space

752
00:37:37,239 --> 00:37:39,680
Speaker 10: and we think that'll be something that will play out

753
00:37:39,719 --> 00:37:42,320
Speaker 10: over several years. So you know, that's number one. The

754
00:37:42,400 --> 00:37:45,920
Speaker 10: second element for US is geothermal energy. We've been a

755
00:37:46,000 --> 00:37:50,040
Speaker 10: leader in geothermal for over two decades, mostly driven by

756
00:37:50,320 --> 00:37:54,359
Speaker 10: our capability in high temperature tools. We've had a capability

757
00:37:54,640 --> 00:37:57,920
Speaker 10: leading to very high differentiation in high temperature, which, as

758
00:37:57,960 --> 00:38:00,719
Speaker 10: you can imagine, is important in geothermal. But we're now

759
00:38:00,800 --> 00:38:04,560
Speaker 10: extending that beyond just drilling, so multiple aspects of the

760
00:38:04,640 --> 00:38:09,919
Speaker 10: geothermal loop. We've got partnerships with organizations like Seraphie with Ever,

761
00:38:10,000 --> 00:38:12,279
Speaker 10: which is a Canadian company doing some very novel work

762
00:38:12,320 --> 00:38:15,360
Speaker 10: in geothermal. As geothermal shifts from this whole notion if

763
00:38:15,400 --> 00:38:17,680
Speaker 10: you've got to be somewhere near a volcanic region to

764
00:38:17,760 --> 00:38:20,640
Speaker 10: now in multiple parts of the world, you know, in

765
00:38:20,840 --> 00:38:23,839
Speaker 10: cities as well. I was in Hamburg about a year

766
00:38:23,880 --> 00:38:26,719
Speaker 10: ago where they're brilling wells in the middle of the

767
00:38:26,840 --> 00:38:31,000
Speaker 10: city itself, you know, providing district heating, et cetera. So

768
00:38:31,080 --> 00:38:34,759
Speaker 10: geothermal is a big platform for us. The next one

769
00:38:34,840 --> 00:38:38,040
Speaker 10: is CCUS. Now, CCUS is a huge ecosystem.

770
00:38:37,560 --> 00:38:39,719
Speaker 2: Carbon capture utilizations nice.

771
00:38:39,880 --> 00:38:45,320
Speaker 10: Yeah, it's a huge, huge ecosystem. We don't play in

772
00:38:45,440 --> 00:38:47,600
Speaker 10: a lot of it, but where we do places in

773
00:38:47,640 --> 00:38:50,480
Speaker 10: the storage and monitoring aspect of it. So again this

774
00:38:50,640 --> 00:38:55,120
Speaker 10: is where our technological capabilities lend themselves more directly. So

775
00:38:55,280 --> 00:38:58,360
Speaker 10: that's a huge space for us sort of leading to

776
00:38:58,600 --> 00:39:01,719
Speaker 10: that or away from that, but somewhat tied is whole

777
00:39:01,800 --> 00:39:06,120
Speaker 10: emissions management and emissions monitoring. We recently just announced a

778
00:39:06,640 --> 00:39:09,400
Speaker 10: agreement and MoU that we signed with Honeywell in this

779
00:39:09,560 --> 00:39:13,320
Speaker 10: whole methane emissions management which brings Honeywell state of the

780
00:39:13,480 --> 00:39:18,239
Speaker 10: art technological capability, especially around sensing our access to our

781
00:39:18,360 --> 00:39:21,960
Speaker 10: customers oil fields. We're also the only ofs player to

782
00:39:22,040 --> 00:39:25,200
Speaker 10: have its own SCARA system, a data acquisitions system built

783
00:39:25,239 --> 00:39:28,759
Speaker 10: on top of our production optimization platform. So that's an

784
00:39:28,840 --> 00:39:31,600
Speaker 10: area that I'm very excited about. And last but not least,

785
00:39:31,600 --> 00:39:34,719
Speaker 10: solutions mining, so that's a big area for us.

786
00:39:35,040 --> 00:39:36,920
Speaker 2: Garrise, we really appreciate it. Thank you so much for

787
00:39:37,000 --> 00:39:39,000
Speaker 2: stopping by. It's so good to get your perspective and

788
00:39:39,040 --> 00:39:41,719
Speaker 2: it's good to get started chatting again and all the

789
00:39:41,760 --> 00:39:44,160
Speaker 2: opportunities there and like I said, Wetherford really autperforming all

790
00:39:44,200 --> 00:39:46,960
Speaker 2: of its peers in the last year. Garish Salaground, President

791
00:39:47,040 --> 00:39:49,359
Speaker 2: and CEO of Weatherford International.

792
00:39:51,120 --> 00:39:54,959
Speaker 1: You're listening to the Bloomberg Intelligence Podcast. Catch us live

793
00:39:55,080 --> 00:39:58,600
Speaker 1: weekdays at ten am Eastern on applecar Play and androud

794
00:39:58,640 --> 00:40:01,759
Speaker 1: Outo with the Bloomberg Business. You can also listen live

795
00:40:01,880 --> 00:40:05,040
Speaker 1: on Amazon Alexa from our flagship New York station. Just

796
00:40:05,120 --> 00:40:07,640
Speaker 1: say Alexa play Bloomberg eleven.

797
00:40:07,480 --> 00:40:11,120
Speaker 2: Thirty Alex Deal here with Carl Sweeney. This is Bloomberg

798
00:40:11,120 --> 00:40:13,280
Speaker 2: Intelligence Radio. We bring you all the news and business

799
00:40:13,320 --> 00:40:16,200
Speaker 2: and economics through a lens of our Bloomberg Intelligence analysts.

800
00:40:16,480 --> 00:40:20,200
Speaker 2: We also every Monday at this time tap Bloomberg ne EF.

801
00:40:20,440 --> 00:40:26,879
Speaker 2: Their research covers commodities, power, transport, industry, buildings, AG sectors, technology,

802
00:40:27,440 --> 00:40:29,360
Speaker 2: anything that we need to know as we kind of

803
00:40:29,400 --> 00:40:34,800
Speaker 2: transition our energy and security and energy transition throughout the world.

804
00:40:35,480 --> 00:40:38,240
Speaker 2: And I should point out that every time they release

805
00:40:38,320 --> 00:40:41,520
Speaker 2: their EV Global Outlook, it is the thing that is

806
00:40:41,640 --> 00:40:43,839
Speaker 2: quoted by Wall Street analysts. You go to Wall Street

807
00:40:43,880 --> 00:40:47,520
Speaker 2: Analysts and they are using BNF's data from evs to

808
00:40:48,080 --> 00:40:50,360
Speaker 2: model their own opinion. So we wanted to dig a

809
00:40:50,360 --> 00:40:53,000
Speaker 2: little deeper the release. The report was released last week.

810
00:40:53,440 --> 00:40:57,799
Speaker 2: Corey Kanter is BNF lead US Electric Vehicle analyst. Corey,

811
00:40:57,920 --> 00:41:01,799
Speaker 2: thank you for joining. What was your overall takeaway like, okay,

812
00:41:02,080 --> 00:41:04,800
Speaker 2: EV growth will be x and then what was it

813
00:41:04,880 --> 00:41:05,359
Speaker 2: for the US?

814
00:41:05,880 --> 00:41:07,279
Speaker 5: Yeah? No, thanks for having me, Alex.

815
00:41:07,360 --> 00:41:09,320
Speaker 11: Great to be back here with you and Paul I

816
00:41:09,400 --> 00:41:12,680
Speaker 11: think the big takeaway is that EV sales growth is

817
00:41:12,800 --> 00:41:16,960
Speaker 11: happening on evenly across different regions in the world. Maybe

818
00:41:17,040 --> 00:41:19,120
Speaker 11: not a surprising finding if you're following EV's on a

819
00:41:19,200 --> 00:41:21,360
Speaker 11: day to day basis, but moving forward, we expect that

820
00:41:21,480 --> 00:41:23,520
Speaker 11: to be a bit of the same. To give you

821
00:41:23,600 --> 00:41:26,040
Speaker 11: a sense of where we see things going, we basically

822
00:41:26,120 --> 00:41:27,799
Speaker 11: have both the near term out look and a long

823
00:41:27,880 --> 00:41:30,239
Speaker 11: term out look. The near turnout look ends in twenty

824
00:41:30,320 --> 00:41:34,280
Speaker 11: twenty seven, and so what we expect is by twenty

825
00:41:34,360 --> 00:41:37,400
Speaker 11: twenty seven, global passenger EV sales will be about thirty

826
00:41:37,480 --> 00:41:40,920
Speaker 11: million in our base case called the economic transition scenario,

827
00:41:41,480 --> 00:41:44,000
Speaker 11: and a probably better metric of that is thinking about

828
00:41:44,200 --> 00:41:47,160
Speaker 11: EV share a passenger vehicle sale. So we'll move from

829
00:41:47,200 --> 00:41:49,960
Speaker 11: a world where one in five cars sold is electric

830
00:41:50,040 --> 00:41:51,799
Speaker 11: to a world where one and three is about thirty

831
00:41:51,840 --> 00:41:56,040
Speaker 11: three percent, up from eighteen percent last year. By twenty forty,

832
00:41:56,160 --> 00:41:58,440
Speaker 11: we expect that about seventy three percent of all new

833
00:41:58,480 --> 00:42:01,200
Speaker 11: car sales will be electric. But there's a long way

834
00:42:01,239 --> 00:42:04,040
Speaker 11: to go. And then on the US question, always good

835
00:42:04,040 --> 00:42:06,520
Speaker 11: to compare it. I think to China and Europe, US

836
00:42:06,600 --> 00:42:09,360
Speaker 11: passenger EV's SHAREFF sale last year was around ten percent.

837
00:42:09,840 --> 00:42:11,799
Speaker 11: We expect the next two years to see a bit

838
00:42:11,920 --> 00:42:14,600
Speaker 11: of a slower growth, So only about twelve percent of

839
00:42:14,719 --> 00:42:17,160
Speaker 11: new car sales should be electric this year, rising to

840
00:42:17,239 --> 00:42:20,759
Speaker 11: about twenty nine percent by twenty twenty seven. Seems pretty good,

841
00:42:20,920 --> 00:42:22,680
Speaker 11: but if you look at Europe in China, it's going

842
00:42:22,719 --> 00:42:24,680
Speaker 11: to be much higher there. So by twenty twenty seven

843
00:42:24,760 --> 00:42:27,759
Speaker 11: we expect about sixty percent of new car sales to

844
00:42:27,840 --> 00:42:31,240
Speaker 11: be electric in China and forty one percent in Europe.

845
00:42:31,400 --> 00:42:33,919
Speaker 11: And when we talk about passenger evs at B and EF,

846
00:42:34,200 --> 00:42:36,960
Speaker 11: that's both battery electric and plug in hybrid electric vehicles.

847
00:42:37,200 --> 00:42:40,600
Speaker 6: So plug and talk to us about those plug in hybrids.

848
00:42:40,719 --> 00:42:42,560
Speaker 6: It it feels like a lot of folks are suggesting

849
00:42:43,000 --> 00:42:46,040
Speaker 6: that might be a very vital interim step for at

850
00:42:46,120 --> 00:42:47,120
Speaker 6: least in the US.

851
00:42:47,360 --> 00:42:49,279
Speaker 7: In terms of the transition to EV. Is that how

852
00:42:49,360 --> 00:42:50,040
Speaker 7: you think about it?

853
00:42:50,440 --> 00:42:52,880
Speaker 5: Paul? A really good question. I also co wrote the

854
00:42:53,200 --> 00:42:55,120
Speaker 5: plug and Hybrid section of the report.

855
00:42:55,160 --> 00:42:56,840
Speaker 11: We do a kind of deep dive which we do

856
00:42:56,960 --> 00:42:58,719
Speaker 11: with a few different deep dives every year, and what

857
00:42:58,760 --> 00:42:59,880
Speaker 11: we call thematic highlights.

858
00:43:00,440 --> 00:43:02,560
Speaker 5: I think around p haves the question.

859
00:43:02,480 --> 00:43:04,919
Speaker 7: Really is pheabs Yeah, Phea, plug again?

860
00:43:05,040 --> 00:43:05,400
Speaker 3: Hybrids?

861
00:43:05,480 --> 00:43:08,680
Speaker 5: Okay, plug in hybrids, Okay, is how good are they

862
00:43:08,760 --> 00:43:09,160
Speaker 5: going to be?

863
00:43:09,800 --> 00:43:12,400
Speaker 11: If you look at the plug and hybrids in China,

864
00:43:12,880 --> 00:43:16,080
Speaker 11: they're all electric mode, meaning they're kind of electric mileage

865
00:43:16,080 --> 00:43:17,640
Speaker 11: they get before they have to turn on that gas

866
00:43:17,680 --> 00:43:21,400
Speaker 11: engine is about twice as high in China currently as

867
00:43:21,480 --> 00:43:22,319
Speaker 11: it is in the US.

868
00:43:22,719 --> 00:43:24,720
Speaker 5: So quite simply, China is making not only.

869
00:43:24,640 --> 00:43:28,880
Speaker 11: Better fully electric vehicles, but better plug and hybrids. We

870
00:43:29,040 --> 00:43:31,640
Speaker 11: still think that there is some role for p havebs

871
00:43:31,680 --> 00:43:34,880
Speaker 11: to play this decade in markets like the US in Japan.

872
00:43:35,360 --> 00:43:37,719
Speaker 11: But what I've been big on pushing on is the

873
00:43:37,800 --> 00:43:40,319
Speaker 11: product that we're getting today is not necessarily as good

874
00:43:40,320 --> 00:43:42,879
Speaker 11: as it should be. So when you hear automakers say, oh, well,

875
00:43:42,920 --> 00:43:44,880
Speaker 11: maybe we'll do more hybrids or do more plug and

876
00:43:44,920 --> 00:43:47,560
Speaker 11: hybrids instead of fully electric vehicles, I think a fair

877
00:43:47,640 --> 00:43:50,160
Speaker 11: response would be to say, well, in Europe and China

878
00:43:50,200 --> 00:43:52,640
Speaker 11: they're getting far more all electric mileage than here, so

879
00:43:52,760 --> 00:43:54,160
Speaker 11: can you deliver some of that more.

880
00:43:54,120 --> 00:43:55,120
Speaker 5: High quality product.

881
00:43:55,960 --> 00:43:58,680
Speaker 11: Ultimately, we do a bunch of different scenario analysis in

882
00:43:58,719 --> 00:44:01,800
Speaker 11: the full report, and one downside of plug in hybrids

883
00:44:01,920 --> 00:44:03,720
Speaker 11: is that if you go down that route and people

884
00:44:03,800 --> 00:44:06,840
Speaker 11: aren't charging them enough, which is harder to do. Because

885
00:44:06,880 --> 00:44:09,560
Speaker 11: of the lower all electric range, you could end up

886
00:44:09,600 --> 00:44:11,799
Speaker 11: in a scenario where you're having a lot higher oil

887
00:44:12,200 --> 00:44:15,480
Speaker 11: demand use than if you just switch to fully electric vehicles,

888
00:44:15,480 --> 00:44:17,520
Speaker 11: and that would not be good for your climate targets.

889
00:44:17,760 --> 00:44:19,920
Speaker 2: When do you think the tipping point is when EV's

890
00:44:20,080 --> 00:44:22,839
Speaker 2: become more of mass adoption here in the US.

891
00:44:23,480 --> 00:44:25,840
Speaker 11: So what we've pointed that historically is this idea of

892
00:44:25,960 --> 00:44:29,520
Speaker 11: upfront price parody. We're seeing total cost of ownership parody,

893
00:44:29,600 --> 00:44:33,279
Speaker 11: including fueling already being hit in many different regions in

894
00:44:33,400 --> 00:44:35,640
Speaker 11: terms of upfront costs. It really depends if you're comparing

895
00:44:35,680 --> 00:44:38,200
Speaker 11: apples to apples, right, you see a lot more evs

896
00:44:38,320 --> 00:44:41,319
Speaker 11: in that kind of low forty thousand dollars price range

897
00:44:41,360 --> 00:44:43,440
Speaker 11: now high thirties. I think once you get to the

898
00:44:43,480 --> 00:44:47,400
Speaker 11: low thirty thousand dollars price point, Really, according to our analysis,

899
00:44:47,480 --> 00:44:49,520
Speaker 11: when we're looking at kind of a generic BEV versus

900
00:44:49,560 --> 00:44:51,920
Speaker 11: a generic ice vehicle, we see it happening in the

901
00:44:52,040 --> 00:44:54,279
Speaker 11: US over let's say the next three to four years,

902
00:44:54,680 --> 00:44:57,799
Speaker 11: really twenty twenty six to twenty twenty eight. But really,

903
00:44:57,840 --> 00:45:00,759
Speaker 11: if you're comparing a Tesla model Y to towards a

904
00:45:01,480 --> 00:45:03,640
Speaker 11: lot of its competitor vehicles or model three.

905
00:45:03,719 --> 00:45:04,880
Speaker 5: You're getting pretty close.

906
00:45:05,800 --> 00:45:07,520
Speaker 11: But that's where you start to see I think higher

907
00:45:07,560 --> 00:45:10,000
Speaker 11: adoption where you won't have to necessarily have a premium

908
00:45:10,080 --> 00:45:10,439
Speaker 11: and price.

909
00:45:10,840 --> 00:45:12,600
Speaker 5: You also get a lot of good leasing deals today

910
00:45:12,640 --> 00:45:13,279
Speaker 5: on EV's but.

911
00:45:13,320 --> 00:45:14,920
Speaker 11: It's a bit messier to kind of figure that out

912
00:45:14,920 --> 00:45:17,160
Speaker 11: because you've got dealer markups, you've got different rates.

913
00:45:17,880 --> 00:45:20,200
Speaker 5: But big picture, that upfront price parity.

914
00:45:20,440 --> 00:45:23,240
Speaker 7: How about the charging infrastructure in the United States?

915
00:45:23,320 --> 00:45:25,680
Speaker 6: To what extent is that been holding back the adoption

916
00:45:25,800 --> 00:45:27,720
Speaker 6: of evs here and kind of how do we expect

917
00:45:27,719 --> 00:45:28,280
Speaker 6: that to evolve?

918
00:45:28,560 --> 00:45:31,400
Speaker 11: Yeah, I think that's the biggest difference between Europe and China.

919
00:45:32,160 --> 00:45:35,279
Speaker 11: Our EVY Outlook for folks who aren't familiar has whole

920
00:45:35,320 --> 00:45:38,000
Speaker 11: sections on charging infrastructure, how much investment is going to

921
00:45:38,040 --> 00:45:41,879
Speaker 11: be needed moving forward, But really just taking a base

922
00:45:42,000 --> 00:45:46,479
Speaker 11: level stat TESLA remains the number one provider of charging

923
00:45:46,520 --> 00:45:49,239
Speaker 11: infrastructure here in the US in terms of reliability, in

924
00:45:49,360 --> 00:45:51,920
Speaker 11: terms of number of fast charging stations, and then there

925
00:45:52,000 --> 00:45:54,279
Speaker 11: isn't really a clear cut number two, three, four, five.

926
00:45:55,320 --> 00:45:57,759
Speaker 11: My colleague Ryan Fisher does a bunch of great presentations

927
00:45:57,800 --> 00:45:59,879
Speaker 11: on this, and one of actually the most impressive find

928
00:46:00,160 --> 00:46:03,200
Speaker 11: is US and Europe actually have a similar amount of

929
00:46:03,400 --> 00:46:07,760
Speaker 11: chargers between the top six kind of charging infratructure operators,

930
00:46:07,800 --> 00:46:10,920
Speaker 11: but Europe has an additional five hundred operators after that

931
00:46:11,040 --> 00:46:12,880
Speaker 11: that really supply the bulk of the market.

932
00:46:13,800 --> 00:46:15,759
Speaker 5: So again, we want to see more of that infrastructure

933
00:46:15,760 --> 00:46:16,160
Speaker 5: built out.

934
00:46:16,200 --> 00:46:19,000
Speaker 11: There's been a lot of reporting around the federal funds

935
00:46:19,120 --> 00:46:21,279
Speaker 11: rolling out really slowly because they've had to go through

936
00:46:21,360 --> 00:46:24,680
Speaker 11: state RFPs. But yeah, that's the number one issue holding

937
00:46:24,719 --> 00:46:27,040
Speaker 11: back probably the US market, maybe even moving past the

938
00:46:27,160 --> 00:46:28,120
Speaker 11: upfront cost issue.

939
00:46:28,520 --> 00:46:30,919
Speaker 2: Oh we only about a minute left. But at least

940
00:46:30,960 --> 00:46:33,120
Speaker 2: with my ic car, right, I can trade it in

941
00:46:34,800 --> 00:46:36,520
Speaker 2: and I can get value for it. Do we know

942
00:46:36,680 --> 00:46:38,600
Speaker 2: how this market evolves for evs?

943
00:46:39,400 --> 00:46:39,600
Speaker 5: Yeah?

944
00:46:39,640 --> 00:46:42,239
Speaker 11: I mean I did a residual value note with the

945
00:46:42,320 --> 00:46:45,160
Speaker 11: team at BADF maybe about two years ago, and the

946
00:46:45,239 --> 00:46:47,719
Speaker 11: market looks so different than that's when Tesla prices were

947
00:46:47,760 --> 00:46:51,520
Speaker 11: going ten to fifteen percent above their kind of selling price.

948
00:46:52,760 --> 00:46:55,120
Speaker 11: And so now you've seen because Tesla brought its prices

949
00:46:55,160 --> 00:46:56,359
Speaker 11: down that residuals for a lot.

950
00:46:56,239 --> 00:46:57,120
Speaker 5: Of evs have crashed.

951
00:46:57,120 --> 00:46:58,680
Speaker 11: I think it's going to be something that continues to

952
00:46:58,760 --> 00:47:01,799
Speaker 11: develop to find out how long batteries are going to last.

953
00:47:01,920 --> 00:47:02,799
Speaker 2: I do I know that yet?

954
00:47:03,440 --> 00:47:04,240
Speaker 5: It varies.

955
00:47:04,320 --> 00:47:06,160
Speaker 11: I mean, we don't have I think any research here

956
00:47:06,200 --> 00:47:08,840
Speaker 11: where we've said that this is what we find amongst

957
00:47:08,880 --> 00:47:10,799
Speaker 11: all the kind of evs in the market. But right,

958
00:47:10,840 --> 00:47:13,000
Speaker 11: if your battery holds up longer than people expect, you'd

959
00:47:13,040 --> 00:47:16,040
Speaker 11: expect to see maybe more residual value. If not, you know,

960
00:47:16,120 --> 00:47:18,000
Speaker 11: you could see more of an issue. But yeah, it's

961
00:47:18,000 --> 00:47:20,200
Speaker 11: an outstanding question, like so much of the space. But

962
00:47:20,320 --> 00:47:23,439
Speaker 11: to your point, Alex, that's why you want to see more,

963
00:47:23,760 --> 00:47:25,759
Speaker 11: you know, look into battery life over time.

964
00:47:26,120 --> 00:47:28,440
Speaker 2: Yeah, exactly. I think that's gonna be really interesting. All right, Corey,

965
00:47:28,560 --> 00:47:31,120
Speaker 2: Thanks Lott. We really appreciated Corey kant be enough lead

966
00:47:31,200 --> 00:47:34,719
Speaker 2: you as electric vehicle analysts joining us on their new report.

967
00:47:34,800 --> 00:47:37,040
Speaker 2: Definitely check it out. It's what all the it's what

968
00:47:37,120 --> 00:47:39,040
Speaker 2: all the street winds up quoting as we sort of

969
00:47:39,120 --> 00:47:41,960
Speaker 2: go through this energy transition with the questions that we

970
00:47:42,080 --> 00:47:43,400
Speaker 2: all have. I don't know how long have you had

971
00:47:43,440 --> 00:47:43,840
Speaker 2: your phone?

972
00:47:44,080 --> 00:47:47,239
Speaker 7: I can burying battery life just five years?

973
00:47:47,280 --> 00:47:49,520
Speaker 2: Maybe five years? Okay, so let's just say five years.

974
00:47:50,120 --> 00:47:51,719
Speaker 2: I'm assuming a car battery is gonna be a lot

975
00:47:51,800 --> 00:47:55,520
Speaker 2: better than your phone battery. I don't know, But I

976
00:47:55,560 --> 00:47:57,920
Speaker 2: don't know if you're forced to, like, if you're forced

977
00:47:57,960 --> 00:48:00,040
Speaker 2: to re up your car because of the battery, I

978
00:48:00,120 --> 00:48:01,920
Speaker 2: know that feels different. That feels different than like, Oh,

979
00:48:01,960 --> 00:48:03,680
Speaker 2: I just got to replace my brakes and welco into

980
00:48:03,680 --> 00:48:05,520
Speaker 2: the Apple Store. Maybe I'm wrong, Yeah, exactly.

981
00:48:05,719 --> 00:48:06,040
Speaker 4: All right.

982
00:48:06,120 --> 00:48:09,600
Speaker 2: This is Bloomberg Intelligence. Happy Monday, everybody.

983
00:48:10,000 --> 00:48:14,520
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984
00:48:14,719 --> 00:48:18,360
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985
00:48:18,520 --> 00:48:21,480
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986
00:48:21,600 --> 00:48:25,000
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987
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988
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