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Speaker 1: Bloomberg Audio Studios, podcasts, radio news. Bloomberg Tech is alive

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Speaker 1: from coast to coast with Caroline Hide in New York

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Speaker 1: and Eva Low in San Francisco.

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Speaker 2: This is Bloomberg Tech coming up. Big swings in Korean

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Speaker 2: stocks after a South Korean policy maker suggests paying citizens

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Speaker 2: at dividend using taxes on AI profits.

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Speaker 3: Past The largest US derivatives exchange CME is planning to

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Speaker 3: create a futures market for computing power, one of the

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Speaker 3: key drivers of the AI.

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Speaker 2: Boom, and SAP pushes further into AI agents across business

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Speaker 2: operations with its new Autonomous Enterprise platform.

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Speaker 4: We'll discussed with the CEO.

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Speaker 3: First we check in on these markets, which well, maybe

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Speaker 3: for once we get a shakeout of what has been

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Speaker 3: a relentless grind hire in the tech industry and most

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Speaker 3: notably some of the chip stocks which today are the

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Speaker 3: biggest foolers having been of course the crescendo effect in

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Speaker 3: the NASDAK we're not by one point four percent. It's

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Speaker 3: the biggest drop we've seen since late March ed and

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Speaker 3: all of this is as we still have anxiety about

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Speaker 3: to your politics and that is feeding through to inflationary trashures.

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Speaker 4: More broadly, take a look at this chart.

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Speaker 2: Korean stocks took a dive on Tuesday following a Facebook

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Speaker 2: post by a South Korean policy maker saying the nation

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Speaker 2: should pay citizens a quote dividend using taxes on AI profits.

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Speaker 2: The benchmark hosspy sank as much as five percent, then

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Speaker 2: paired losses when the Korean government later said that was

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Speaker 2: his personal opinion.

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Speaker 4: South Korean shares of.

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Speaker 2: Samsung's and s k heinez recoup some of their losses,

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Speaker 2: but still closed down around five percent. Let's get more

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Speaker 2: with Bloomberg's executive editor for Global Tech, Peter Elstrove. It's

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Speaker 2: the kind of story you wake up, you see at

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Speaker 2: number one on the Bloomberg terminal, and you're not really surprised,

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Speaker 2: but you do a double take and you go a

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Speaker 2: Facebook post that sank an entire market.

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Speaker 4: Who is this policy maker and what do we need

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Speaker 4: to know? Yeah, it is a.

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Speaker 5: Bit of a surprise, and there are surprising dynamics behind

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Speaker 5: this post. So, as you mentioned, this advisor Kim Engbung

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Speaker 5: posted on Facebook about this idea of an AI dividend

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Speaker 5: really a citizen's dividend because of the AI profits. Again,

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Speaker 5: it was posted on Facebook. It's not official policy. The

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Speaker 5: President's office was quick to come out and say that

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Speaker 5: it's his personal opinion. But it's a twenty five hundred

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Speaker 5: word post. It's very in depth. It's actually quite philosophical.

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Speaker 5: He talks about the evolution of the Korean economy, what

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Speaker 5: it means for the people, what it means for citizens,

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Speaker 5: how they're going to be challenges, but they're going to

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Speaker 5: be opportunities too, and then he homes in out in

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Speaker 5: this idea that perhaps there should be a dividend to

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Speaker 5: rebuild the social foundation of the country as they go

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Speaker 5: into this new era. So he's not talking about new

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Speaker 5: taxes on these companies, just to be clear, on the

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Speaker 5: key companies like Samsung and sk Heinix, he's just talking

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Speaker 5: about how the country is going to benefit from their

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Speaker 5: profits and what the country should do with those profits.

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Speaker 5: And the profits are pretty staff just to be clear,

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Speaker 5: Samsung is on track to make something like two hundred

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Speaker 5: and twenty billion dollars this year. Sk Heinix won't be

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Speaker 5: far behind. So you're talking about four hundred billion dollars

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Speaker 5: in profits from just two companies. Of course, it's not

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Speaker 5: as much as you would get in the US, but

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Speaker 5: it's much more concentrated in Korea, so the contribution to

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Speaker 5: the Korean budget is going to be much more substantial.

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Speaker 5: They're going to have this windfall, and so he's talking

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Speaker 5: about what they should do with it.

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Speaker 3: He's clicking in on a hot button topic, whether it

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Speaker 3: be here in the United States, where Open Ai has

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Speaker 3: been essentially suggesting ways in which there could be some

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Speaker 3: sort of wealth fund created to distribute the wealth created

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Speaker 3: by AI more broadly. But also there's potential labor issues,

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Speaker 3: particularly for Samsung.

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Speaker 6: Sk heinis has.

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Speaker 3: Been promising profits towards its engineers and workers, but Samsung

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Speaker 3: is facing a potential strike.

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Speaker 5: Yeah, it's a really important point. This is not just

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Speaker 5: a Korea issue. This is really a global issue. Governments

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Speaker 5: around the world. They're trying to figure out, what are

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Speaker 5: we going to do if there is this big, big

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Speaker 5: AI boom as we've seen so far, what are you

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Speaker 5: going to do with all those profits? What are you

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Speaker 5: going to do with that new wealthy You've had the

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Speaker 5: billionaire's tax proposed of course in California too. Now Samsung

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Speaker 5: and eske Heinix have been wrestling with this issue. As

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Speaker 5: you mentioned, Samsung right now is in negotiations with its

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Speaker 5: labor union, which is threatened to strike because they want

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Speaker 5: to bigger share those profits too. Again, this is not

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Speaker 5: a new tax on these companies though, if they proceed

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Speaker 5: with this dividend. As we've talked about, it's more a

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Speaker 5: sense of what the Korean government can do to prepare.

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Speaker 5: And the big message from Kim in this whole discussion

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Speaker 5: is that his government in Korea and then governments around

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Speaker 5: the world, need to be more proactive and thinking about

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Speaker 5: how they're going to navigate this much more complex world

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Speaker 5: with AI as it begins to change the economy, begins

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Speaker 5: to change the workplace and employment too.

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Speaker 3: Philosophical indeed, blom bags Peter Alstrom, thanks for running us

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Speaker 3: through it. Look Staying in Asia, President Trump is poised

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Speaker 3: to travel to China to meet with President Shijinping later

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Speaker 3: this week now, a number of top tech executives are

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Speaker 3: expected to join the trip.

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Speaker 6: As we told you yesterday, the.

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Speaker 3: Likes of Tim Kok, the likes of tests Evil Musk

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Speaker 3: notably absent in Vidio CEO Jensen Wang, who was reportedly

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Speaker 3: not even invited here with Moris Bloomberg's Chip and AI

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Speaker 3: reporter Maggi Easton say is that the case that the

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Speaker 3: invite wasn't extended to Jensen who seems so close to

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Speaker 3: the president.

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Speaker 7: Yes, exactly, that's what we're reporting here. In Vidia's chief

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Speaker 7: executive officer, the leader of America's most valuable company, did

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Speaker 7: not get the invite to come to China, even though

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Speaker 7: he has a lot at stake in China, and Jiwang

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Speaker 7: is continuing to push for some sort of AI chip

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Speaker 7: sale there, though. This seems to be a signal that

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Speaker 7: he's not going to get Blackwell sales in China anytime soon,

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Speaker 7: at least from the US permission side.

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Speaker 2: It's interesting you're writing about this in your Tech in

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Speaker 2: Depth today right that the President's priorities and Jensen Wang's

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Speaker 2: priorities right now they might not be as aligned as

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Speaker 2: they have been in recent months. Just take us into

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Speaker 2: your Tech in Debt.

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Speaker 7: Absolutely, so, there's really a stark contrast here. If you

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Speaker 7: look at the last time President Trump met with President

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Speaker 7: she in Korea last October, Blackwells were top of mind.

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Speaker 7: You know, President Trump was telling reporters that he was

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Speaker 7: going to talk.

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Speaker 6: To She about those chips.

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Speaker 7: At the same time, in video was lobbying for potentially

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Speaker 7: selling those high powered processors to China. So now we're

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Speaker 7: seeing sort of a reversal in Trump's priorities.

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Speaker 6: The issue of AI chips has.

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Speaker 7: Been deliberated, and it was decided that, you know, the

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Speaker 7: US would allow in Video to sell its H two

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Speaker 7: hundred processor, which is less powerful than the Blackwell. And

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Speaker 7: it seems to be that that's sort of where the

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Speaker 7: line stands, and the latest signal of that is, of

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Speaker 7: course Jensen not joining for this China trip.

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Speaker 3: It's interesting that maybe more on the focus from the

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Speaker 3: Chinese leadership perspective is Taiwan, and there in line is

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Speaker 3: the whole issue of supply chain and a desire to

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Speaker 3: make America stand alone a little bit more in its

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Speaker 3: own ability to fabricate these chips. Margie, who do you

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Speaker 3: think is going to be centered around conversation?

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Speaker 6: And when it comes to.

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Speaker 3: Jensen, is it a big loss because the market is

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Speaker 3: down what eight ten percent on his name today?

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Speaker 7: Well, look, it's certainly not the boost that the idea

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Speaker 7: that AI chips could be on the table and Blackwells

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Speaker 7: could be on the table was last October. I mean

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Speaker 7: that's sent in Video's you know market cap above five

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Speaker 7: trillion dollars. So we're not seeing that same enthusiasm, and

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Speaker 7: even for something like the H two hundreds, it's unclear

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Speaker 7: if in video will ever be able to you know,

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Speaker 7: tally up sales from selling those to China. China could

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Speaker 7: still reject those. You know, it's possible that comes up

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Speaker 7: in this meeting, though the focus is probably going to

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Speaker 7: be bigger geopolitical issues, especially the warn Iran, and so

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Speaker 7: it seems since AI chips are just not a focus

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Speaker 7: in videos, definitely not going to get a boost from

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Speaker 7: this meeting, and you know, they might even see some declines.

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Speaker 6: As you're pointing.

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Speaker 2: Out Lin Beg's Maggie Eastland, thank you very much. The

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Speaker 2: melt up in chip SUNDAYI infrastructure stocks is hitting a

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Speaker 2: pause today. I'm looking at the Philadelphia Semiconductor Index. It's

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Speaker 2: up behind forty percent over the last twelve months through

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Speaker 2: yesterday's close, up seventy percent year to date, but today,

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Speaker 2: in the moment, we're on track for our biggest drop

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Speaker 2: since that last week of March. Is probably worth pointing

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Speaker 2: out as well that CPI inflation accelerating in April, coming

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Speaker 2: in three point eight percent year on year. That has

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Speaker 2: had big impact on the markets of the moment. Let's

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Speaker 2: get more with Kim Forrest, CEO Boca Capital Partners. I

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Speaker 2: was talking with the equities desk this morning at Bloomberg

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Speaker 2: News about a lot of these names that are really

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Speaker 2: lower today, taking a pause, Intel, Micron, Intel particular, they

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Speaker 2: were kind of primed for a bit of a pullback, right.

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Speaker 4: Is that it is that.

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Speaker 2: Just timing in the moment, or is it this CPI

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Speaker 2: print we got this morning.

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Speaker 8: I think the CPI print is completely disregarded by the

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Speaker 8: Chip Nation and AI because they don't care. They just

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Speaker 8: simply don't care what cast things are, or I guess

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Speaker 8: overall they don't care. God knows that. You know, AMD

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Speaker 8: is probably making some gains because they have a somewhat

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Speaker 8: lower price GPU than in Nvidia, and it's capable, so

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Speaker 8: you know, cost is relative. But yes, I don't think

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Speaker 8: CPI has anything to do with today's tech selloff. I

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Speaker 8: think it has more to do with just look at

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Speaker 8: the gains for the year, and sometimes you just run

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Speaker 8: out of buyers, even momentum buyers can't continue. So it's

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Speaker 8: probably that as well as what happened in South Korea. Again,

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Speaker 8: buyers want to buy companies that are going up and

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Speaker 8: perhaps yesterday's sell off of those memory names was enough

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Speaker 8: to cool the temperature of buying chip stocks today.

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Speaker 3: It's interesting to talk about momentum, and we've been hearing

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Speaker 3: from some of the biggest leaders on Wall Street just

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Speaker 3: today about whether AI is real, what the investment opportunities are,

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Speaker 3: who wins, who lose?

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Speaker 6: Just take a listen to Jamie Diamond a little bit earlier.

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Speaker 9: Kim, The way I look at it is that AI

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Speaker 9: is re all. A lot of money's going to go

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Speaker 9: into it. It doesn't mean everyone does it is going

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Speaker 9: to be a winner. Like go back to the Internet.

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Speaker 9: A lot of people lost, a lot of people won.

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Speaker 9: And so you know in the hyper skills those data centers.

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Speaker 4: Not find use.

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Speaker 9: They probably will, But is it possible some do it badly,

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Speaker 9: design it badly, didn't get the right Yes, of course

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Speaker 9: it's possible, Kim.

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Speaker 3: You've that on invested in the right names, some that

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Speaker 3: have done incredibly well through momentum otherwise recently, But are

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Speaker 3: too many ramping higher at this moment?

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Speaker 6: Will we start to see more discernment?

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Speaker 8: I hope so it Actually we've seen some discernment with

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Speaker 8: Intel coming back from you know, it was not only

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Speaker 8: dead and buried, but it had the.

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Speaker 4: Grass grew over.

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Speaker 8: It's great, right, I mean, it was gone, and yet

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Speaker 8: here we are, and why are we here? I think

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Speaker 8: it's the forward movement of AI development. And whenever AI

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Speaker 8: came on the scene and chat GPT captured everyone's imagination

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Speaker 8: both in Nvidia and open AI seemed to be like

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Speaker 8: the winners, and everybody else was just going to languish. Well,

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Speaker 8: technology rollouts don't really work that way. And I think

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Speaker 8: we're probably in I've been watching a lot of baseball

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Speaker 8: because the Pittsburgh Pirates are actually tolerable to watch this

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Speaker 8: year so far, and we're probably in the bottom of

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Speaker 8: the second inning in AIM, so we have a lot

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Speaker 8: of road to go ahead of us.

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Speaker 2: The big calendar item this week probably is President Trump's

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Speaker 2: visit to China meeting with President President g and also

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Speaker 2: the delegation of top CEOs, all relevant to to the

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Speaker 2: fields that you've outlined. What's at stake here for the

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Speaker 2: technology investor and for markets this week.

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Speaker 8: Well, the US and China are walking a really really

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Speaker 8: narrow line between each other. Where AI is considered is

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Speaker 8: you know, the topic for a long time America has

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Speaker 8: been winning. But I think it feels like decades ago

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Speaker 8: whenever Deep Seek came out. Maybe it was the beginning

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Speaker 8: of twenty twenty five. You know, the shiver went through

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Speaker 8: the AI community going, oh my gosh, China might have

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Speaker 8: something here. And while we want competition, it's the military

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Speaker 8: uses of AI and the military uses of the chips

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Speaker 8: that were very cognizant of. And I think that's why,

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Speaker 8: you know, Jensen Wong didn't get the invite. They don't

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Speaker 8: really want to discuss that at this point, so don't

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Speaker 8: invite them, don't have the conversation about it. But yes,

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Speaker 8: AI is very much a contention between the US and China,

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Speaker 8: and I know that the US is you know, US

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Speaker 8: first would like to develop it and sell it to

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Speaker 8: the rest of the world, but so would China. So

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Speaker 8: there's going to be tension over the world of AI.

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Speaker 3: Kim Forest Cio of Boca Capital Partners, it's always great

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Speaker 3: to check in with you. Thanks the expertise. Now coming

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Speaker 3: up the largest US de riveters exchange. That's the CME.

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Speaker 3: It's planning to create a futures market for computing power details.

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Speaker 6: Next, this is Bloomberg Tech.

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Speaker 10: The United States is short power for short compute we're

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Speaker 10: short chipped. Is there going to be shortages at all?

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Speaker 10: Three and memory for things. I actually believe a new

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Speaker 10: acid class will be buying futures of compute. We just

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Speaker 10: don't have enough compute power right now.

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Speaker 3: That was black Rock CEO Larry Fink a week ago

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Speaker 3: at Milken.

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Speaker 6: For telling what is big news out today.

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Speaker 3: CME and Silicon Data are teaming up to create a

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Speaker 3: futures market for computing power, one of the pillars of

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Speaker 3: the AI boom.

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Speaker 6: Bloomberg's finance for portech. Adam Doherty has actually.

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Speaker 3: Been following what's the condage has been doing around this

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Speaker 3: for a while, and now the CME brings it because,

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Speaker 3: according to Terry Duffy at the CME computes the new oil.

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Speaker 11: That's right, it's just another commodity that is going to

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Speaker 11: be able to not just be traded, tracked versus That's

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Speaker 11: really what was the first pillar was the index that

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Speaker 11: was created Silicon Data bringing that too investors so they

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Speaker 11: could at least start to have more transparency around putting

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Speaker 11: a number to what people were valuing as the price

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Speaker 11: of compute technology. And now we have the ability to hedge,

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Speaker 11: to hedge against price moves and some of the risks

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Speaker 11: that are out there, as it would you tracking oil

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Speaker 11: or other commodity prices. This is really bringing this into

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Speaker 11: the institutional space, and you're going to have both the

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Speaker 11: tech firms and investors that are going to jump into

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Speaker 11: this and build the market and grow it so that

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Speaker 11: it has the actual liquidity to back it.

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Speaker 2: Kata and I go even more basic than that. You know,

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Speaker 2: futures contracts an agreement to buy or sell something at

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Speaker 2: a later date at a fixed price, So you're either

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Speaker 2: locking in that cost or you're betting in a price

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Speaker 2: change in either direction. But like with compute, like I

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Speaker 2: think we're talking about GPUs or GPU hours something like that.

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Speaker 2: You know, have they worked out how this would work

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Speaker 2: in the real world, that's.

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Speaker 11: Right, So the index is where you're getting into that

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Speaker 11: detail about GPUs and the processing power. That was kind

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Speaker 11: of the first step. Now with the futures contracts, as

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Speaker 11: you are pointing out, this is the ability to hedge

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Speaker 11: for future moves, putting a price to or really the

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Speaker 11: bet of where these contracts are going to be traded

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Speaker 11: in the future.

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Speaker 6: So it's both looking at.

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Speaker 11: Where is the price of these GPU processing power trading

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Speaker 11: today and where do we see it in a few weeks,

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Speaker 11: months and as it builds out it's really going to be.

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Speaker 11: It has to develop, and I think that it's something

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Speaker 11: that also needs the blessing of regulators. But the intent

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Speaker 11: is to be able to put a price on not

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Speaker 11: just where this power is trading at the very moment,

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Speaker 11: but in the future.

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Speaker 3: Silicon Data commonly who's the founder of all this previously

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Speaker 3: a trader, was her idea to bring transparency to those

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Speaker 3: who were going and trying to buy compute and just

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Speaker 3: understand what one offering was like to another. Or she

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Speaker 3: really thinking that this could become a fully fledged asset

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Speaker 3: class that the retail investors want to get in it,

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Speaker 3: and more broadly, we want to sort of build up

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Speaker 3: an ecosystem.

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Speaker 11: Around I do think it was all about the ecosystem.

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Speaker 11: What Silicon Data and what Carmen was building from the

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Speaker 11: very start was again one pillar to something that was

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Speaker 11: much larger. And when we talk about transparency, before today,

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Speaker 11: there really wasn't a big player like CME that was

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Speaker 11: able to bring compute as an asset class to the

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Speaker 11: market in this way. As a derivatives exchange, they already

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Speaker 11: have the traders and so You might not have just

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Speaker 11: the tech firms and the AI providers, the superscalers that

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Speaker 11: are going to be using this to hedge their own costs,

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Speaker 11: but you're bringing an entire new institutional base that is

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Speaker 11: going to look at this asset class in the same

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Speaker 11: way that they would oil, metals and other things that

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Speaker 11: they trade. So it's going to be kind of a

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Speaker 11: mix of many different worlds that is going to build

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Speaker 11: this ecosystem, this new market.

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Speaker 2: That was my next question really is like put CME

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Speaker 2: in the context of the broader derivatives markets. A next

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Speaker 2: step would be, I guess other players would make similar

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Speaker 2: proposals for futures contracts on computes in other jurisdictions.

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Speaker 11: Yes, you already have seen some exchanges, some upstarts, but

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Speaker 11: no one to the size of CME, which is the

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Speaker 11: largest US derivatives exchange, come into this space. It's very

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Speaker 11: likely that we'll see other large exchange operators will jump

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Speaker 11: into this and build their own marketplace, because it's all

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Speaker 11: about the more liquidity, the more trading, and the more

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Speaker 11: interest that you can build, the better it is for

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Speaker 11: the market as a whole. It doesn't need to be

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Speaker 11: just one exchange.

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Speaker 2: Bloombo's Karen Doherty on a big breaking news story this morning,

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Speaker 2: Thank you very much. Sam Altman is expected to take

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Speaker 2: the stand today in the closely watched trial over the

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Speaker 2: charitable status of open Ai. Elon Musk has accused the

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Speaker 2: startup and his fellow co founders and Microsoft of betraying

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Speaker 2: open AI's founding mission for their own benefit. Yesterday, we

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Speaker 2: learn more about the financial gains during testimony from Microsoft

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Speaker 2: CEO Sati and Nadella and open AI's former chief scientist

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Speaker 2: Ilia Sutzkiva. Bloomberg's Madeline Meckelberg is covering the case and

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Speaker 2: has been there every single day. Let's start with the

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Speaker 2: what's to come, Sam Altman. You know this is the

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Speaker 2: testimony probably that the world's waiting for.

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Speaker 4: What do we know at this stage?

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Speaker 10: That's right.

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Speaker 12: This is definitely the high profile witness that we've been

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Speaker 12: waiting to hear from. We've heard from at this point

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Speaker 12: all of the other major players in this open Ai

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Speaker 12: battle with Elon Musk, that includes Elon Musk, Greg Brockman,

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Speaker 12: Ilias Setskov, Sati, Nadella. As you said, and so we

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Speaker 12: don't know much about Altman. We don't even know what

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Speaker 12: time we're expecting him to take the stand today, but

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Speaker 12: there's just a few days left at trial, and he

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Speaker 12: really has a lot of questions that he's going to

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Speaker 12: have to answer for before the jury. I think we're

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Speaker 12: going to hear him grilled on a lot of the

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Speaker 12: subjects that we've covered already at trial, mainly about his

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Speaker 12: relationship with Elon Musk, but also chiefly about his ouster.

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Speaker 12: That's something that Musk's legal team has been making a

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Speaker 12: really big issue of. This is back in the twenty

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Speaker 12: twenty two twenty twenty three time period, and they're going

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Speaker 12: through a lot of concerns that employees voiced at that time,

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Speaker 12: or members of the board rather voiced at that time

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Speaker 12: about his leadership style. So I think this is going

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Speaker 12: to be an opportunity for him to kind of respond

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Speaker 12: to a lot of the allegations and the description that we've

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Speaker 12: heard so far and tell his side of the story,

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Speaker 12: which is an essential one in this case.

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Speaker 3: And the essential element of the story is well to

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Speaker 3: convince that it wasn't just out of greed that they were.

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Speaker 6: Turning into a for profit business.

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Speaker 3: What is it that through Sam's leadership style that they're

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Speaker 3: looking to prove one way or other.

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Speaker 4: That's right.

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Speaker 12: So that's the central argument from Musk here, is that

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Speaker 12: they've betrayed the founding mission in an effort to try

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Speaker 12: to enrich themselves. That's why we've heard so much about

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Speaker 12: how much stake some of these leaders have in open AI,

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Speaker 12: how much money was being thrown around and made here

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Speaker 12: since they've made this conversion to a for profit. I

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Speaker 12: know your viewers know that the value of open ai

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Speaker 12: has skyrocketed, especially in recent years, and so all these

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Speaker 12: folks who had equity in the very early days of

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Speaker 12: making it a for profit have made significant return since then.

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Speaker 12: Their steak has grown so much. And so I think

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Speaker 12: what we've seen from Musk lawyers is an attempt to

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Speaker 12: show that all men has maybe not been truthful to

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Speaker 12: the board and the past asked, his motives have not

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Speaker 12: always been clear. So while he may be saying one

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Speaker 12: thing about his commitment to the mission, I think they're

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Speaker 12: trying to have the jury ask some questions about whether

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Speaker 12: he's telling the truth there and whether that's really where

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Speaker 12: his motivation is.

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Speaker 3: Megs, Madlin and Macabeg will let you get back to

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Speaker 3: that courtroom.

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Speaker 6: We appreciate you.

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Speaker 3: Checking in on eBay and GameStop shares well. Apparently the

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Speaker 3: fifty six billion dollar takeover offer from GameStop is.

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Speaker 6: Deeply non credible nor attractive.

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Speaker 3: According to eBay itself, ed, we have clearly something that

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Speaker 3: now could become some sort of proxy battle. It could

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Speaker 3: become hostile takeover where Ryan Cohen goes directly to shareholders

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Speaker 3: of eBay. But thus far a company that is worth

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Speaker 3: a quarter of the company it's trying to book bid

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Speaker 3: four hasn't managed to convince the board.

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Speaker 2: Yeah, the offer was one hundred and twenty five dollars

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Speaker 2: a share, fifty percent cash, fifty percent game Stop stock.

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Speaker 2: eBay's at one oh seven, and there were concerns about

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Speaker 2: actually how game Stop would come up with the financing

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Speaker 2: of that offer.

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Speaker 4: What happens next?

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Speaker 3: Yeah, and question of course all about whether or not

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Speaker 3: this can remain an investment grade company if combined, and

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Speaker 3: that seems to be a key issue that our reporting

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Speaker 3: shows that resources showing that that TV offering not enough

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Speaker 3: if it's not investment graded.

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Speaker 2: Not the end of that story. Welcome back to Bloomberg Tech.

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Speaker 2: Generally speaking, we're seeing technology stocks down and quite significantly then,

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Speaker 2: as that one hundred off by almost two percent now,

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Speaker 2: and actually semiconductors and chips are the mainstay of that decline.

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Speaker 2: There's two parts to it. We saw an astonishing rally,

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Speaker 2: in particular in chip stocks that as of yesterday's close

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Speaker 2: we're up seventy percent year to date, so we're taking

441
00:22:44,960 --> 00:22:48,160
Speaker 2: a time out a breather, but the Philadelphia Semiconductor Index

442
00:22:48,240 --> 00:22:50,560
Speaker 2: down almost six percent and on track for its biggest

443
00:22:50,600 --> 00:22:51,879
Speaker 2: drop since the last week of March.

444
00:22:52,080 --> 00:22:53,720
Speaker 4: We did get a pretty hot.

445
00:22:53,480 --> 00:22:56,760
Speaker 2: Inflation print this morning, and our equities desk is saying

446
00:22:57,240 --> 00:22:59,639
Speaker 2: in the Global markets wrap that that's part of it,

447
00:22:59,720 --> 00:23:01,720
Speaker 2: the whole in rally. In the rally we see in

448
00:23:01,760 --> 00:23:06,240
Speaker 2: stocks carry now. Intel is an interesting case study one

449
00:23:06,240 --> 00:23:08,920
Speaker 2: of those taking a breather. It's been driven by reports

450
00:23:08,920 --> 00:23:11,760
Speaker 2: for a potential deal with Apple and a strategic pivot

451
00:23:11,760 --> 00:23:14,320
Speaker 2: into AI. Intel was staging a comeback and in a

452
00:23:14,359 --> 00:23:17,320
Speaker 2: blazing rally, added over four hundred billion dollars in market

453
00:23:17,400 --> 00:23:20,680
Speaker 2: value in just six weeks, but short interest is near

454
00:23:20,720 --> 00:23:24,119
Speaker 2: a fifty two week high, suggesting that for some today

455
00:23:24,200 --> 00:23:27,520
Speaker 2: might be the day to bet against some momentum rhyme.

456
00:23:27,560 --> 00:23:31,399
Speaker 2: Vastellica joins us with for once some good timing on

457
00:23:31,440 --> 00:23:33,520
Speaker 2: the piece you put out this morning. I joke, I joke,

458
00:23:34,600 --> 00:23:37,240
Speaker 2: explain the short interest piece to me. How does that work?

459
00:23:37,280 --> 00:23:38,800
Speaker 2: Why would it drive the stock like this?

460
00:23:39,840 --> 00:23:43,359
Speaker 13: Sure, so, as you mentioned, Intel has seen some really

461
00:23:43,440 --> 00:23:47,160
Speaker 13: tremendous momentum in the Star price over the past few weeks.

462
00:23:47,200 --> 00:23:49,760
Speaker 13: I think it's up more than two hundred percent since

463
00:23:50,000 --> 00:23:53,280
Speaker 13: late March. So that's a very attractive opportunity for a

464
00:23:53,320 --> 00:23:56,560
Speaker 13: lot of short sellers who are expecting that this momentum

465
00:23:56,600 --> 00:23:59,679
Speaker 13: will not only reverse, but reverse in a pretty dramatic fashion.

466
00:23:59,720 --> 00:24:02,280
Speaker 13: Because in addition to how much the stock is moved up,

467
00:24:02,640 --> 00:24:05,719
Speaker 13: the multiple is at an all time high over one

468
00:24:05,760 --> 00:24:09,119
Speaker 13: hundred times estimated earnings. So you have a high valuation

469
00:24:09,280 --> 00:24:12,560
Speaker 13: stock that's already seen some pretty significant games. It's not

470
00:24:12,600 --> 00:24:15,480
Speaker 13: really a surprise that people are betting on a reversal,

471
00:24:15,840 --> 00:24:18,480
Speaker 13: even though a lot of short sellers are saying, when

472
00:24:18,520 --> 00:24:22,119
Speaker 13: you have a company like this with so much positive momentum,

473
00:24:22,320 --> 00:24:26,840
Speaker 13: so much fundamental momentum, it's very difficult to pick a

474
00:24:26,960 --> 00:24:29,560
Speaker 13: top and really write the move down. So a lot

475
00:24:29,560 --> 00:24:32,280
Speaker 13: of confusion here, but certainly some people are betting on

476
00:24:32,320 --> 00:24:33,400
Speaker 13: a reversal.

477
00:24:33,400 --> 00:24:36,479
Speaker 3: And they're looking pretty clever today at least as we're

478
00:24:36,480 --> 00:24:39,240
Speaker 3: currently trading off by more than ten percent. What's interesting, though,

479
00:24:39,320 --> 00:24:42,440
Speaker 3: is that the analyst community still think one should be

480
00:24:42,440 --> 00:24:44,880
Speaker 3: buying the stock. What is it seventeen buys only three cells,

481
00:24:44,880 --> 00:24:45,720
Speaker 3: even though the price.

482
00:24:45,560 --> 00:24:47,479
Speaker 6: Target is a little out of whack who it currently

483
00:24:47,520 --> 00:24:47,800
Speaker 6: is run.

484
00:24:48,800 --> 00:24:50,800
Speaker 13: I would say that consensus is a little bit more

485
00:24:50,880 --> 00:24:53,879
Speaker 13: muted on Intel relative to some other big tech names.

486
00:24:54,440 --> 00:24:57,280
Speaker 13: I think there's far more hold ratings than there are buys.

487
00:24:57,320 --> 00:24:59,720
Speaker 13: But I do think people are warming up to this story.

488
00:25:00,160 --> 00:25:03,359
Speaker 13: A lot of skepticism for years about will they be

489
00:25:03,440 --> 00:25:07,000
Speaker 13: able to get their foundry business back at the top

490
00:25:07,040 --> 00:25:09,159
Speaker 13: of the line the industry standard, and there's been a

491
00:25:09,160 --> 00:25:12,000
Speaker 13: lot of optimism that they are showing some progress on

492
00:25:12,040 --> 00:25:14,919
Speaker 13: This turnaround was a very ambitious move. It's cost them

493
00:25:14,960 --> 00:25:17,280
Speaker 13: a lot of money. There's been a lot of skepticism,

494
00:25:17,320 --> 00:25:20,480
Speaker 13: but lately we are seeing very strong results. We had

495
00:25:20,560 --> 00:25:23,960
Speaker 13: this report about potentially working with Apple on chip making,

496
00:25:24,000 --> 00:25:26,960
Speaker 13: which would be a huge validation for the chip making business.

497
00:25:27,160 --> 00:25:30,160
Speaker 13: So there are some very positive signs here. Like I said,

498
00:25:30,280 --> 00:25:32,720
Speaker 13: the multiple is very high, there's a lot of questions

499
00:25:32,720 --> 00:25:35,119
Speaker 13: out there, and the stock has already seen a pretty

500
00:25:35,119 --> 00:25:36,160
Speaker 13: significant move.

501
00:25:36,400 --> 00:25:38,400
Speaker 3: And that's benefit of the US government for one play

502
00:25:38,440 --> 00:25:40,200
Speaker 3: bags Ron Plastelica, thanks so much.

503
00:25:40,400 --> 00:25:41,400
Speaker 6: Always great reporting.

504
00:25:41,560 --> 00:25:44,040
Speaker 3: Now let's talk about a growing number of bench firms

505
00:25:44,119 --> 00:25:47,360
Speaker 3: who are pumping ever larger sums into leading startups, open

506
00:25:47,400 --> 00:25:48,200
Speaker 3: AI and topic.

507
00:25:48,240 --> 00:25:50,240
Speaker 6: But our next guest is taking a different approach.

508
00:25:50,240 --> 00:25:52,480
Speaker 3: Bennett Segeil is a co founder of a style which

509
00:25:52,520 --> 00:25:56,840
Speaker 3: targets seed stage startups. Checks three five million dollars, it's

510
00:25:56,880 --> 00:25:59,080
Speaker 3: just closed. It's third fund four hundred and fifty million

511
00:25:59,080 --> 00:26:01,960
Speaker 3: dollars in total. That's a large seed round and fund,

512
00:26:02,560 --> 00:26:05,480
Speaker 3: but perhaps small versus multi stage VC fundraises that we've

513
00:26:05,480 --> 00:26:07,359
Speaker 3: seen of late. So Bennett and I'm pleased to welcome

514
00:26:07,440 --> 00:26:11,960
Speaker 3: you here into the New York studio. Seeds rounds have

515
00:26:12,080 --> 00:26:14,280
Speaker 3: become astronomically large in many ways.

516
00:26:14,440 --> 00:26:17,000
Speaker 6: So are you doing what you've always done? Are you

517
00:26:17,040 --> 00:26:18,960
Speaker 6: having to change with the times? How is your VC

518
00:26:19,080 --> 00:26:19,560
Speaker 6: model looking?

519
00:26:19,760 --> 00:26:19,879
Speaker 1: Well?

520
00:26:19,920 --> 00:26:21,920
Speaker 14: First off, thank you for having me. I think we

521
00:26:22,400 --> 00:26:24,280
Speaker 14: right now live in a world of giants, both on

522
00:26:24,359 --> 00:26:26,840
Speaker 14: the venture capital side and the company side, and we've

523
00:26:26,960 --> 00:26:30,320
Speaker 14: really stuck to our craft, which is early stage investing,

524
00:26:30,440 --> 00:26:33,040
Speaker 14: backing founders with an idea of raising a few million

525
00:26:33,080 --> 00:26:35,960
Speaker 14: dollars and looking to build a giant of tomorrow, and

526
00:26:36,080 --> 00:26:38,880
Speaker 14: we wanted a fund size that allowed us to execute

527
00:26:38,920 --> 00:26:40,960
Speaker 14: on this strategy where we could be a close partner

528
00:26:41,000 --> 00:26:44,320
Speaker 14: to these founders. As funds get larger, incentive shift and

529
00:26:44,359 --> 00:26:46,880
Speaker 14: they increasingly put larger amounts of capital on the later

530
00:26:46,960 --> 00:26:49,000
Speaker 14: stage rounds, and you see that with Anthropic and Open

531
00:26:49,080 --> 00:26:53,200
Speaker 14: AI raising many billions of dollars. We tend to start

532
00:26:53,600 --> 00:26:56,600
Speaker 14: more at the ground floor and have crafted our fund

533
00:26:56,640 --> 00:26:59,280
Speaker 14: in our team to be a partner to founders when

534
00:26:59,560 --> 00:27:02,440
Speaker 14: it's not obvious and before the technology is clear, before

535
00:27:02,480 --> 00:27:03,920
Speaker 14: the market opportunity is present.

536
00:27:04,400 --> 00:27:07,399
Speaker 3: But the size of the seed rounds, even when a

537
00:27:07,480 --> 00:27:09,920
Speaker 3: product hasn't developed. I mean, you're thinking, what was it

538
00:27:10,040 --> 00:27:13,440
Speaker 3: reporting around two billion being raised by Thinking Machines Lab.

539
00:27:13,840 --> 00:27:17,720
Speaker 3: You're thinking about safer superintelligence again, a two billion seed round.

540
00:27:18,000 --> 00:27:19,679
Speaker 6: I know Ed's going to come in with the avocados

541
00:27:19,720 --> 00:27:23,040
Speaker 6: and the mangoes, But how do you stick to your knitting? Oh,

542
00:27:23,119 --> 00:27:25,240
Speaker 6: you just you ignore those sorts of coming.

543
00:27:25,240 --> 00:27:27,280
Speaker 14: No, it's a great question. I think there's a bifurcation

544
00:27:27,400 --> 00:27:29,680
Speaker 14: in the market. I think there's traditional seed rounds, which

545
00:27:29,800 --> 00:27:34,000
Speaker 14: increasingly companies started by younger founders, graduates from Harvard MIT Stanford.

546
00:27:34,040 --> 00:27:36,359
Speaker 14: They're raising what we call more traditional seed round of

547
00:27:36,440 --> 00:27:38,880
Speaker 14: between three to five million dollars. In many cases, they're

548
00:27:38,880 --> 00:27:42,120
Speaker 14: building on top of foundational model companies, so they're leveraging

549
00:27:42,680 --> 00:27:46,320
Speaker 14: the technology and the capital invested in open Ianthropic and

550
00:27:46,400 --> 00:27:48,399
Speaker 14: we've backed a number of those companies and they build them.

551
00:27:48,520 --> 00:27:51,360
Speaker 14: What we call the application layer on the flip side

552
00:27:51,440 --> 00:27:53,400
Speaker 14: is exactly the types of rounds you're talking about. It's

553
00:27:53,400 --> 00:27:57,320
Speaker 14: typically researchers that are spinning out of established model companies.

554
00:27:57,359 --> 00:27:59,960
Speaker 14: They're raising in many cases could be hundreds of millions,

555
00:28:00,040 --> 00:28:01,600
Speaker 14: could be billions of dollars out of the gate to

556
00:28:01,680 --> 00:28:04,720
Speaker 14: go and do research and perhaps commercialize the future technology.

557
00:28:05,040 --> 00:28:08,240
Speaker 14: We've largely avoided those rounds. In those rounds have been

558
00:28:08,480 --> 00:28:11,280
Speaker 14: led by companies like Indries and Horrowitz and others. We

559
00:28:11,400 --> 00:28:14,160
Speaker 14: will pick our spots, but many cases founders don't really

560
00:28:14,240 --> 00:28:16,119
Speaker 14: need five hundred million dollars out of the gate, though

561
00:28:16,160 --> 00:28:18,320
Speaker 14: in this capital markets environment, they're able to get it,

562
00:28:18,560 --> 00:28:20,480
Speaker 14: and there are funds that will back them to do so.

563
00:28:21,920 --> 00:28:25,560
Speaker 2: Before co founding a Star, you did four years at

564
00:28:25,600 --> 00:28:30,000
Speaker 2: CO two and I imagine focused on slightly different scale

565
00:28:30,240 --> 00:28:32,520
Speaker 2: and domains, but would you just reflect a little bit

566
00:28:32,560 --> 00:28:35,879
Speaker 2: on the difference in your experience what that was like

567
00:28:35,960 --> 00:28:39,360
Speaker 2: out investing out of CO two versus the seed stage

568
00:28:39,600 --> 00:28:41,960
Speaker 2: at these check sizes and round sizes.

569
00:28:42,520 --> 00:28:44,960
Speaker 14: Yeah, it's a great question. I think incentives do matter,

570
00:28:45,160 --> 00:28:48,800
Speaker 14: and there's a reason that funds increasingly raise larger amounts

571
00:28:48,840 --> 00:28:51,040
Speaker 14: of money over time, and when they raise larger quantuments

572
00:28:51,040 --> 00:28:53,040
Speaker 14: of capital, they tend to invest in the later stages

573
00:28:53,080 --> 00:28:55,840
Speaker 14: and they tend to focus on large dollar deployment. You know,

574
00:28:55,920 --> 00:28:58,320
Speaker 14: CO two is a multi stage fund. They invest venturing

575
00:28:58,360 --> 00:29:00,480
Speaker 14: through public markets. Most of the focus tends to be

576
00:29:00,560 --> 00:29:03,200
Speaker 14: on the growth stages when there's already clear winners and

577
00:29:03,320 --> 00:29:06,240
Speaker 14: you could invest hundreds and millions of dollars in a company.

578
00:29:06,000 --> 00:29:08,200
Speaker 4: And look to earn a multiple on that.

579
00:29:08,440 --> 00:29:10,720
Speaker 14: You know where we play at the seed stage, we're

580
00:29:10,880 --> 00:29:13,440
Speaker 14: investing typically it starts out at a couple of million dollars.

581
00:29:13,480 --> 00:29:16,760
Speaker 14: We're backing on a founder before there's an idea, before

582
00:29:16,760 --> 00:29:19,760
Speaker 14: there's consensus around a market, and we're working with them

583
00:29:19,840 --> 00:29:20,680
Speaker 14: to build their business.

584
00:29:20,960 --> 00:29:22,280
Speaker 4: The beauty of our model is.

585
00:29:22,400 --> 00:29:24,640
Speaker 14: We can actually make venture type returns, and we can

586
00:29:24,720 --> 00:29:26,640
Speaker 14: make one hundred, two hundred and three hundred times our

587
00:29:26,680 --> 00:29:29,040
Speaker 14: money but we have to go and find these, you know,

588
00:29:29,320 --> 00:29:32,080
Speaker 14: incredible opportunities early, and it takes many years for the

589
00:29:32,200 --> 00:29:35,160
Speaker 14: companies to sort of grow and mature. The other aspect

590
00:29:35,200 --> 00:29:37,520
Speaker 14: of our model, which is different from coaches, will continue

591
00:29:37,600 --> 00:29:40,200
Speaker 14: to invest, which we've done in our best companies over time,

592
00:29:40,640 --> 00:29:43,320
Speaker 14: and be one of the largest shareholders in the cap table,

593
00:29:43,360 --> 00:29:46,000
Speaker 14: so be much more concentrated with a handful of companies

594
00:29:46,040 --> 00:29:48,160
Speaker 14: that we hope will go from inception stage to the

595
00:29:48,200 --> 00:29:50,160
Speaker 14: public markets over a decade or longer.

596
00:29:51,040 --> 00:29:54,640
Speaker 2: Well, Caroline was referring to about coconut rounds, avocado rounds,

597
00:29:54,720 --> 00:29:57,000
Speaker 2: mango seed rounds. Is I wrote a column a few

598
00:29:57,040 --> 00:30:00,560
Speaker 2: months ago that it's pointless saying seed because inside cases

599
00:30:01,280 --> 00:30:04,480
Speaker 2: the entry level is so high. But you're committed to

600
00:30:04,560 --> 00:30:08,440
Speaker 2: this two to five million dollar level, you know, that

601
00:30:08,880 --> 00:30:12,040
Speaker 2: would counter that that the seed market is alive and

602
00:30:12,160 --> 00:30:14,120
Speaker 2: well and true to its definition.

603
00:30:14,680 --> 00:30:16,400
Speaker 14: Look, we're going to play the game in the field.

604
00:30:16,480 --> 00:30:19,080
Speaker 14: We've modestly grown fun size. We started out with a

605
00:30:19,120 --> 00:30:21,040
Speaker 14: three hundred million dollar fund. We're now in fun three

606
00:30:21,120 --> 00:30:23,640
Speaker 14: or four hundred and fifty million, So we see inflation

607
00:30:23,960 --> 00:30:26,360
Speaker 14: in round size, and you know, our goals to partner

608
00:30:26,440 --> 00:30:28,760
Speaker 14: with the best founders in Silicon Valley, so we will

609
00:30:28,800 --> 00:30:31,800
Speaker 14: do what we need to do to accomplish that. That said,

610
00:30:32,160 --> 00:30:35,280
Speaker 14: it's still rare for founders to raise one hundred million

611
00:30:35,320 --> 00:30:38,880
Speaker 14: dollars out of the gate with no product or prior

612
00:30:39,000 --> 00:30:42,080
Speaker 14: track record. That is a rare, I would say circumstance

613
00:30:42,120 --> 00:30:45,040
Speaker 14: of particularly researchers coming out of labs what we see

614
00:30:45,120 --> 00:30:48,000
Speaker 14: in other cases. For instance, with a company called Decagon,

615
00:30:48,080 --> 00:30:50,240
Speaker 14: which is one of the leaders in AI customer support.

616
00:30:50,320 --> 00:30:52,760
Speaker 14: It's one of the killer use cases that AI where

617
00:30:52,760 --> 00:30:54,800
Speaker 14: you could replace a lot of folks in the call

618
00:30:54,880 --> 00:30:57,440
Speaker 14: center functions. You know, we co let a seed round

619
00:30:57,440 --> 00:31:00,080
Speaker 14: at a twenty two point five million dollar valuation. In

620
00:31:00,200 --> 00:31:02,360
Speaker 14: less than three years, the company has valued at nearly

621
00:31:02,440 --> 00:31:05,440
Speaker 14: five billion dollars, and we've invested in every single round

622
00:31:05,720 --> 00:31:07,640
Speaker 14: and worked with them to build the business. I think

623
00:31:07,640 --> 00:31:09,920
Speaker 14: there are a number of examples like that where you

624
00:31:10,000 --> 00:31:12,240
Speaker 14: can do a lot with less capital and in fact

625
00:31:12,400 --> 00:31:15,000
Speaker 14: enforces discipline on the teams and the companies.

626
00:31:15,760 --> 00:31:19,040
Speaker 2: Decagoon founded by Jesse Jang and Ashri and Stream of Us.

627
00:31:19,080 --> 00:31:22,360
Speaker 2: I think I've been on this program Bennett's eeg or

628
00:31:22,360 --> 00:31:25,240
Speaker 2: Astar co founder, not enough time, but really interesting look

629
00:31:25,280 --> 00:31:27,440
Speaker 2: at that earlier stage of investing. Thank you very much.

630
00:31:27,880 --> 00:31:31,000
Speaker 2: Now coming up, we're going to speak with SAPCO Christian Klein.

631
00:31:31,440 --> 00:31:36,040
Speaker 2: There's the company debuts, it's autonomous enterprise platform, it's conversations.

632
00:31:36,120 --> 00:31:37,600
Speaker 4: Next, this is Doonberg Tech.

633
00:31:40,880 --> 00:31:44,440
Speaker 2: SAP has unveiled a new autonomous enterprise platform at this

634
00:31:44,560 --> 00:31:49,160
Speaker 2: year's SAP Sapphire Conference, expanding its push into AI agents

635
00:31:49,200 --> 00:31:54,160
Speaker 2: across business operations. Joining us now is SAP CEO Christian Client.

636
00:31:54,440 --> 00:31:57,840
Speaker 2: Let's start by stripping away the jargon. What is an

637
00:31:57,840 --> 00:32:01,160
Speaker 2: autonomous enterprise platform and what is it that your customers

638
00:32:01,200 --> 00:32:04,160
Speaker 2: can now do, Christian that they couldn't do before.

639
00:32:05,240 --> 00:32:07,560
Speaker 4: Yeah, thanks a lot. First of all, ed for having

640
00:32:07,640 --> 00:32:08,520
Speaker 4: me yesterday.

641
00:32:08,680 --> 00:32:12,160
Speaker 15: We launch the Autonomous Enterprise and we have record attendency

642
00:32:12,200 --> 00:32:15,680
Speaker 15: at Sapphire and I see only thousands of customers very

643
00:32:15,760 --> 00:32:19,600
Speaker 15: excited about the Autonomous Enterprise because we showed our customers

644
00:32:19,640 --> 00:32:22,760
Speaker 15: today that while the large language models are getting better

645
00:32:22,800 --> 00:32:26,000
Speaker 15: and better, they don't know anything about your business data

646
00:32:26,080 --> 00:32:29,160
Speaker 15: and your business processes. And as part of the autonomous

647
00:32:29,240 --> 00:32:32,040
Speaker 15: Enterprise is our new AI platform. And here we are

648
00:32:32,080 --> 00:32:35,120
Speaker 15: infusing the brain of every company, which is the EERP,

649
00:32:35,760 --> 00:32:38,800
Speaker 15: into the platform, so that the agents also not only

650
00:32:38,920 --> 00:32:41,400
Speaker 15: have the large language models, but also that they have

651
00:32:41,600 --> 00:32:44,640
Speaker 15: the context of how a company wants. And then on

652
00:32:44,760 --> 00:32:47,520
Speaker 15: top we had customers like eight and AM, JP Mong

653
00:32:47,640 --> 00:32:50,360
Speaker 15: Chase who have brewn that you know, with these agents

654
00:32:50,440 --> 00:32:54,560
Speaker 15: you can really deliver accurate, compland and reliable results.

655
00:32:54,840 --> 00:32:57,920
Speaker 6: Christian, how are you showing that productivity?

656
00:32:58,280 --> 00:33:00,880
Speaker 3: What sort of data, what sort of statistics you're able

657
00:33:00,960 --> 00:33:01,800
Speaker 3: to show your clients?

658
00:33:02,680 --> 00:33:05,640
Speaker 15: Actually we shottle together with JP Mong Chase that they

659
00:33:05,720 --> 00:33:08,080
Speaker 15: can close the books faster now by thirty percent.

660
00:33:08,360 --> 00:33:11,120
Speaker 4: We have shown with H and M that the turno.

661
00:33:11,560 --> 00:33:14,440
Speaker 15: In their commerce shop is now better because of our

662
00:33:14,520 --> 00:33:18,120
Speaker 15: personalized agent. We have shown that inventory god reduced by

663
00:33:18,200 --> 00:33:21,560
Speaker 15: ten percent because actually our agents work with each other

664
00:33:21,920 --> 00:33:25,400
Speaker 15: and the demand agent actually signaled the inventory agent, hey,

665
00:33:25,600 --> 00:33:29,280
Speaker 15: how to optimize and to how to optimize procurement. So

666
00:33:29,400 --> 00:33:32,320
Speaker 15: we really could also connect the story very well from

667
00:33:32,360 --> 00:33:35,440
Speaker 15: the front office into the fulfillment functions, which is the

668
00:33:35,520 --> 00:33:36,400
Speaker 15: power of SAP.

669
00:33:38,320 --> 00:33:42,160
Speaker 2: Very recently spoke to AWS CEO Matt Garman, an AWS

670
00:33:42,440 --> 00:33:45,920
Speaker 2: partner of SAPs, but they are also moving into this

671
00:33:46,080 --> 00:33:50,080
Speaker 2: exact domain. How much pressure you feel, in Christian to

672
00:33:50,240 --> 00:33:55,720
Speaker 2: offer this sort of encompassing agentic platform because if you don't,

673
00:33:55,840 --> 00:33:56,640
Speaker 2: someone else will.

674
00:33:57,640 --> 00:33:58,200
Speaker 4: Yeah, for sure.

675
00:33:58,280 --> 00:34:01,360
Speaker 15: But look, take AWS actually a great partner. I mean,

676
00:34:01,600 --> 00:34:04,440
Speaker 15: Matta and I talk regularly, and because you know, as

677
00:34:04,480 --> 00:34:06,960
Speaker 15: a matter of fact, not all data of the world

678
00:34:07,040 --> 00:34:09,880
Speaker 15: sits in SEP systems. And with AWS, we are now

679
00:34:09,960 --> 00:34:12,680
Speaker 15: partnering to also build a harmony data layer because of

680
00:34:12,760 --> 00:34:16,480
Speaker 15: course still agents they can't compensate for problem data modules.

681
00:34:16,640 --> 00:34:19,840
Speaker 15: And as part of our new SEP business aiplatform, we

682
00:34:19,960 --> 00:34:23,600
Speaker 15: also now harmonized data SAP non SEP data, and then

683
00:34:23,640 --> 00:34:26,759
Speaker 15: we've infused it into the agents, so we see AWS

684
00:34:27,000 --> 00:34:29,759
Speaker 15: Microsoft we had in Vitair. Here on stage we have

685
00:34:29,920 --> 00:34:33,000
Speaker 15: data break Snowflakes. They are all now joining our platform

686
00:34:33,120 --> 00:34:35,920
Speaker 15: to harmonize business data and these are the partnerships we

687
00:34:36,040 --> 00:34:38,200
Speaker 15: need to deliver highly ecoate AI.

688
00:34:39,080 --> 00:34:41,719
Speaker 3: Is it the accuracy that you think wins people over

689
00:34:41,800 --> 00:34:44,560
Speaker 3: from worrying that you're going to lose out competition? That's

690
00:34:44,560 --> 00:34:47,240
Speaker 3: the heart of where it's going, Like everyone's a frenemi,

691
00:34:47,400 --> 00:34:49,760
Speaker 3: but also the labs serious competition.

692
00:34:49,880 --> 00:34:51,560
Speaker 6: How do you fend off the software anxiety?

693
00:34:52,680 --> 00:34:53,560
Speaker 4: Caroline Exactly.

694
00:34:53,760 --> 00:34:55,799
Speaker 15: I guess the heart of the new platform is clearly

695
00:34:55,880 --> 00:34:58,680
Speaker 15: our contact layer, because the brain of every company is

696
00:34:58,760 --> 00:35:01,000
Speaker 15: the EERP. I mean, we have over seven point five

697
00:35:01,040 --> 00:35:04,120
Speaker 15: million data fields in there, we have thousands of business processes,

698
00:35:04,360 --> 00:35:07,360
Speaker 15: and that knowledge sits in our platform. And this is

699
00:35:07,440 --> 00:35:10,399
Speaker 15: clearly how the platform also can differentiate. You can use

700
00:35:10,480 --> 00:35:13,879
Speaker 15: any commodity LLM you want. People can bring their own

701
00:35:13,960 --> 00:35:16,440
Speaker 15: modules what they would like to use. But then on

702
00:35:16,560 --> 00:35:20,399
Speaker 15: the blootform, these agents immediately get the context what only

703
00:35:20,600 --> 00:35:23,319
Speaker 15: SEP has and that's our why to win, and that's

704
00:35:23,320 --> 00:35:24,759
Speaker 15: how SEP will differentiate.

705
00:35:26,440 --> 00:35:30,440
Speaker 2: Christian in Nvidia CEO Jens Munk's formula or equation is

706
00:35:30,560 --> 00:35:35,560
Speaker 2: very simple. More compute, more tokens, more revenues. Do you

707
00:35:35,600 --> 00:35:38,080
Speaker 2: have any case studies with customers where you can say

708
00:35:38,400 --> 00:35:42,000
Speaker 2: there's actual real revenues through the agentic work they've done

709
00:35:42,040 --> 00:35:42,560
Speaker 2: with SAP.

710
00:35:43,719 --> 00:35:43,919
Speaker 4: Yeah.

711
00:35:43,960 --> 00:35:46,200
Speaker 15: I had Chensen actually with me on the keynote today

712
00:35:46,239 --> 00:35:48,880
Speaker 15: and he clearly said he, of course, which is our

713
00:35:49,000 --> 00:35:51,120
Speaker 15: best luck first of all as a customer to SVP,

714
00:35:51,440 --> 00:35:54,440
Speaker 15: but the second obviously in order to get higher consumption

715
00:35:54,600 --> 00:35:57,600
Speaker 15: of compute and chips. I mean, you need consumption at

716
00:35:57,640 --> 00:36:00,719
Speaker 15: the top where the real value creation happens. And that's

717
00:36:00,760 --> 00:36:03,919
Speaker 15: why when we actually now can build an autonomous supply

718
00:36:04,040 --> 00:36:06,400
Speaker 15: chain for in Vitia. I mean they see this immediately

719
00:36:06,480 --> 00:36:08,799
Speaker 15: also in the hardware consumption. And this is where also

720
00:36:08,880 --> 00:36:11,759
Speaker 15: in Vita and SAP are partnering up to build the

721
00:36:11,800 --> 00:36:12,920
Speaker 15: autonomous enterprise.

722
00:36:13,440 --> 00:36:17,320
Speaker 3: Christian Klein of SAP Sapphire event, we very much appreciate

723
00:36:17,360 --> 00:36:18,200
Speaker 3: you joining from Florida.

724
00:36:18,280 --> 00:36:18,560
Speaker 6: Thank you.

725
00:36:24,560 --> 00:36:26,600
Speaker 3: Ford, and it's set to open a nearly three billion

726
00:36:26,640 --> 00:36:30,520
Speaker 3: dollar battery plant in Marshall, Michigan, bringing new manufacturing jobs.

727
00:36:30,320 --> 00:36:31,560
Speaker 6: An investment to the United States.

728
00:36:31,719 --> 00:36:35,480
Speaker 3: The facility will use technology though license from China's COATL

729
00:36:35,719 --> 00:36:39,400
Speaker 3: supplying LITHIUMAH and phosphate battery chemistry, an arrangement drawing some

730
00:36:39,520 --> 00:36:42,239
Speaker 3: scrutiny amid the US China attentions. This comes across as

731
00:36:42,280 --> 00:36:44,320
Speaker 3: President Trump heads to China this week for talks of

732
00:36:44,360 --> 00:36:46,640
Speaker 3: President using ping so joining us. We've got a roundtable

733
00:36:46,920 --> 00:36:49,759
Speaker 3: Niberg's Auto Report at Keith Norton and Senior Tech editor

734
00:36:49,840 --> 00:36:52,840
Speaker 3: Mike Shephard And Keith, I start with you, because what

735
00:36:53,040 --> 00:36:56,040
Speaker 3: is the relationship like between Ford and CAATL. Has it

736
00:36:56,120 --> 00:36:59,600
Speaker 3: been rosy throughout the ability to build out this manufacturing site.

737
00:37:00,600 --> 00:37:00,759
Speaker 10: Yeah.

738
00:37:00,880 --> 00:37:05,200
Speaker 16: CTL is in Marshall, Michigan right now, training workers, helping

739
00:37:05,400 --> 00:37:07,920
Speaker 16: get this plant off the ground. It's due to open

740
00:37:08,520 --> 00:37:12,080
Speaker 16: this year. Ford takes great pains to say it's fully

741
00:37:12,200 --> 00:37:14,720
Speaker 16: owned by Ford and the workers are employed by Ford.

742
00:37:15,120 --> 00:37:17,040
Speaker 16: It is just a licensing deal. But they've had a

743
00:37:17,080 --> 00:37:22,000
Speaker 16: good relationship to develop these lower cost LFP batteries that

744
00:37:22,080 --> 00:37:27,080
Speaker 16: are central to Ford's efforts to overhaul its EV strategy

745
00:37:27,360 --> 00:37:31,920
Speaker 16: and deploy more affordable evs in twenty twenty seven.

746
00:37:32,480 --> 00:37:37,040
Speaker 3: But Mike this relationship, though Rosie hasn't been particularly well

747
00:37:37,080 --> 00:37:40,320
Speaker 3: loved by some people in Michigan. But even and the

748
00:37:40,360 --> 00:37:43,239
Speaker 3: wholes of Congress, right, how has this been sitting The

749
00:37:43,400 --> 00:37:46,240
Speaker 3: sharing of technology between China and US giants?

750
00:37:47,600 --> 00:37:50,200
Speaker 17: Well, in general, there has been a lot of reluctance

751
00:37:50,360 --> 00:37:53,560
Speaker 17: to allow this kind of a partnership. Anything that remotely

752
00:37:53,719 --> 00:37:58,680
Speaker 17: touches on advanced technology immediately draws concerns from wawmakers here

753
00:37:59,200 --> 00:38:03,560
Speaker 17: in Washington who really fear the leakage of technology to China,

754
00:38:03,680 --> 00:38:08,000
Speaker 17: but also the potential leakage of data and other information

755
00:38:08,239 --> 00:38:11,960
Speaker 17: that could jeopardize US national security. And we have seen that,

756
00:38:12,080 --> 00:38:15,200
Speaker 17: of course in the battle over TikTok, and then more

757
00:38:15,280 --> 00:38:19,040
Speaker 17: recently we have seen this in terms of legislation at

758
00:38:19,080 --> 00:38:21,880
Speaker 17: the State level, and even introduced here at the national

759
00:38:22,000 --> 00:38:25,960
Speaker 17: level this week in Washington aimed at restricting Chinese purchases

760
00:38:26,160 --> 00:38:30,480
Speaker 17: of land and also investments in businesses here for those

761
00:38:30,640 --> 00:38:33,680
Speaker 17: verious security reasons. And it's important to know, Caro, that

762
00:38:33,880 --> 00:38:38,000
Speaker 17: COTL itself is the focus of some of those concerns.

763
00:38:38,160 --> 00:38:40,719
Speaker 17: The company in twenty twenty five was added to this

764
00:38:40,920 --> 00:38:45,240
Speaker 17: Pentagon list of companies that the US government believes support

765
00:38:45,360 --> 00:38:46,720
Speaker 17: China's military.

766
00:38:47,360 --> 00:38:50,279
Speaker 2: Keith, do you not have a great sense of deja vu?

767
00:38:50,880 --> 00:38:53,879
Speaker 2: Didn't you and I write about a COATL licensing deal

768
00:38:53,920 --> 00:38:57,560
Speaker 2: in twenty twenty three that Sections as a Republican Party

769
00:38:57,760 --> 00:38:59,280
Speaker 2: then said was a trojan horse.

770
00:39:00,000 --> 00:39:00,320
Speaker 4: Different.

771
00:39:01,280 --> 00:39:04,799
Speaker 16: Yeah, So there continues to be these concerns, as Mike

772
00:39:04,840 --> 00:39:08,839
Speaker 16: is saying about ties to the Chinese Commingist Party with CTL.

773
00:39:09,160 --> 00:39:13,399
Speaker 16: But here's the reality, Ed, you cannot pursue an EV

774
00:39:13,600 --> 00:39:17,759
Speaker 16: strategy without dealing with the Chinese. The Chinese control eighty

775
00:39:17,800 --> 00:39:21,360
Speaker 16: percent of the world's capacity for batteries, and that is

776
00:39:21,440 --> 00:39:25,440
Speaker 16: the most costly component of an electric vehicle. CATL has

777
00:39:25,560 --> 00:39:28,880
Speaker 16: half of that, So they're the battery giant that you

778
00:39:29,040 --> 00:39:31,680
Speaker 16: must deal with if you want to have an electric

779
00:39:31,760 --> 00:39:32,600
Speaker 16: vehicle strategy.

780
00:39:33,800 --> 00:39:36,920
Speaker 2: What that story at the time showed shep and became

781
00:39:37,080 --> 00:39:40,279
Speaker 2: true in the first few months of this administration was

782
00:39:40,360 --> 00:39:44,200
Speaker 2: there is a scale of China hawkishness right ranging from

783
00:39:44,560 --> 00:39:48,319
Speaker 2: we need complete access and work with China to let's

784
00:39:48,360 --> 00:39:50,520
Speaker 2: not do any business with China. And when the President

785
00:39:50,640 --> 00:39:53,839
Speaker 2: goes with that entourage with CEOs in the next twenty

786
00:39:53,880 --> 00:39:57,719
Speaker 2: four hours, that spectrum of hawkishness will also be a

787
00:39:57,800 --> 00:39:59,240
Speaker 2: part of the political story.

788
00:40:00,680 --> 00:40:03,600
Speaker 17: Well, it certainly will ed. We will see that follow

789
00:40:03,760 --> 00:40:07,360
Speaker 17: the delegation with the President. And these are the concerns

790
00:40:07,440 --> 00:40:11,040
Speaker 17: that's around the ability of China, for example, to purchase

791
00:40:11,719 --> 00:40:15,239
Speaker 17: advanced AI chips from Nvidia, and a notable absence of

792
00:40:15,360 --> 00:40:18,960
Speaker 17: courses noted early on the program is Nvidia's Jensen Wang

793
00:40:19,560 --> 00:40:23,799
Speaker 17: and also the Iran conflict itself will barge into these

794
00:40:23,880 --> 00:40:28,200
Speaker 17: talks and really perhaps restrain the ability of unfettered deal

795
00:40:28,280 --> 00:40:30,800
Speaker 17: making by some of these companies. They'll be looking for

796
00:40:31,400 --> 00:40:35,399
Speaker 17: smaller wins, perhaps in the Chinese market, and then we'll

797
00:40:35,480 --> 00:40:38,080
Speaker 17: come up the question, of course, of what can China

798
00:40:38,160 --> 00:40:40,560
Speaker 17: do for the US, which is what Donald Trump has

799
00:40:40,640 --> 00:40:44,320
Speaker 17: tried with other trading partners like Japan, South Korea, the

800
00:40:44,440 --> 00:40:48,439
Speaker 17: European Union, encouraging them to invest here in the US

801
00:40:48,480 --> 00:40:51,880
Speaker 17: as part of trade negotiations. The challenge is though reaching

802
00:40:51,960 --> 00:40:54,480
Speaker 17: some sort of a grand bargain with the US would

803
00:40:54,560 --> 00:40:58,600
Speaker 17: require much more complex talks on issues ranging from tariffs

804
00:40:58,880 --> 00:41:02,680
Speaker 17: to market access China, and then also the even more

805
00:41:02,760 --> 00:41:07,240
Speaker 17: sensitive question of rare earths and whether China would relax

806
00:41:07,520 --> 00:41:10,840
Speaker 17: its position in terms of handling the choke point that

807
00:41:10,960 --> 00:41:15,040
Speaker 17: it holds, the chokehold that it holds over those elements

808
00:41:15,080 --> 00:41:19,000
Speaker 17: that are critical to manufacturing in so many areas, including autos,

809
00:41:19,080 --> 00:41:20,479
Speaker 17: but across the economy, I mean.

810
00:41:20,400 --> 00:41:22,520
Speaker 3: Where US is where it's that when it comes to

811
00:41:22,640 --> 00:41:25,600
Speaker 3: battery technology. Keith and I go back in many ways

812
00:41:25,640 --> 00:41:28,440
Speaker 3: to market access, because with one breath you'll hear the

813
00:41:28,520 --> 00:41:32,600
Speaker 3: Ford CEO working on this relationship with the atl and

814
00:41:32,640 --> 00:41:34,480
Speaker 3: then the second best saying, but we don't want Chinese

815
00:41:34,520 --> 00:41:36,759
Speaker 3: main cars or auto's coming to the United States.

816
00:41:36,800 --> 00:41:38,600
Speaker 6: So that's something that's got to be balanced.

817
00:41:39,000 --> 00:41:42,480
Speaker 16: Exactly right, because the United States is still well behind

818
00:41:42,560 --> 00:41:46,440
Speaker 16: the Chinese and eb technology maybe a decade behind. And

819
00:41:47,120 --> 00:41:50,720
Speaker 16: of course the Chinese auto industry is supported by its government,

820
00:41:50,840 --> 00:41:54,560
Speaker 16: so they have lower costs. So Jim Farley, the CEO

821
00:41:54,640 --> 00:41:57,799
Speaker 16: of Ford, says, keep the Chinese out, but we also

822
00:41:58,000 --> 00:41:59,840
Speaker 16: value our partnerships with the Chinese.

823
00:42:00,120 --> 00:42:01,879
Speaker 5: We want to do more of them.

824
00:42:02,040 --> 00:42:05,600
Speaker 16: So yeah, it's a very fine line that they're treading here,

825
00:42:05,840 --> 00:42:08,320
Speaker 16: and they do need Chinese tech if they want to

826
00:42:08,400 --> 00:42:12,000
Speaker 16: have evs, but they also would be swamped by Chinese

827
00:42:12,040 --> 00:42:15,600
Speaker 16: competition if Chinese evs were allowed in For America.

828
00:42:16,120 --> 00:42:20,600
Speaker 2: Bloombergs Keith Norton and Bloomberg's Mike Shepherd, thank you very much. Okay,

829
00:42:20,640 --> 00:42:23,320
Speaker 2: before we go, let's take a look at today's big number.

830
00:42:23,440 --> 00:42:25,640
Speaker 2: One hundred and thirty five billion dollars. That's how much

831
00:42:25,719 --> 00:42:29,360
Speaker 2: Netflix says it has spent over the past decade making

832
00:42:29,440 --> 00:42:32,560
Speaker 2: films and TV shows in more than fifty countries. That's

833
00:42:32,600 --> 00:42:35,480
Speaker 2: a part of a new website called the Netflix Effect

834
00:42:35,840 --> 00:42:38,240
Speaker 2: that the company is using to show how it boosts

835
00:42:38,280 --> 00:42:41,800
Speaker 2: local economies. Netflix says the impact goes beyond direct employment.

836
00:42:41,840 --> 00:42:45,439
Speaker 2: For instance, highlighting how South Korea Caro sort of twenty

837
00:42:45,520 --> 00:42:47,400
Speaker 2: five percent spike in airline bookings.

838
00:42:47,880 --> 00:42:50,359
Speaker 3: I just think new film Nana and the Magician's Nephew

839
00:42:50,400 --> 00:42:53,759
Speaker 3: actually going to having a long run in theaters. How

840
00:42:54,000 --> 00:42:56,920
Speaker 3: Netflix is changing the game that does it though, for

841
00:42:57,040 --> 00:42:59,120
Speaker 3: this edition of Bloomberg Tech, a.

842
00:42:59,200 --> 00:43:01,719
Speaker 2: Big show ahead, a big remainder of the week. Don't

843
00:43:01,760 --> 00:43:03,719
Speaker 2: forget to check out the pod. That's where you can

844
00:43:03,800 --> 00:43:05,719
Speaker 2: find it. This is Bloomberg Tech.

845
00:43:06,560 --> 00:43:06,960
Speaker 7: M HM