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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 v Lovelow in San Francisco.

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Speaker 2: This is Bloomberg Tech. Coming up. Tech helps stocks close

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Speaker 2: in on record highs with Mag seven earnings.

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Speaker 3: Plus Bridget Mendland Northwood and raises one hundred million dollars

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Speaker 3: to modernize space infrastructure on Earth.

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Speaker 2: And Amazon shuddering its physical stores but doubling down on

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Speaker 2: deliveries Walmart, Uber and door Dash all drop.

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Speaker 3: Let's check out more broad moves on the market right now.

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Speaker 4: And because we have a wall of call it worry.

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Speaker 3: Whether you're thinking about what the mag seven is going

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Speaker 3: to report, whether you're thinking about the federal rate decision

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Speaker 3: on Wednesday, a lot for the market time digest, but

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Speaker 3: still were pushed to record highs the S and P

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Speaker 3: five hundred. We have up nine ten percent on the

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Speaker 3: Nasdaq one hundred, and I know you're checking on individual movers.

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Speaker 3: They've been helping some moves in the benchmark.

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Speaker 2: Yeah, an interesting deal up to six billion dollar partnership

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Speaker 2: between Meta and Corning for fiber optic cabling to support

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Speaker 2: Meada's data center efforts over a number of years. You

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Speaker 2: know Corning, right, it's a key optics supplier to Apple,

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Speaker 2: for example, But look at that stock absolutely flying up

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Speaker 2: more than seventeen percent. There's a lot going on as

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Speaker 2: well in the semiconductor space. Micron is long term trying

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Speaker 2: to triage the shortage of supply, investing a lot of

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Speaker 2: money up to twenty four billion dollars over years in

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Speaker 2: Singapore that's focused on land and then overnight and career

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Speaker 2: sk Heinex the biggest move of the upside. Basically, there's

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Speaker 2: dip buying, there's retail investors coming in, and there's a

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Speaker 2: lot of focus. What's happening in the context of a

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Speaker 2: US career trade agreement agreement where there might be exemptions.

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Speaker 2: Let's get to all of that. Bloomberg Senior Tech editor

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Speaker 2: Mike Shephard joins us. Now, let's start with the Micron piece. Right,

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Speaker 2: Like the story is well told if I say to

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Speaker 2: myself on this program about the memory shortage and memory

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Speaker 2: pricing situation. But Micron here is looking at where it

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Speaker 2: can expand supply. It's looking at Singapore.

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Speaker 5: What do we need to know, Well, it's looking at

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Speaker 5: Singapore ed and this is over a ten year period

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Speaker 5: and twenty four billion dollar investment there. And what they're

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Speaker 5: looking at a specifically is so called nand memory, and

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Speaker 5: this is something that is in demand to meet the

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Speaker 5: needs of artificial intelligence chips and processors more broadly, and

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Speaker 5: it's an area of focus because for AI, the memory

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Speaker 5: needs are enormous and they are not fully being met.

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Speaker 5: Of course, Micron competes with Samsung and s k Heinex

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Speaker 5: in this memory market, and all three companies have warned

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Speaker 5: of increasingly tight supplies. And this supply issue also has

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Speaker 5: spillover effects. It It actually touches on smartphonemakers and PC

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Speaker 5: makers too, because as those companies that we just mentioned

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Speaker 5: shift their efforts to meet the needs of the AI

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Speaker 5: data centers, the areas for PCs and smartphones risk going

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Speaker 5: wanting in the SSD type memory and flash memory that

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Speaker 5: is needed for those kinds of devices. So we're seeing

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Speaker 5: that expansion by Micron. This just comes at less than

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Speaker 5: two weeks after Micron cut the ribbon on a one

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Speaker 5: hundred billion dollar plant in upstate New York one that's

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Speaker 5: been a couple of years in coming. So we are

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Speaker 5: watching to see how much more these companies are going

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Speaker 5: to be investing not only in Asia but also in

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Speaker 5: the US.

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Speaker 3: As well, and how much more of our shares can fly.

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Speaker 3: Just think sk Heinis at a new record high, even

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Speaker 3: as we see the threat of well broader tariffs in

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Speaker 3: South Korea. We know the chip makers are excluded, but

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Speaker 3: sk Heinis in a record because it's going to be benefiting

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Speaker 3: from Microsoft's push into AI chips as well.

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Speaker 2: Mike, Well, that's right.

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Speaker 5: And I'm glad you brought that up, Carol, because we

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Speaker 5: saw the news yesterday. We all followed it so closely

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Speaker 5: on this plan by Microsoft to introduce a new generation

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Speaker 5: of its Maya AI chip. The Maya two hundred and

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Speaker 5: local business paper in South Korea, the mainly business newspaper,

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Speaker 5: is reporting that as many as six Skhinex HBM three

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Speaker 5: E units will go into each Maya processor. We don't

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Speaker 5: know how many of these Maya two hundred processors Microsoft

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Speaker 5: will ultimately have produced for its needs for its data

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Speaker 5: centers and for other customers as well, but the promise

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Speaker 5: is big, and it signals that there could be a

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Speaker 5: lot of demand for this HBM THREEE processor that sk

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Speaker 5: Heinex has developed to meet those AI memory needs, and

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Speaker 5: it could be something else. Now you mentioned the threat

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Speaker 5: of additional tariffs. The President yesterday warned that the South

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Speaker 5: Korea trade deal could be reworked to jack up the

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Speaker 5: teriff freight on South Korean imports to twenty five percent.

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Speaker 5: For now, we're not seeing anything effect memory, but we'll

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Speaker 5: be watching that closely because there is a lot of

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Speaker 5: pressure from the administration for more investment by South Korean

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Speaker 5: companies here in the US.

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Speaker 3: Mike Shepherd breaking it down so well as always, we

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Speaker 3: thank you AT's return to us stox right now because

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Speaker 3: if you said, the near record highs tech shares have

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Speaker 3: been leading the way again as we brace for earning season,

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Speaker 3: it comes thick and fast. At Weekles's discussed it all

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Speaker 3: with Christina who for Chief Market Strategists and Man Group,

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Speaker 3: and we still have tariff anxiety. You still have the

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Speaker 3: warriors of what the Friend's going to do tomorrow, and

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Speaker 3: yet we push higher. Is that the fundamental analysis we

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Speaker 3: should have that their numbers are going to be good.

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Speaker 6: I do think the numbers will be good, but I

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Speaker 6: think there could be obstacles as we move through the year.

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Speaker 6: And first off, I would anticipate that if we do

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Speaker 6: see a big increase or at least a substantial increase

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Speaker 6: in yields on the long end that could very easily

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Speaker 6: exert downward pressure on tech stock prices. So I think

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Speaker 6: that could be the first problem. But as we move

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Speaker 6: through the year, we could see problems with financing, some

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Speaker 6: issues with Nimby.

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Speaker 3: Okay, so go there the financing you mean around AI

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Speaker 3: data centers. You think about the anxiety building up around

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Speaker 3: Oracle and the debt that it has to take on.

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Speaker 6: Absolutely, I think that that could very well slow down

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Speaker 6: the AI data center build out. So there are a

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Speaker 6: number of different things that could slow progress over the

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Speaker 6: course of the year and really tamp down stock prices.

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Speaker 2: Christina, so stock's in near record highs and tech is

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Speaker 2: pushing the way and the Nasdaq one hundreds up for

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Speaker 2: a fifth consecutive session right ahead of earnings. Explain that

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Speaker 2: that psychology of the market, why they would push the

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Speaker 2: market higher ahead of what is a critical week for

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Speaker 2: some of the biggest technology names in the world.

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Speaker 6: Well, there is an old adage buy on the rumor

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Speaker 6: sell on the news, and I do think there is

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Speaker 6: a lot of positive sentiment right now around these companies

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Speaker 6: being able to meet and potentially exceed earning ze expectations.

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Speaker 6: So I think that's what's happening right now. I also

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Speaker 6: believe something else is occurring, and we have to recognize

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Speaker 6: that the backdrop is an economy that is sputtering. I

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Speaker 6: am in the minority in this view, but I do

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Speaker 6: think the economy is facing some very significant headwinds right now.

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Speaker 6: We just saw consumer confidence reading that was the lowest

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Speaker 6: since twenty fourteen, and I think what happens typically is

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Speaker 6: in an environment like that, investors move to technology. They

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Speaker 6: move to areas that are more defensive, that can perform

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Speaker 6: well in a variety of different environments, the secular place.

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Speaker 6: And again tech has been the poster child for secular

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Speaker 6: place for some time now.

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Speaker 2: So in that sense, though like nothing changes, we write

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Speaker 2: in our markets wrap on the terminal, which is like

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Speaker 2: it's the first thing you read every morning, right, but

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Speaker 2: it says, in spite or not, even a slide in

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Speaker 2: consumer confidence could stop the market rally. At the end

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Speaker 2: of the day, we'll go into this earnings period at

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Speaker 2: the same things capital expenditures and top line growth of

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Speaker 2: the biggest companies, and then you'll come back or your

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Speaker 2: peers will say well, these companies have really strong balance

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Speaker 2: sheets and they're quite well diversified to weather an economic

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Speaker 2: slow down. Nothing's really new.

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Speaker 6: Well, I think what is becoming increasingly true is that

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Speaker 6: there is a divorcing, a decoupling between Wall Street and

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Speaker 6: Main Street, and that is most obvious in the tech sector.

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Speaker 6: So we can see strong balance sheets, we can see

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Speaker 6: companies that are performing well. But and this is a

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Speaker 6: big butt, we could see external forces like yields on

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Speaker 6: the long end, the ten year treasure yield, if it

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Speaker 6: were to get to five percent or higher, I think

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Speaker 6: that would exert downward pressure, especially on tech stock prices.

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Speaker 3: So Christina, do you sell into that or do you

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Speaker 3: just load up when the prices get lower?

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Speaker 4: And longer term? Still they committed to tech briefly, please, So.

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Speaker 6: I would say staying committed longer term to tech, but

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Speaker 6: ensuring you're well diversified. You are taking some profit and

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Speaker 6: moving your exposure because tech is not just in the

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Speaker 6: United States, it's also in China, where valuations are significantly lower.

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Speaker 6: So this is an opportunity I think to diversify portfolios.

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Speaker 2: Christina Hooper, chief market strategist in the Man Group. Thank

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Speaker 2: you very much, Amazon is closing its Amazon branded grocery

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Speaker 2: stores and automated grab and go markets, eliminating two centerpieces

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Speaker 2: of its push into physical retail and caro. Very interesting

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Speaker 2: here because actually Amazon's continue to push higher since the news.

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Speaker 2: The main takeaway is not that they're closing fourteen ghost

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Speaker 2: stores and fifty eight fresh stores. That's small footprint, but

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Speaker 2: actually even more committed to delivery. You tell me about

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Speaker 2: the names that dropped in reaction, I.

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Speaker 4: Mean, isn't it interesting?

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Speaker 3: Well, exactly to your point, the fact that we see

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Speaker 3: door Dash, we'll see other of those delivery companies maybe

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Speaker 3: see it feeling the effects from all of this. But

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Speaker 3: what's really interesting as well to sort of take on

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Speaker 3: board is they're also deploying massive scale in terms of

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Speaker 3: bricks and water in Chicago.

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Speaker 4: But it's alongside the.

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Speaker 3: Element that's also going to be helping delivery.

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Speaker 4: It's also going to be about warehouse space.

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Speaker 3: So they're just rethinking the way in which they put

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Speaker 3: bricks and water on the ground.

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Speaker 7: Right.

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Speaker 3: Well, we're looking Walmarts, off, Ubers, off, door Dashes off.

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Speaker 3: It really speaks to maybe Amazon investors thinking this is

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Speaker 3: a sign of strength, a good pivot.

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Speaker 2: Yeah, And lastly, grocery commitment, right, Like, they're not saying

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Speaker 2: we're done with grocery, they're just saying we're moving it online.

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Speaker 2: And that's reflected in that market reaction.

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Speaker 3: Though it's quite like those Paler stores though, got to

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Speaker 3: say rest in peace. Coming up, autonomous trucking startup Gatick.

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Speaker 4: Into a new deal. We'll discuss the self.

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Speaker 3: Driving companies growth with its CEO. That's next list blue

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Speaker 3: bag Tech.

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Speaker 2: Autonomous trucking company Gatick has landed a deal with a

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Speaker 2: major consumer goods company. Gatic's not named the customer yet,

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Speaker 2: but says the deal will double its contracted revenue to

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Speaker 2: six hundred million dollars over the next five years, joining

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Speaker 2: us as Gatti CEO and co founder Galton Nrang. Look, yeah,

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Speaker 2: I'm going to few the opportunity to day in the customer.

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Speaker 2: I know that you're not going to. I've pushed you

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Speaker 2: over a number of days. But I think the main

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Speaker 2: thing our audience wants to get a sense of is

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Speaker 2: this is real. You have trucks on roads with major

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Speaker 2: customers that are paying you, and therefore you're booking revenues

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Speaker 2: on it. Take it from there and explain the reality

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Speaker 2: for sure.

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Speaker 8: So as you know, God Think is in the business

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Speaker 8: of autonomous route and today we're announcing that we're operating

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Speaker 8: fully driver lists, faith only drugs with no safety driver,

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Speaker 8: no safety observer across real faith operations, multiple markets.

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Speaker 2: To do it is small though, like ten trucks right

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Speaker 2: now in today, by year end all one hundreds of drugs.

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Speaker 8: But very soon in the coming weeks, we'll have over

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Speaker 8: sixty drugs fully driver lists on public roads doing daily

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Speaker 8: commercial operations.

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Speaker 2: That's cool.

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Speaker 3: Talk to us how legislatively this has worked? Regularly this

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Speaker 3: has worked? How have you managed to make this a reality?

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Speaker 3: While yes, we see real impact from waymowing cars, but

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Speaker 3: in certain states, in certain areas.

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Speaker 8: Where are you working so you know today we're live

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Speaker 8: across multiple markets. This is Texas, Northwest, Arkansas, Phoenix. We

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Speaker 8: work very closely with the regulators at the local, Lebel,

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Speaker 8: state level, federal level, and from the early days we

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Speaker 8: decided to focus on automating these regional networks, which is

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Speaker 8: within the states, and that's one of the fastest ways

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Speaker 8: to commercialize this technology.

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Speaker 3: Commercializing then to where we've talked about six herremillion, just

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Speaker 3: one key customer.

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Speaker 4: What do you think your revenue run?

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Speaker 6: Right?

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Speaker 4: Is going to look like.

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Speaker 8: So today we're working with some of the largest companies

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Speaker 8: across retail, grocery, e commerce, and distribution. So each of

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Speaker 8: these customers have made multi year commitment. What's unique about

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Speaker 8: these commitments is these are non cancellable commitments where our

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Speaker 8: technology is now being absorbed across their supply chain at scale.

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Speaker 2: Those are the customers that you can name. We're showing

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Speaker 2: them on the screen, Kroger, Tyson, Walmart. People will say, well,

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Speaker 2: if you can't name this one, how real is it,

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Speaker 2: I'm going to put it out there, right, because we're

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Speaker 2: transparent on this show. The business model is interesting. You

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Speaker 2: don't sell them the trucks. What is the business model?

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Speaker 8: So it's an autonomous transportation as a service model as

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Speaker 8: a service as a service, yes, where we charge a

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Speaker 8: fixed feed prodrug pert a year, and each of these

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Speaker 8: commit commitments are multi year long. So we have revenue

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Speaker 8: certainty from each of these customers and that's also very

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Speaker 8: unique compared to some of the other models.

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Speaker 9: In our space.

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Speaker 2: You have some peers in industry. One of them is Aurora, right,

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Speaker 2: there are some similarities and differences. One is that they're public.

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Speaker 2: You're private, sure, let's talk about that first. I mean,

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Speaker 2: you know, you've been pretty open that there's a route

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Speaker 2: to the public markets. What would be the motive to

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Speaker 2: do that?

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Speaker 8: So let me start with the fact that we have

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Speaker 8: a lot of respect for all the peers in the space.

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Speaker 8: But what has been our focus from day one is

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Speaker 8: helping our customers move freight from their real how to

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Speaker 8: retail stores and doing that at scale. And with this milestone,

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Speaker 8: we have been able to prove that it's real, it's

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Speaker 8: happening at scale. So today, truly there is no safety driver,

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Speaker 8: no observer on public roads and in our space, no

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Speaker 8: one can make that claim today public well, we are

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Speaker 8: well caplized today with the very strong runway and have

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Speaker 8: clear line of sight towards profitability, and we're always evaluating

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Speaker 8: all the options that we have and keeping a very

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Speaker 8: close watch on the market conditions.

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Speaker 3: Partners From a technology perspective, obviously, in Nvidia, how much

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Speaker 3: do you rely on on the hardware at the moment?

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Speaker 4: How much is that cost base? Where do you look

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Speaker 4: for these partnerships.

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Speaker 8: So with our latest generation, generation three, the hardware is

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Speaker 8: fully hardened and we're working very closely with the Nvidia

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Speaker 8: with the Suzu Motors to mass produce these drugs, and

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Speaker 8: towards the end of next year, Isuzu's production plant in

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Speaker 8: South Carolina will be up and running and we expect

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Speaker 8: to have these vehicles coming off the line at the

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Speaker 8: big volumes. We're looking at tens of thousands of vehicles annually.

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Speaker 2: Caroline's really asked this, right, but we should go back

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Speaker 2: to it, which is the regulatory environment. Yes, you know

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Speaker 2: you've launched in these markets because you can. How much

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Speaker 2: do you think we need this federal level framework for

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Speaker 2: you to go from very small to something more substantial.

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Speaker 8: So it's really important to like have a nationwide av framework, right,

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Speaker 8: So we work and we don't. Well, we're working very

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Speaker 8: closely with the current administration to inform them, educate them

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Speaker 8: on the safelod lot of this technology, and we expect

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Speaker 8: to have a nation wide framework really soon.

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Speaker 3: Come back when you've helped work that one out. Golton Narraang.

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Speaker 3: It's great has in time with the GETIC CEO. Meanwhile,

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Speaker 3: elsewhere in vehicles, GM CEO Mary Barras As a regulatory.

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Speaker 4: Shift away from EVS.

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Speaker 3: We'll see slower adoption, but the company is still committed

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Speaker 3: to its EV pipeline MEGS, Matt Miller sat down with

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Speaker 3: the GM CEO, Mary Barrow, take a listen.

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Speaker 9: The whole industry.

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Speaker 7: We were on a p as that we were working

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Speaker 7: to get to forty to fifty percent evs by twenty thirty.

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Speaker 7: So now that the regulatory environment has changed and the

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Speaker 7: consumer incentives have gone, there is going to be slower

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Speaker 7: EV adoption. We're still committed evs and we've got a

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Speaker 7: great portfolio that we're working on taking costs out. But

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Speaker 7: in the meantime, we also have a great internal combustion

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Speaker 7: engine platform, and you're right, full size trucks are one

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Speaker 7: of the strengths we have, as well as full size SUVs,

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Speaker 7: mid sized crossovers. So we really have a strong line

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Speaker 7: up across the board and that is really what is

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Speaker 7: fueling our business success.

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Speaker 10: I have had as the host of Hot Pursuit of

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Speaker 10: Bloomberg podcast about cars, the opportunity to drive a lot

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Speaker 10: of your evs, from the Sierra EV to the Hummer

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Speaker 10: EV to the Escalaid IQ and they're fantastic products. Are

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Speaker 10: you not deterred that Americans aren't buying more of these vehicles?

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Speaker 10: You know how capable, how capable they are you know

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Speaker 10: how useful they are in daily life. What needs to

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Speaker 10: happen for more Americans to buy these evs?

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Speaker 7: Well, I think the consumer is very rational when they're

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Speaker 7: making a decision about what card by.

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Speaker 9: Let's remember it's one.

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Speaker 7: Of the most important and expensive decisions that they make.

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Speaker 7: And one of the things we have to continue to

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Speaker 7: work on to drive ev adaption is a more robust

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Speaker 7: charging infrastructure, and that still is continuing to happen, So

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Speaker 7: every quarter more and more chargers are available. I think

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Speaker 7: we as people in their individual communities see that they've

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Speaker 7: got a robust charging network and believe if they have

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Speaker 7: to go on a road trip there's that as well,

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Speaker 7: they're going to make that choice.

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Speaker 2: That was GM CEO Mary Barras speaking with Bloomberg's Matt Miller.

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Speaker 2: Now coming up, we will dive into anthropics new tool

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Speaker 2: and how it could broadly impact jobs. Come up next,

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Speaker 2: this is Bloomberg Tech Silicon Valley leaders adjoining tech workers

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Speaker 2: decrying tensions in Minnesota after two US citizens were fatally

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Speaker 2: shot by federal agents. Anthropic CEO Dario Emma Day posting

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Speaker 2: about the quote importance of preserving democratic values and rights.

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Speaker 2: Open AI CEO Sam Altman wrote in an internal memo

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Speaker 2: to staff yesterday, that's what quote. What's happening with Ice

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Speaker 2: is going too far. That's according to a Bloomberg source.

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Speaker 2: The executives joined the chorus of other tech leaders, including

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Speaker 2: LinkedIn co founder Reid Hoffman, Reddit co founder Alexis o'hanian,

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Speaker 2: and venture capitalist Vinode Koestler, who have spoken out.

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Speaker 3: Karen one to watch now, let's shift elsewhere for Anthropic

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Speaker 3: right now, because it is released a new version on

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Speaker 3: its Claude chatbot called claud cowork. They can take actions

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Speaker 3: on a computer on your computer. Bloomberg opinion columnist parme

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Speaker 3: Olsen writes that this could have broad repercussions and potentially

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Speaker 3: be painful for some white collar workers, even as Anthropic

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Speaker 3: frames itself as the most safety conscious of the AI developers.

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Speaker 3: Parmi Elsen joins us, Now, so the redefinement of the

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Speaker 3: engineering talent right now, the companies you've spoken to, How

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Speaker 3: is Claudes products changing that?

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Speaker 2: Yeah?

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Speaker 11: I mean, first of all, claud cowork is the new product.

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Speaker 11: And before that was claud Code, which is an AI

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Speaker 11: tool for writing software programs, and that's been around for

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Speaker 11: about a year and it's been getting rave reviews among

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Speaker 11: technologists and coders who can use it to spin up

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Speaker 11: a website within hours, and the people an Anthropic effectually

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Speaker 11: use that tool to build this new tool. They did

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Speaker 11: it in ten days. They didn't write a single line

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Speaker 11: of code, or very little code. And this new version

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Speaker 11: is something that it's sort of like people have been

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Speaker 11: talking about the word AI agents. That was a big

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Speaker 11: buzzword last year, but it sort of fell flat.

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Speaker 9: There were issues with reliability.

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Speaker 11: This could be perhaps the first mainstream breakout of an

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Speaker 11: AI agent because it does work on your computer, accesses

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Speaker 11: files and applications, and not just saying that it does

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Speaker 11: that people are actually using I've used it, and there's

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Speaker 11: been a lot of general kind of excitement and buzz

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Speaker 11: about this tool that is able to just take action,

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Speaker 11: not just you know if you research in.

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Speaker 2: Part of the industry is paying attention. Like I think

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Speaker 2: that CS Caroline was speaking to a Montenesia from General Catalyst.

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Speaker 2: I think he summed it up pretty well.

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Speaker 12: Just listen to this, yeah, squad, it's it's really redefining

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Speaker 12: the engineering department, and just think about the size of

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Speaker 12: that market you might you spend on tools and engineers

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Speaker 12: to be able to build products, and you know, the

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Speaker 12: amount of progress is like Silicon Value companies now code

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Speaker 12: self rights for most of what they do. I think

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Speaker 12: it's a real transformation with clouds really enabled.

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Speaker 2: There there's a line in your Bloomberg opinion column, which

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Speaker 2: by the way, is one of the most read things

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Speaker 2: today on Bloomberg about the relevance to Microsoft. You know,

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Speaker 2: Microsoft historically is very good at selling software that you

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Speaker 2: could otherwise get for free. Just just talk a little

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Speaker 2: bit more about that. You kind of flicked it.

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Speaker 11: I just looked at it because I thought Cowork is

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Speaker 11: pretty much what Copilot could have been and probably should

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Speaker 11: have been. Copilot is the AI tool that's underpinned by CHATGBT,

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Speaker 11: GPT four point five or whatever the latest model is,

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Speaker 11: and it has access to all your office tools, so

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Speaker 11: it should be able to, you know, take documents from

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Speaker 11: a particular folder and turn them into a spreadsheet, as

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Speaker 11: claud Cowork can do, but it doesn't have quite that

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Speaker 11: same capability. So I think the speed at which Anthropic

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Speaker 11: was able to do this and using an AI tool

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Speaker 11: to build the software in the first place, really speaks

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Speaker 11: to how effective AI coding has become. You know, coders

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Speaker 11: are saying now they don't even write code anymore. They

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Speaker 11: just talked to it in plain language. And the reason

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Speaker 11: I think this is kind of meaningful for other jobs

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Speaker 11: is coding AI coding a tool that can do that

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Speaker 11: can generalize to other domains. This is what Anthropics CEO

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Speaker 11: has been saying. That's why they're moving into healthcare and

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Speaker 11: who knows what other areas they will move into. But

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Speaker 11: I think because computer code is such a perfect digital

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Speaker 11: representation of you know, the behavior that you and the

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Speaker 11: actions that you can take online. That's why it can

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Speaker 11: be so good as a tool to do other things

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Speaker 11: like operate a computer.

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Speaker 2: Bloomberg Opinions, PA me awesome with today's must read, Thank

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Speaker 2: you very much, so coming up Northward raises one hundred

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Speaker 2: million dollars in its latest funding. We speak with the

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Speaker 2: CEO Bridget Menla. That conversation coming up next and you

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Speaker 2: don't want to miss it. This is Bloomberg Tech.

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Speaker 4: Welcome back to Bloomberg Tech.

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Speaker 3: A quick check on these markets Nasdaq one hundred shows

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Speaker 3: big tech is back on top. We're still almost a

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Speaker 3: percentage point as we brace for mag seven earnings. Interesting

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Speaker 3: move for bitcoin, we call it digital gold Well it's

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Speaker 3: not getting the debasement trade that real gold is. At

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Speaker 3: the moment, we're an eighty two hundred and forty six though,

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Speaker 3: just up in the green ever so slightly. Move on

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Speaker 3: to the individual movers. We want you to keep an

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Speaker 3: eye on Amazon up almost one and a half percent.

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Speaker 3: They're closing Amazon Fresh Amazon ghost stores with some locations

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Speaker 3: are going to be converted into whole foods market stores. Look,

438
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Speaker 3: they are not moving away from groceries. They're going to

439
00:23:10,880 --> 00:23:13,919
Speaker 3: sell them online and offline. But really this is about

440
00:23:13,960 --> 00:23:16,520
Speaker 3: delivery once again. And you also have to look at

441
00:23:16,520 --> 00:23:18,280
Speaker 3: what's happening over at Pinterest. We're going to dwell on

442
00:23:18,280 --> 00:23:20,119
Speaker 3: that for a minute. We're off by almost ten percent.

443
00:23:20,840 --> 00:23:23,520
Speaker 3: They are letting go of people less than fifteen percent

444
00:23:23,560 --> 00:23:25,600
Speaker 3: of its workforce. We understand that they're planning to reduce

445
00:23:25,640 --> 00:23:28,359
Speaker 3: office space as well, and Bloomberg Intelligence is saying it

446
00:23:28,440 --> 00:23:32,240
Speaker 3: likely suggests more aggressive investments in building AI capabilities. Let's

447
00:23:32,280 --> 00:23:36,119
Speaker 3: stick in with blouemmeg Exiti's reporter around Verastelica, a company.

448
00:23:35,760 --> 00:23:37,240
Speaker 4: That has seen competition ride.

449
00:23:37,280 --> 00:23:39,680
Speaker 3: Maybe as we talk more and more about Agendaki, we're

450
00:23:39,720 --> 00:23:42,159
Speaker 3: just talking about it in terms of anthropic For example.

451
00:23:43,080 --> 00:23:45,440
Speaker 13: Yes, good morning, thanks for having me. So pinterest is

452
00:23:45,480 --> 00:23:47,760
Speaker 13: down quite significantly today. It does seem like there is

453
00:23:47,800 --> 00:23:50,680
Speaker 13: a lot of concern that these workforce reductions and other

454
00:23:50,720 --> 00:23:53,199
Speaker 13: steps that they're taking in terms of this restructuring, that

455
00:23:53,320 --> 00:23:56,840
Speaker 13: maybe this pours in some weaker growth trends at the company.

456
00:23:57,040 --> 00:23:58,840
Speaker 13: As I'm sure you know, this stock has struggled for

457
00:23:58,960 --> 00:24:01,800
Speaker 13: quite a bit of time as it really just has

458
00:24:01,840 --> 00:24:05,120
Speaker 13: a lot of difficulty going up against the bigger players

459
00:24:05,160 --> 00:24:08,280
Speaker 13: in the space, most notably Meta. So the stock is

460
00:24:08,320 --> 00:24:09,960
Speaker 13: quite down, and I think people are sort of like

461
00:24:10,000 --> 00:24:11,960
Speaker 13: wondering what's going to be sort of a catalyst or

462
00:24:11,960 --> 00:24:12,880
Speaker 13: revive growth here.

463
00:24:14,119 --> 00:24:17,480
Speaker 2: Ryan, Data is fun. I really hope that you agree

464
00:24:17,520 --> 00:24:19,560
Speaker 2: with that. And so I'm looking at the Bloomberg terminal.

465
00:24:19,840 --> 00:24:22,639
Speaker 2: The Nazak one hundred is for a five day stretch

466
00:24:22,680 --> 00:24:24,720
Speaker 2: the first time this year. It had a five day

467
00:24:24,720 --> 00:24:27,360
Speaker 2: stretch at the end of December, so not that long ago.

468
00:24:27,960 --> 00:24:32,480
Speaker 2: We're right on the cusp of huge earnings and tech

469
00:24:32,560 --> 00:24:36,720
Speaker 2: is driving this market higher. Why great question.

470
00:24:36,760 --> 00:24:39,840
Speaker 13: So going into this recent rally, obviously there had been

471
00:24:39,880 --> 00:24:42,080
Speaker 13: a rotation out of Tech, a lot of people looking

472
00:24:42,080 --> 00:24:44,520
Speaker 13: elsewhere in the market, especially sort of cyclical parts of

473
00:24:44,600 --> 00:24:45,160
Speaker 13: the market.

474
00:24:45,280 --> 00:24:47,280
Speaker 2: There was some concern about Tech's earnings.

475
00:24:47,800 --> 00:24:50,080
Speaker 13: Is growth decelerating or is this going to be enough

476
00:24:50,119 --> 00:24:53,240
Speaker 13: to justify the valuations there. At the same time, people

477
00:24:53,280 --> 00:24:56,040
Speaker 13: continue to view tech as really a port of safety

478
00:24:56,080 --> 00:24:59,000
Speaker 13: in the market, continues to be very dominant and still

479
00:24:59,000 --> 00:25:01,080
Speaker 13: has the highest growth among the S and P five

480
00:25:01,160 --> 00:25:04,600
Speaker 13: hundred sectors. People remain pretty positive about his prospects, about

481
00:25:04,600 --> 00:25:06,919
Speaker 13: the potential of AI, all that is there. It's not

482
00:25:06,960 --> 00:25:08,960
Speaker 13: surprising to me to see a little bit of people

483
00:25:09,000 --> 00:25:11,959
Speaker 13: wanting to jump in buy that dip, you know, especially

484
00:25:11,960 --> 00:25:12,800
Speaker 13: ahead of earnings.

485
00:25:15,160 --> 00:25:17,760
Speaker 2: The most ryan for Stelica. Oh sorry, carry, I got

486
00:25:17,840 --> 00:25:21,280
Speaker 2: excited about the data thing I do with the earnings

487
00:25:21,320 --> 00:25:24,080
Speaker 2: preview and embraced right, let's go to private markets for

488
00:25:24,119 --> 00:25:27,119
Speaker 2: a second. Northwood has announced it's raised one hundred million

489
00:25:27,160 --> 00:25:30,720
Speaker 2: dollars in new funding led by Washington Harbor Partners and

490
00:25:30,760 --> 00:25:34,480
Speaker 2: Indres and Horowitz. The Southern California based company makes phased

491
00:25:34,600 --> 00:25:37,560
Speaker 2: array and tenors and other things that help increase satellite

492
00:25:37,600 --> 00:25:41,080
Speaker 2: connectivity here on Earth. Here with the latest is Bridget

493
00:25:41,119 --> 00:25:45,359
Speaker 2: Menla Northwood CEO. You know, Bridget, We've been fortunate to

494
00:25:45,359 --> 00:25:47,120
Speaker 2: talk to you, you know, a number of times over

495
00:25:47,520 --> 00:25:50,040
Speaker 2: over the last year. Actually, like this is less than

496
00:25:50,040 --> 00:25:52,399
Speaker 2: a year from your Series A. And the thing that

497
00:25:52,440 --> 00:25:54,920
Speaker 2: I've learned speaking to us future investors is that you

498
00:25:55,840 --> 00:25:59,080
Speaker 2: move quickly, right, you move quickly on deployment of the tech.

499
00:25:59,320 --> 00:26:02,520
Speaker 2: But you've also let's start by just asking like, why

500
00:26:02,520 --> 00:26:04,400
Speaker 2: did you need to raise one hundred million dollars here?

501
00:26:04,560 --> 00:26:06,200
Speaker 2: There must be a need for that capital.

502
00:26:07,840 --> 00:26:11,520
Speaker 14: Yeah, absolutely, thanks for having me again, It's great to

503
00:26:11,560 --> 00:26:15,200
Speaker 14: be speaking with you all. For us, it's really about

504
00:26:15,240 --> 00:26:18,639
Speaker 14: taking space missions further faster. I think you guys have

505
00:26:18,640 --> 00:26:21,520
Speaker 14: been really tracking the developments in the space industry over

506
00:26:21,560 --> 00:26:23,879
Speaker 14: the past year, both on the commercial side and on

507
00:26:24,080 --> 00:26:24,840
Speaker 14: government side.

508
00:26:25,240 --> 00:26:26,800
Speaker 9: Domestically and abroad.

509
00:26:26,840 --> 00:26:29,240
Speaker 14: There's a ton of enthusiasm for what we can do

510
00:26:29,320 --> 00:26:31,320
Speaker 14: in space and really changing our.

511
00:26:31,200 --> 00:26:32,600
Speaker 9: Perceptions on what's possible.

512
00:26:33,400 --> 00:26:37,240
Speaker 14: Oftentimes, there winds up being more friction and taking those

513
00:26:37,240 --> 00:26:39,840
Speaker 14: space missions live due to the ground and that's something

514
00:26:39,840 --> 00:26:41,760
Speaker 14: that has to change. We have to be able to

515
00:26:42,119 --> 00:26:44,800
Speaker 14: push the boundaries on capabilities, and we have to be

516
00:26:44,840 --> 00:26:47,159
Speaker 14: able to do that on a rapid time scale. So

517
00:26:47,240 --> 00:26:50,800
Speaker 14: for us, what this funding represents is a significant amount

518
00:26:50,840 --> 00:26:52,960
Speaker 14: of demand that we've seen from a wide variety of

519
00:26:53,040 --> 00:26:55,640
Speaker 14: customers and being able to enable their missions to go

520
00:26:55,840 --> 00:27:00,560
Speaker 14: further faster. So this year has been a really exciting

521
00:27:00,960 --> 00:27:03,239
Speaker 14: example for us to kind of show what that end

522
00:27:03,280 --> 00:27:06,119
Speaker 14: to end concept looks like for Northwood. Many people do

523
00:27:06,240 --> 00:27:08,960
Speaker 14: know us by our Phase raise, which is critical to

524
00:27:09,000 --> 00:27:12,520
Speaker 14: how we think about the ground really introducing novel hardware

525
00:27:12,520 --> 00:27:14,840
Speaker 14: solutions so that we can do more in space. But

526
00:27:14,960 --> 00:27:17,960
Speaker 14: we view ourselves as an end to end partner for

527
00:27:18,040 --> 00:27:20,320
Speaker 14: these space missions all the way from the concept that

528
00:27:20,359 --> 00:27:22,399
Speaker 14: they are initially coming up with to the time when

529
00:27:22,400 --> 00:27:25,400
Speaker 14: their data is streaming live and actually you know, delivered

530
00:27:25,400 --> 00:27:26,159
Speaker 14: to end users.

531
00:27:26,359 --> 00:27:27,399
Speaker 9: And we've actually done that.

532
00:27:27,440 --> 00:27:30,480
Speaker 14: We've gone from an initial concept of saying, hey, let's

533
00:27:30,480 --> 00:27:33,720
Speaker 14: have dynamic links that you can access not just from

534
00:27:33,760 --> 00:27:36,000
Speaker 14: low Earth orbit but all the way up to geostationary

535
00:27:36,080 --> 00:27:39,960
Speaker 14: orbit in the same system, and then let's show how

536
00:27:39,960 --> 00:27:42,439
Speaker 14: fast we can bring that concept into reality. And so

537
00:27:42,880 --> 00:27:46,160
Speaker 14: you know, we're talking today as well about our contract

538
00:27:46,200 --> 00:27:48,399
Speaker 14: that we close with the US Space Force.

539
00:27:48,760 --> 00:27:50,639
Speaker 2: Well, bridget let me jump in here. Like they know,

540
00:27:50,680 --> 00:27:53,600
Speaker 2: it's a forty nine million dollar contract with the Space Force.

541
00:27:54,119 --> 00:27:56,240
Speaker 2: You know, what will you be doing with them specifically?

542
00:27:56,320 --> 00:27:58,840
Speaker 2: But also my understanding is that there is a link

543
00:27:58,880 --> 00:28:01,679
Speaker 2: here between the money that you raised in the Series

544
00:28:01,800 --> 00:28:04,679
Speaker 2: B and being able to kind of just execute on

545
00:28:04,720 --> 00:28:05,480
Speaker 2: that contract.

546
00:28:07,000 --> 00:28:11,399
Speaker 14: Absolutely well, we've already executed on that contract across a

547
00:28:11,480 --> 00:28:16,320
Speaker 14: number of milestones. So contract was executed and at this

548
00:28:16,359 --> 00:28:19,480
Speaker 14: point there's been a three month turnaround time from kickoff

549
00:28:19,520 --> 00:28:23,240
Speaker 14: of that contract to actually delivering links live in the field.

550
00:28:23,840 --> 00:28:26,200
Speaker 14: So we have those links live in the field already,

551
00:28:26,320 --> 00:28:28,720
Speaker 14: and so what the funding represents for us is, let's

552
00:28:28,880 --> 00:28:31,520
Speaker 14: scale that model, Let's do it more. Let's demonstrate how

553
00:28:31,520 --> 00:28:36,280
Speaker 14: we're able to deploy a global network of this portal

554
00:28:36,320 --> 00:28:40,160
Speaker 14: product that supports the dynamic links between lower orbit and

555
00:28:40,160 --> 00:28:44,040
Speaker 14: geostationary orbit, but also serve up more space capabilities that

556
00:28:44,080 --> 00:28:46,600
Speaker 14: we're getting a lot of appetite for. So the funding

557
00:28:46,600 --> 00:28:49,360
Speaker 14: really represents being able to serve the appetite that we're

558
00:28:49,360 --> 00:28:51,800
Speaker 14: seeing and hit larger production volumes.

559
00:28:52,040 --> 00:28:53,600
Speaker 3: We've been lucky enough to talk to some of your

560
00:28:53,680 --> 00:28:55,880
Speaker 3: key investors and Mina has been on the show before

561
00:28:55,920 --> 00:28:58,160
Speaker 3: from Washington Harbor Partners, and you put it to Ed

562
00:28:58,240 --> 00:29:02,360
Speaker 3: that Northwood provides the only viable approach capable of scaling

563
00:29:02,400 --> 00:29:06,280
Speaker 3: ground station capacity, but you're not actually technically the only

564
00:29:06,840 --> 00:29:09,640
Speaker 3: approach that could be taken because you could also go

565
00:29:09,640 --> 00:29:11,800
Speaker 3: to blue Halo for example. So what is your unique

566
00:29:11,800 --> 00:29:14,600
Speaker 3: setting point, how you differentiate it from others that have

567
00:29:14,640 --> 00:29:15,600
Speaker 3: been winning contracts.

568
00:29:17,160 --> 00:29:19,640
Speaker 14: Yeah, I think the way that we view our difference

569
00:29:19,720 --> 00:29:22,960
Speaker 14: is really for space providers today, they wind up running

570
00:29:23,120 --> 00:29:25,880
Speaker 14: two companies. They wind up having to run the space

571
00:29:25,920 --> 00:29:28,600
Speaker 14: mission that they're supporting, but they also have to stitch

572
00:29:28,640 --> 00:29:32,360
Speaker 14: together a complex value chain of different pieces of the ground.

573
00:29:32,480 --> 00:29:35,000
Speaker 9: You know, they have to think about ground hardware like you.

574
00:29:34,960 --> 00:29:38,200
Speaker 14: Mentioned, you know, blue Halo and other developer of phase

575
00:29:38,280 --> 00:29:40,440
Speaker 14: or A hardware, but they also have to think about,

576
00:29:40,800 --> 00:29:45,320
Speaker 14: you know, sites, global shipping logistics operations around the world.

577
00:29:45,320 --> 00:29:47,240
Speaker 14: They have to think about the software interfaces in the

578
00:29:47,280 --> 00:29:49,920
Speaker 14: network backbone attached to that. And so where we find

579
00:29:49,920 --> 00:29:53,320
Speaker 14: ourselves really differentiated is we take on that full problem scope.

580
00:29:53,640 --> 00:29:55,640
Speaker 14: And I think you know, what we've connected with with

581
00:29:55,760 --> 00:29:59,040
Speaker 14: MINA specifically on is the importance of being able to

582
00:29:59,080 --> 00:30:01,880
Speaker 14: deliver the end to end solution and do it on

583
00:30:01,920 --> 00:30:04,920
Speaker 14: a condensed timeline. And we feel like there's huge value

584
00:30:04,920 --> 00:30:06,680
Speaker 14: in being able to do that, and that's why we've

585
00:30:06,920 --> 00:30:08,800
Speaker 14: invested in that kind of differentiated approach.

586
00:30:09,480 --> 00:30:12,440
Speaker 3: You've kindly said, we've been focused on space for quite

587
00:30:12,440 --> 00:30:14,280
Speaker 3: a while here on the show, and many are now

588
00:30:14,320 --> 00:30:15,800
Speaker 3: training that advice on SpaceX.

589
00:30:15,840 --> 00:30:19,000
Speaker 4: But are you winning contract? How's your relationship being built

590
00:30:19,040 --> 00:30:21,160
Speaker 4: with Starlink for example? Are the I any talks along

591
00:30:21,160 --> 00:30:21,960
Speaker 4: that motion?

592
00:30:23,680 --> 00:30:23,840
Speaker 11: Yeah.

593
00:30:23,880 --> 00:30:27,200
Speaker 14: I think for us, we've seen significant interests from commercial

594
00:30:27,360 --> 00:30:32,560
Speaker 14: as well as government use cases. The ambition and the

595
00:30:32,640 --> 00:30:36,520
Speaker 14: challenge for space just continues to grow. And for ourselves,

596
00:30:36,520 --> 00:30:39,760
Speaker 14: we've had contact with that company and with other companies,

597
00:30:40,160 --> 00:30:43,560
Speaker 14: and we're excited to have our capabilities just kind of

598
00:30:43,560 --> 00:30:47,040
Speaker 14: be the proof in themselves that we are the infrastructure

599
00:30:47,080 --> 00:30:50,160
Speaker 14: provider that makes sense for a whole host of industry

600
00:30:50,240 --> 00:30:50,760
Speaker 14: use cases.

601
00:30:51,800 --> 00:30:54,720
Speaker 2: Bridgie, I know you don't want to focus on this necessarily.

602
00:30:54,760 --> 00:30:59,760
Speaker 2: You know, your former actor, platinum singer songwriter, you went away,

603
00:31:00,080 --> 00:31:03,840
Speaker 2: turned to academia, founded Northwood right at the end of

604
00:31:03,880 --> 00:31:06,320
Speaker 2: twenty twenty two, did a series A at the beginning

605
00:31:06,320 --> 00:31:08,600
Speaker 2: of twenty four and now here we are, and I

606
00:31:08,640 --> 00:31:11,080
Speaker 2: think there's a lot of interest to learn how big

607
00:31:11,160 --> 00:31:13,880
Speaker 2: is Northwood now? How many people? What is your footprint?

608
00:31:14,160 --> 00:31:16,720
Speaker 2: Where are you deployed around the world, because you have

609
00:31:16,800 --> 00:31:17,800
Speaker 2: done it quite quickly.

610
00:31:19,120 --> 00:31:23,920
Speaker 14: Yeah, we're just around seventy people. We have sites deployed

611
00:31:23,920 --> 00:31:27,880
Speaker 14: across two continents. At this point in time, we have

612
00:31:28,120 --> 00:31:31,600
Speaker 14: a full production facility running not just our Phasory product,

613
00:31:31,640 --> 00:31:34,560
Speaker 14: but two other hardware products that both fit in with

614
00:31:34,600 --> 00:31:37,880
Speaker 14: that hardware stack as well as work and complement to it.

615
00:31:38,480 --> 00:31:41,600
Speaker 14: So excited to be sharing those product lines as well.

616
00:31:42,320 --> 00:31:43,560
Speaker 14: And this year is going to be a really big

617
00:31:43,640 --> 00:31:46,600
Speaker 14: year for us. We're planning on deploying eighteen sites across

618
00:31:46,640 --> 00:31:50,520
Speaker 14: five continents. So just continuing to ramp up our production

619
00:31:51,880 --> 00:31:53,560
Speaker 14: and the offerings that we can provide to the space

620
00:31:53,600 --> 00:31:55,560
Speaker 14: industry this year, Bridget.

621
00:31:55,600 --> 00:31:58,160
Speaker 2: As you know, Caroline and I are very thorough on

622
00:31:58,200 --> 00:32:01,800
Speaker 2: Bloomberg Tech. Just very quickly, the company did not disclose

623
00:32:01,840 --> 00:32:05,440
Speaker 2: its valuation. Is northward at Unicorn status yet? Is that

624
00:32:05,520 --> 00:32:07,000
Speaker 2: a milestone that you've achieved.

625
00:32:09,360 --> 00:32:11,880
Speaker 14: We will not disclose valuation at this point in time,

626
00:32:12,160 --> 00:32:13,320
Speaker 14: but we're very.

627
00:32:13,160 --> 00:32:14,360
Speaker 9: Happy with where we ended up.

628
00:32:15,120 --> 00:32:18,320
Speaker 3: Nice answer, Briship Lendler of Northwood.

629
00:32:18,480 --> 00:32:19,400
Speaker 4: We always have to ask.

630
00:32:19,600 --> 00:32:23,080
Speaker 3: We appreciate you coming back, Thank you very much, indeed, congrats. Meanwhile,

631
00:32:23,080 --> 00:32:26,560
Speaker 3: coming up the AI landscape, it shifts from general AI

632
00:32:27,040 --> 00:32:30,080
Speaker 3: to highly specialized intelligence systems. We're going to be discussing

633
00:32:30,080 --> 00:32:32,200
Speaker 3: that with constantin Ula, of course, a partner at Sekoia.

634
00:32:32,520 --> 00:32:33,520
Speaker 4: This is bluebg Tech.

635
00:32:38,080 --> 00:32:39,600
Speaker 3: This is Bloomberg Tech, and you are looking at a

636
00:32:39,640 --> 00:32:40,680
Speaker 3: live shot at the principal room.

637
00:32:40,760 --> 00:32:42,840
Speaker 4: Check out the Bloomberg Tech podcast. Find it on the

638
00:32:42,920 --> 00:32:44,240
Speaker 4: terminal as well as online.

639
00:32:44,000 --> 00:32:57,120
Speaker 3: On Apple, Spotify, and iHeart this is Bloomberg. Moonshot AI

640
00:32:57,320 --> 00:33:00,320
Speaker 3: has released an upgrade to its flagship model. I'm thing

641
00:33:00,440 --> 00:33:03,800
Speaker 3: up pressure in China's domestic AI race look. The company's

642
00:33:03,880 --> 00:33:06,239
Speaker 3: K two point five model is said to outperform its

643
00:33:06,320 --> 00:33:11,040
Speaker 3: open source peers and can process text, images, videos simultaneously.

644
00:33:10,480 --> 00:33:11,880
Speaker 4: From just a single prompt now.

645
00:33:11,920 --> 00:33:14,640
Speaker 3: The release comes ahead of deep Seak's next major update,

646
00:33:14,680 --> 00:33:17,920
Speaker 3: which has been teasing now four weeks ed.

647
00:33:18,040 --> 00:33:20,160
Speaker 2: What have you got. Let's stay on the topic of

648
00:33:20,200 --> 00:33:23,400
Speaker 2: AI and not just general purpose models, but the rise

649
00:33:23,440 --> 00:33:28,640
Speaker 2: of artificial specialized intelligence. Joining us now Constantine Buler partner

650
00:33:29,040 --> 00:33:31,720
Speaker 2: at Sequoia, and this is your bet for the year.

651
00:33:32,640 --> 00:33:35,920
Speaker 2: You think and where you will focus your investments going

652
00:33:35,960 --> 00:33:38,600
Speaker 2: forward is in the area of do we call it

653
00:33:38,680 --> 00:33:43,400
Speaker 2: asi specialized intelligence as a place to start, define that

654
00:33:43,680 --> 00:33:46,200
Speaker 2: what is the difference? Absolutely?

655
00:33:46,200 --> 00:33:48,920
Speaker 15: Ad Caroline, Thanks for having me twenty twenty six is

656
00:33:48,960 --> 00:33:52,320
Speaker 15: going to be the year all about AI capabilities in

657
00:33:52,440 --> 00:33:53,840
Speaker 15: specialized areas.

658
00:33:54,040 --> 00:33:55,480
Speaker 2: And we've got a taste of this.

659
00:33:55,360 --> 00:33:59,240
Speaker 15: In twenty twenty five in some pretty big important categories.

660
00:33:59,480 --> 00:34:00,640
Speaker 2: Think about self driving.

661
00:34:00,880 --> 00:34:03,960
Speaker 15: We now have waymos on the streets of San Francisco

662
00:34:04,280 --> 00:34:06,680
Speaker 15: and any other places and many other places, and those

663
00:34:06,680 --> 00:34:10,319
Speaker 15: are operating ten times safer than the average human driver,

664
00:34:10,480 --> 00:34:15,360
Speaker 15: ten times safer. Also, you see other specialized areas. Anthropic,

665
00:34:15,480 --> 00:34:18,640
Speaker 15: for example, focused on coding and in twenty twenty five

666
00:34:18,719 --> 00:34:22,239
Speaker 15: went mainstream with their cloud code product where developers can

667
00:34:22,320 --> 00:34:25,440
Speaker 15: choose to work with cloud code agents to prototype and

668
00:34:25,480 --> 00:34:28,600
Speaker 15: even put software into production much faster. We're going to

669
00:34:28,600 --> 00:34:30,239
Speaker 15: see a lot more of that in twenty twenty six.

670
00:34:30,520 --> 00:34:34,400
Speaker 15: It's going to be specialized capabilities in many new areas.

671
00:34:34,480 --> 00:34:36,160
Speaker 2: Now, how big are the checks? Then you're going to

672
00:34:36,200 --> 00:34:39,200
Speaker 2: have to write because what weimo Anthropy and even like

673
00:34:39,440 --> 00:34:42,440
Speaker 2: in the legal sector, like a Harvey having common is

674
00:34:42,520 --> 00:34:45,960
Speaker 2: that they are well capitalized at this point. They had

675
00:34:46,000 --> 00:34:49,960
Speaker 2: to commit a lot of capital to train those specialized

676
00:34:49,960 --> 00:34:53,319
Speaker 2: models in the first place and then deploy them absolutely well.

677
00:34:53,400 --> 00:34:56,120
Speaker 15: You mentioned to Harvey, I'm focused on the early stage

678
00:34:56,160 --> 00:34:59,880
Speaker 15: investing and in the case of Harvey, they started really small.

679
00:35:00,040 --> 00:35:03,200
Speaker 15: They basically focused on an area and they said, hey,

680
00:35:03,239 --> 00:35:05,080
Speaker 15: this is an area we're going to be deep experts in.

681
00:35:05,160 --> 00:35:08,000
Speaker 15: That's the legal area, and they focused on the actual

682
00:35:08,080 --> 00:35:12,000
Speaker 15: user obsession. They now have over one thousand customers for

683
00:35:12,160 --> 00:35:14,920
Speaker 15: the legal tech space, and they are kind of a

684
00:35:15,000 --> 00:35:17,680
Speaker 15: right hand person to the lawyer. In fact, one of

685
00:35:17,719 --> 00:35:20,880
Speaker 15: their customers said, I would sooner lose my coffee for

686
00:35:20,960 --> 00:35:23,600
Speaker 15: the year than my Harvey license. My sister's is a lawyer,

687
00:35:23,640 --> 00:35:26,080
Speaker 15: she uses Harvey. She'd probably say the same exact thing.

688
00:35:26,440 --> 00:35:27,960
Speaker 15: Twenty twenty six, We're going to look back at the

689
00:35:28,040 --> 00:35:31,000
Speaker 15: end of the year and realize how many areas in

690
00:35:31,080 --> 00:35:33,080
Speaker 15: AI we just couldn't live without.

691
00:35:33,239 --> 00:35:35,319
Speaker 4: Constantin Where is next?

692
00:35:35,360 --> 00:35:38,080
Speaker 3: Therefore, because you actually already have made these bets in

693
00:35:38,120 --> 00:35:41,400
Speaker 3: these very focused areas and applications of AI.

694
00:35:41,760 --> 00:35:43,880
Speaker 4: We just named Harvey, but you're.

695
00:35:43,680 --> 00:35:45,319
Speaker 3: Also in eleven labs if you're thinking about the way

696
00:35:45,360 --> 00:35:46,600
Speaker 3: in which we're going to interact with it from a

697
00:35:46,680 --> 00:35:51,279
Speaker 3: vocal perspective and create ourselves. But Where's next hasn't been

698
00:35:51,280 --> 00:35:53,520
Speaker 3: disrupted absolutely.

699
00:35:53,560 --> 00:35:56,000
Speaker 15: I'll give two tastes of what's coming next, one in

700
00:35:56,120 --> 00:35:58,760
Speaker 15: the physical world, and then one in the digital world.

701
00:35:59,800 --> 00:36:03,120
Speaker 15: In the physical world, were investors in a company called Vercata.

702
00:36:03,440 --> 00:36:09,400
Speaker 15: They are the leading AI physical security company and they're

703
00:36:09,440 --> 00:36:12,319
Speaker 15: basically an extension to those physical security guards who walk

704
00:36:12,320 --> 00:36:15,600
Speaker 15: around a premise and can now monitor an even larger

705
00:36:15,960 --> 00:36:21,600
Speaker 15: premis for physical security. They help investigations go thirty percent faster,

706
00:36:21,880 --> 00:36:25,839
Speaker 15: dramatically faster. And that sounds like a statistic, but let's make.

707
00:36:25,760 --> 00:36:26,400
Speaker 2: It very real.

708
00:36:26,600 --> 00:36:30,439
Speaker 15: They were working with a major airport that had a

709
00:36:30,480 --> 00:36:33,440
Speaker 15: bomb threat and they were able to help close that

710
00:36:33,560 --> 00:36:39,560
Speaker 15: investigation significantly faster, which means that the airplanes actually boarded, flights,

711
00:36:39,560 --> 00:36:42,120
Speaker 15: got out on time, and passengers got to their destination.

712
00:36:42,160 --> 00:36:44,000
Speaker 2: We're going to see a lot of that now.

713
00:36:44,040 --> 00:36:47,400
Speaker 15: In the digital world. We work with a company called Expo.

714
00:36:47,560 --> 00:36:51,040
Speaker 15: It's a AI penetration tester. They set out to get

715
00:36:51,040 --> 00:36:55,280
Speaker 15: really good at finding vulnerabilities in websites and applications. Within

716
00:36:55,400 --> 00:36:58,960
Speaker 15: six months, they became as good as a human penetration tester,

717
00:36:59,160 --> 00:37:03,720
Speaker 15: a profession at finding vulnerabilities. Within eighteen months, they've actually

718
00:37:03,800 --> 00:37:06,879
Speaker 15: become best in the world. They're top ranked on hacker one,

719
00:37:06,920 --> 00:37:09,920
Speaker 15: which is the global leader board for individual hackers, and

720
00:37:10,000 --> 00:37:14,360
Speaker 15: they're finding major vulnerabilities at companies, reporting those to the companies,

721
00:37:14,560 --> 00:37:16,520
Speaker 15: helping them patch them so that the bad guys don't

722
00:37:16,520 --> 00:37:18,960
Speaker 15: get there. We'll have a lot more capabilities like that

723
00:37:19,000 --> 00:37:19,879
Speaker 15: in twenty twenty six.

724
00:37:20,640 --> 00:37:24,160
Speaker 3: What's interesting is how therefore you're going to build and

725
00:37:24,239 --> 00:37:26,799
Speaker 3: scale at the pace that's necessary. If there's a lot

726
00:37:26,840 --> 00:37:29,719
Speaker 3: of capital looking for these more specialized areas, there are

727
00:37:29,760 --> 00:37:32,719
Speaker 3: people building in it, how do you talk to your

728
00:37:32,719 --> 00:37:34,520
Speaker 3: portfolio companies at this moment being like, you need to

729
00:37:34,520 --> 00:37:36,120
Speaker 3: get that edge, you need to lead the market at

730
00:37:36,120 --> 00:37:38,360
Speaker 3: this moment because there's an opportunity that's moving fast.

731
00:37:39,920 --> 00:37:41,400
Speaker 2: Absolutely right, Caroline.

732
00:37:41,719 --> 00:37:44,759
Speaker 15: And you know, we think about the word courage in

733
00:37:44,800 --> 00:37:46,840
Speaker 15: twenty twenty six. There's been so much focus on the

734
00:37:46,840 --> 00:37:50,920
Speaker 15: frontier four Open AI and Anthropic and Google and Xai.

735
00:37:51,160 --> 00:37:54,200
Speaker 15: They're doing amazing work, and it can be intimidating for

736
00:37:54,239 --> 00:37:56,080
Speaker 15: the early stage founder to say, you know what, I'm

737
00:37:56,080 --> 00:37:58,280
Speaker 15: going to go up and build an amazing big company

738
00:37:58,760 --> 00:38:01,640
Speaker 15: in the presence of these giants. But we encourage founders

739
00:38:01,640 --> 00:38:05,440
Speaker 15: to be courageous in twenty twenty six. They know areas deeply,

740
00:38:05,480 --> 00:38:09,080
Speaker 15: know those areas specialize in that delight your customers, and

741
00:38:09,120 --> 00:38:12,960
Speaker 15: there will be amazing opportunity. For example, in the healthcare space,

742
00:38:13,320 --> 00:38:16,240
Speaker 15: we work with a company called Open Evidence, which helps

743
00:38:16,320 --> 00:38:20,319
Speaker 15: physicians diagnose really complicated problems. In fact, my wife is

744
00:38:20,320 --> 00:38:23,160
Speaker 15: a surgeon. She uses Open Evidence to help diagnose problems.

745
00:38:23,360 --> 00:38:26,160
Speaker 15: She takes that extra time and puts it back into patients.

746
00:38:26,440 --> 00:38:28,319
Speaker 15: That was started by someone who said, you know what,

747
00:38:28,400 --> 00:38:30,960
Speaker 15: the healthcare area is so important that it's going to

748
00:38:31,000 --> 00:38:34,799
Speaker 15: need specialization, it's going to need these specific capabilities. And

749
00:38:34,840 --> 00:38:38,320
Speaker 15: they've been absolutely right. That type of courage will continue

750
00:38:38,360 --> 00:38:38,920
Speaker 15: to pay off.

751
00:38:38,960 --> 00:38:42,080
Speaker 2: In twenty twenty six, I started the week with my

752
00:38:42,200 --> 00:38:45,360
Speaker 2: column about how there's no point using the term seed

753
00:38:45,480 --> 00:38:48,120
Speaker 2: round anymore because some of them are in the hundreds

754
00:38:48,160 --> 00:38:50,680
Speaker 2: of millions of dollars right out the gate with a

755
00:38:50,719 --> 00:38:53,680
Speaker 2: team of a dozen people. That's the domain that you

756
00:38:53,800 --> 00:38:57,000
Speaker 2: oper eight in. But it particularly in the field of AI.

757
00:38:57,600 --> 00:38:59,959
Speaker 2: How much do you expect that trend to keep happen?

758
00:39:00,200 --> 00:39:02,719
Speaker 2: You know, you keep saying I invest early, but you

759
00:39:02,880 --> 00:39:05,080
Speaker 2: know that that actually you're not the only person that's

760
00:39:05,120 --> 00:39:08,799
Speaker 2: looking at ASI. And you know the whole point is

761
00:39:08,840 --> 00:39:12,800
Speaker 2: standing up sometimes a research lab from scratch.

762
00:39:14,040 --> 00:39:16,720
Speaker 15: I loved your article the coconut round, right the coconut

763
00:39:16,800 --> 00:39:19,719
Speaker 15: round or the avocado round or the mango seed round. Yeah, yeah,

764
00:39:19,760 --> 00:39:23,239
Speaker 15: these massive seeds. I'll say, how we think about it? Sure,

765
00:39:23,440 --> 00:39:25,640
Speaker 15: First and foremost, we don't think about the size of

766
00:39:25,640 --> 00:39:28,280
Speaker 15: the seed. We think about the quality of the company.

767
00:39:28,719 --> 00:39:30,799
Speaker 15: So we take a step back and we look at

768
00:39:30,800 --> 00:39:33,200
Speaker 15: an AI business, and first of all, we might say,

769
00:39:33,239 --> 00:39:35,319
Speaker 15: this is an AI business that does X, Y or Z,

770
00:39:35,880 --> 00:39:38,319
Speaker 15: and we'll cover the term AI. We'll put our finger

771
00:39:38,360 --> 00:39:40,120
Speaker 15: over the term AI and say does it still make

772
00:39:40,239 --> 00:39:42,359
Speaker 15: sense as a business even without AI?

773
00:39:42,800 --> 00:39:43,960
Speaker 2: That's test number one.

774
00:39:44,239 --> 00:39:46,799
Speaker 15: And secondly, if it does, then we say, is this

775
00:39:46,840 --> 00:39:49,160
Speaker 15: the kind of business that we want to spend years

776
00:39:49,320 --> 00:39:52,799
Speaker 15: really being company builders for? And once we go through

777
00:39:52,840 --> 00:39:56,239
Speaker 15: those phases, then we look at the financing dynamics and

778
00:39:56,280 --> 00:39:58,759
Speaker 15: the size of the round and we decide, hey, is

779
00:39:58,760 --> 00:40:00,560
Speaker 15: this something that we want to do with that scale.

780
00:40:00,960 --> 00:40:05,000
Speaker 15: I've consistently found that great founders are willing to pick

781
00:40:05,120 --> 00:40:09,040
Speaker 15: the best possible partners and shape rounds that are smart

782
00:40:09,040 --> 00:40:11,320
Speaker 15: for the business in the long term and then attract

783
00:40:11,360 --> 00:40:13,439
Speaker 15: more and more capital in the years to come. That's

784
00:40:13,440 --> 00:40:15,640
Speaker 15: how we've been approaching these sizable seat rounds.

785
00:40:16,080 --> 00:40:17,279
Speaker 4: Constantine come back.

786
00:40:17,360 --> 00:40:20,759
Speaker 3: We always of it Constantine, Buna of Sequoia appreciate it.

787
00:40:21,520 --> 00:40:23,839
Speaker 3: Now we turn our attention to France because the National

788
00:40:23,880 --> 00:40:27,480
Speaker 3: Assembly there has followed in the footsteps of Australia, passing

789
00:40:27,520 --> 00:40:30,120
Speaker 3: a bill last night to ban under fifteen year olds

790
00:40:30,160 --> 00:40:34,160
Speaker 3: from social media. Legislation now heads to France's Senate. The move,

791
00:40:34,200 --> 00:40:37,440
Speaker 3: of course, comes as Meta TikTok YouTube they head to

792
00:40:37,480 --> 00:40:41,080
Speaker 3: court in the United States over allegations that they misled

793
00:40:41,120 --> 00:40:44,480
Speaker 3: the public about the safety of their apps, accusations the

794
00:40:44,520 --> 00:40:45,480
Speaker 3: companies have rejected.

795
00:40:45,960 --> 00:40:52,000
Speaker 2: Ed coming up, there is no one quite like Jensen Wang.

796
00:40:52,360 --> 00:40:56,439
Speaker 2: What does that mean for succession planning at Nvidia. We'll

797
00:40:56,440 --> 00:41:06,440
Speaker 2: have that discussion next. This is Bloomberg Tech. When you

798
00:41:06,480 --> 00:41:09,160
Speaker 2: see the future of AI is resting on the shoulders

799
00:41:09,280 --> 00:41:12,040
Speaker 2: of Nvidia, But the future of the chip maker after

800
00:41:12,080 --> 00:41:16,160
Speaker 2: its current CEO and co founder Jensen Wong departs one day, well,

801
00:41:16,200 --> 00:41:20,719
Speaker 2: that's unclear. Bloomberg's semiconductor reporter in King has written a

802
00:41:20,719 --> 00:41:23,520
Speaker 2: pretty wonderful piece. I mean, Jensen Wong has been at

803
00:41:23,520 --> 00:41:26,840
Speaker 2: the helm of Nvidia for more than three decades. He

804
00:41:27,040 --> 00:41:29,759
Speaker 2: is the longest seven Silicon Valley CEO. There is no

805
00:41:29,920 --> 00:41:32,920
Speaker 2: suggestion that he's wants to pack it in. But what

806
00:41:32,960 --> 00:41:35,080
Speaker 2: you're writing about is nor is there any evidence that

807
00:41:35,160 --> 00:41:38,640
Speaker 2: Nvidia has really done anything in succession either. Yeah.

808
00:41:38,680 --> 00:41:42,280
Speaker 16: I mean, you know, with a company that's become as important,

809
00:41:42,280 --> 00:41:45,200
Speaker 16: it has to a whole industry and arguably the stock

810
00:41:45,239 --> 00:41:48,040
Speaker 16: market and the economy as well. Usually like to have

811
00:41:48,280 --> 00:41:50,600
Speaker 16: a better idea of who the people at the top are,

812
00:41:51,040 --> 00:41:53,960
Speaker 16: and even people like myself who've been looking at this

813
00:41:54,000 --> 00:41:57,239
Speaker 16: company for a very long time, it's him, right. The

814
00:41:57,320 --> 00:41:59,719
Speaker 16: whole company is built around him, and that's all there

815
00:41:59,760 --> 00:42:00,120
Speaker 16: is to it.

816
00:42:00,400 --> 00:42:02,399
Speaker 3: And what's really interesting is you interview people who talk

817
00:42:02,400 --> 00:42:05,440
Speaker 3: about how flat the organization is and alsomate how difficult

818
00:42:05,480 --> 00:42:06,920
Speaker 3: would be to run by.

819
00:42:06,760 --> 00:42:08,200
Speaker 4: Anyone else than Chansten.

820
00:42:08,320 --> 00:42:10,840
Speaker 3: One can he talks to who the other well key

821
00:42:11,480 --> 00:42:14,319
Speaker 3: presidents are, but perhaps and not in line to.

822
00:42:14,280 --> 00:42:15,600
Speaker 4: Take the throne.

823
00:42:15,880 --> 00:42:18,399
Speaker 16: Yeah, I mean, you know, the way to do this

824
00:42:18,560 --> 00:42:21,879
Speaker 16: is to think about things through Jensen's eyes, because he's

825
00:42:22,000 --> 00:42:25,760
Speaker 16: explicit about this. He created an organization where he wants

826
00:42:25,840 --> 00:42:28,400
Speaker 16: to know where he believes the CEO needs to know

827
00:42:28,440 --> 00:42:30,520
Speaker 16: what's going on, and the way to do that is

828
00:42:30,600 --> 00:42:33,719
Speaker 16: to have less of the traditional corporate structure and just

829
00:42:34,120 --> 00:42:37,520
Speaker 16: a large group forty to fifty sixty depends on the

830
00:42:37,600 --> 00:42:39,600
Speaker 16: day as to the number he gives you. Of people

831
00:42:39,640 --> 00:42:43,760
Speaker 16: who don't directly report to him, they have responsibilities.

832
00:42:42,880 --> 00:42:46,200
Speaker 2: But we've spoken to Jensen quite a lot in the

833
00:42:46,280 --> 00:42:49,760
Speaker 2: last few years. There are other people though, like collect Cress.

834
00:42:49,760 --> 00:42:53,480
Speaker 2: The CFO is a highly capable person. But as you

835
00:42:53,600 --> 00:42:56,640
Speaker 2: write in Silicon Valley and Tech, you don't usually hire

836
00:42:56,640 --> 00:42:58,800
Speaker 2: the CEO from the finance department.

837
00:42:58,719 --> 00:43:01,600
Speaker 16: Correct, I mean, you know, has a good reputation on

838
00:43:01,640 --> 00:43:05,000
Speaker 16: Wall Street. She was brought in and she's obviously presided

839
00:43:05,000 --> 00:43:07,600
Speaker 16: over the company when it's been enormously successful. But this

840
00:43:07,680 --> 00:43:10,400
Speaker 16: is a very technical job, and it's also a very

841
00:43:10,480 --> 00:43:13,680
Speaker 16: dynamic job. He's on the one hand a science leader,

842
00:43:13,719 --> 00:43:16,040
Speaker 16: and he's on the other hand an advocate and driving

843
00:43:16,080 --> 00:43:17,600
Speaker 16: the whole industry forward.

844
00:43:18,000 --> 00:43:19,480
Speaker 4: And spends a lot of time on planes.

845
00:43:19,480 --> 00:43:21,360
Speaker 3: It feels like at the age of sixty three, Bloomberg

846
00:43:21,400 --> 00:43:24,720
Speaker 3: zin king, thank you very much, I urge of yours

847
00:43:24,800 --> 00:43:26,920
Speaker 3: to go read that Deep Dive. It's a great piece

848
00:43:27,040 --> 00:43:30,240
Speaker 3: and video's lack clear successor for superstar CEO.

849
00:43:30,480 --> 00:43:33,280
Speaker 4: That does it though for this edition a Bloomberg techech.

850
00:43:34,000 --> 00:43:36,200
Speaker 2: Yeah, there's a lot happening in public markets and in

851
00:43:36,320 --> 00:43:39,760
Speaker 2: private markets, but we are bracing for big tech earnings

852
00:43:39,880 --> 00:43:42,720
Speaker 2: in earnest check out the pods so much to recap

853
00:43:42,920 --> 00:43:46,160
Speaker 2: you know where to find it on iHeart, Spotify, Apple,

854
00:43:46,320 --> 00:43:48,319
Speaker 2: and of course in all the Bloomberg platforms as well.

855
00:43:48,680 --> 00:43:51,319
Speaker 2: Two days into an astonishingly busy week in the world

856
00:43:51,400 --> 00:43:53,560
Speaker 2: of technology. This is Bloomberg Tech