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Speaker 1: From Mahard where Innovation of Money and Power Collie in

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Speaker 1: Silicon Valley, NBN.

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Speaker 2: This is Bloomberg Technology with Caroline Hyde and Ed Ludlow.

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Speaker 3: I'm Caroline Heinde of Bloomberg's World headquarters in New York,

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Speaker 3: and I'm Ed Ludlow in San Francisco.

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Speaker 2: This is Bloomberg Technology coming up.

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Speaker 3: The US clums down on China's chip access with sweeping

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Speaker 3: updates to export controls. What'll discuss the impact on the

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Speaker 3: semiconductor industry.

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Speaker 2: Plus will bring you the latest updates from the trial

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Speaker 2: of Sam Bankman freed as the third member of his

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Speaker 2: inner circle testifies against him.

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Speaker 3: And we'll continue our conversation on the technology ecosystem right here.

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Speaker 1: In the Big Apple.

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Speaker 3: New York Tech Week continues, but first let's check in

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Speaker 3: on these markets and actually tech the laggard of choice

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Speaker 3: at the moment. Today, Ed, we're seeing the Nasdaq one

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Speaker 3: hundred folks down about a tenth percent. Yes, we know

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Speaker 3: that stocks sometimes struggle in the face of rising bond yields. Naturally,

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Speaker 3: we saw some other areas catch a bid bag of

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Speaker 3: America coming out with some earnings that beat although Gold

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Speaker 3: and Sachs as well and worse than had been anticipated

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Speaker 3: in terms of its own profitability targets. I'm looking at

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Speaker 3: a tenure yield pushing up once again to about two

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Speaker 3: thousand and seven highs. So we're anticipating this strong data

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Speaker 3: that we've just seen out of the US, whether, of course,

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Speaker 3: the overall the macro picture looks a little bit better,

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Speaker 3: and what ultimately that means for the Federal Reserve. I think, unfortunately,

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Speaker 3: we've just moved on a gear. We're looking at crane shares.

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Speaker 3: I'm looking at what's happening overall in the tech space.

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Speaker 1: In China.

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Speaker 3: We've got the Belton Road initiative that catch up meetings.

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Speaker 3: They're happening with world leaders, but also China, of course

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Speaker 3: itself trying to stimulate its economy while the US tries

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Speaker 3: to impede some of its technological know how. We're looking

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Speaker 3: in it down some three quarters percent. I know you

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Speaker 3: I'd dig into that one.

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Speaker 4: Ed.

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Speaker 3: Let's look at some of the individual areas of risk

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Speaker 3: assets that we like to focus on the tech though.

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Speaker 3: I want to focus on what's happening in bitcoin because

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Speaker 3: we have had once again a wild ride. Is Larry

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Speaker 3: Fink on the side of bitcoin certainly he sees some

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Speaker 3: sort of move to maybe even a solace, a place

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Speaker 3: of refuge, a area to be seen as safety. That's

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Speaker 3: certainly what seemed to be being talked about by the

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Speaker 3: head of black Rock. And overall we're seeing it just

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Speaker 3: up about a quarter percent as we see flip flopping

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Speaker 3: around that all important twenty eight thousand level.

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Speaker 2: There's a lot in the news cycle that's pushing individuals stocks. Lucid,

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Speaker 2: the ev makers, saw its production drop thirty percent quarter

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Speaker 2: and quarter, really casting doubt about its full year production

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Speaker 2: targets for high endvs. That stock down almost four percent.

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Speaker 2: Apple down six tens to one percent. It's out with

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Speaker 2: a new Apple pencil. Go out onto Apple's website and

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Speaker 2: see the details. Not doing much to support the stock.

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Speaker 2: There is some hangover from that counterpoint research that came

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Speaker 2: out twenty four hours ago showing that early sales of

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Speaker 2: iPhone fifteen in China are not doing as well relative

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Speaker 2: to iPhone fourteen last year, and Amazon down four ten

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Speaker 2: to one percent. Really strong retail sales data here in

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Speaker 2: the US for the month of September not doing much

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Speaker 2: to support e commerce related stocks. The top story in

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Speaker 2: the top mover is in Vidia, a really notable moved

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Speaker 2: downwards after the US confirmed it is expanding export curbs

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Speaker 2: relating to chip technology. That move now three point five percent.

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Speaker 2: It had been at one point seven percent, on track

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Speaker 2: for its biggest drop since early May. That said, you know,

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Speaker 2: despite shedding sixty to seventy billion dollars in market cap,

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Speaker 2: this is to a one point one trillion dollar stock

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Speaker 2: all about the eight hundred and h eight hundred the

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Speaker 2: specific China chips that it was exporting. Let's get the

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Speaker 2: details out of DC with Bloombo's Mackenzie Hawkins and Mackenzie.

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Speaker 2: We knew this was coming, Bloomberg had reported it, but

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Speaker 2: how is this impacting in Vidia specifically?

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Speaker 5: So what we saw today as the Biden administration released

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Speaker 5: updated regulations on these sweeping export controls that they imposed

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Speaker 5: on China last year and in response to last year's curbs,

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Speaker 5: and Vidia designed chips specifically for the Chinese market that

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Speaker 5: went right up to the threshold that the administration set.

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Speaker 5: And now the administration has tightened that threshold to capture

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Speaker 5: the chips that Nvidia designed for China, meaning that they

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Speaker 5: can't sell those chips there without a license, and so

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Speaker 5: their's stock to hit this morning.

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Speaker 3: It wasn't just in video that was being focused on

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Speaker 3: from a business model perspective. McKenzie took us through some

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Speaker 3: of the AI companies that it also being targeted in China.

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Speaker 5: Sure, So, in addition to tightening the threshold for graphics

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Speaker 5: chips like in videos, you also saw the Biden administration

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Speaker 5: add two AI firms that are Chinese AI's startups to

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Speaker 5: the entity list, which basically means overseas companies have to

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Speaker 5: get a license to export and trade with those firms.

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Speaker 5: And you know, one of those companies have said we're

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Speaker 5: going to appeal that decision. We strongly disagree. Chinese Foreign

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Speaker 5: minister said yesterday that you know, we don't want the

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Speaker 5: US to weaponize trade issues, but this is the Biden

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Speaker 5: administration clamping down on what they see as rapid advancement

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Speaker 5: in China's chip industry. And beyond that, we also have

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Speaker 5: to look at the equipment makers because it's not just

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Speaker 5: the actual manufacturer of chips, but also the highly expensive

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Speaker 5: and technical equipment required to make them. And so one

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Speaker 5: of the key players there is Dutch company ASML, and

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Speaker 5: they've said that the restrictions, the new restrictions that we're

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Speaker 5: announced this morning, are going to impact some of their

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Speaker 5: China facilities as well.

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Speaker 2: We're just showing on the screen. Mackenzie SML's response to this,

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Speaker 2: these export control measures will likely have an impact on

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Speaker 2: the regional split of our system sales in the medium

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Speaker 2: to long term. What was interesting about this, The whole

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Speaker 2: point of codifying and updating these curves was to address

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Speaker 2: the loopholes and gray areas from last October. And yet

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Speaker 2: I think I'm right in saying that officials on the

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Speaker 2: US side Mackenzie didn't specifically explain which chip making equipment

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Speaker 2: was going to be caught by the expanded controls.

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Speaker 5: So they released the text of the rules this morning,

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Speaker 5: and you know, companies, industry analysts, trade organizations are rapidly

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Speaker 5: going through that text to identify which specific, which specific

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Speaker 5: pieces of equipment are affected. And so in ASA's case,

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Speaker 5: you'd be looking specifically at less advanced what are called

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Speaker 5: DUV machines, which are lithography machines that actually help you

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Speaker 5: cut wafer cut ships into a semiconductor wafer. And the

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Speaker 5: US has to coordinate with the Netherlands on that policy

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Speaker 5: because ASML is a Dutch company, it's one of the

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Speaker 5: most valuable companies in Europe, and one of the main

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Speaker 5: loopholes of the initial expert controls announced last October was

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Speaker 5: that Washington went ahead, but they hadn't yet gotten Amsterdam

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Speaker 5: and Tokyo on board, where some of the main ship

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Speaker 5: equipment makers are located.

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Speaker 3: A great global perspective, Mackenzie Hawkins, We thank you so

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Speaker 3: much for jumping on that news of day. Meanwhile, no,

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Speaker 3: we're going to stay over in Washington and talk globally

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Speaker 3: as well, because President Biden is set to travel to

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Speaker 3: Israel tomorrow and any moment now, of course, the US

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Speaker 3: House itself will hold a vote on electing a new speaker.

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Speaker 3: It is busy down there, I mean, most Cadie lines

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Speaker 3: is always all across this first and foremost to the

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Speaker 3: President and the anticipated trip at the moment, how are

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Speaker 3: we anticipating this to be sort of taken by the

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Speaker 3: rest of the administration and indeed by the Republicans.

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Speaker 6: Well, of course, this is something that President Biden is

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Speaker 6: doing at the invitation of Israeli Prime Minister Benjamin Netan Yahoo.

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Speaker 6: It's going to be a literal, physical manifestation of the

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Speaker 6: US's support for Israel's show of reel solidarity, and it's

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Speaker 6: a trip that the President is making at great personal risk.

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Speaker 6: He is heading into an active war zone. But there's

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Speaker 6: a number of things that he is going to be

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Speaker 6: trying to achieve in addition to showing support for Israel

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Speaker 6: and talking with the Israelis Berendaman Prime Minister and Benjamin Netanyak,

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Speaker 6: the Prime Minister, and other leaders about what it is

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Speaker 6: they need in terms of aid. He also goes there

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Speaker 6: with the knowledge that there is several Americans that are

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Speaker 6: understood to be hostages of Hamas. He would like to

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Speaker 6: see them rescued as we are on the cusp it

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Speaker 6: seems of an Israeli ground invasion in Gaza, and also

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Speaker 6: likely is going to be bringing with him a message

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Speaker 6: of restraint concern for the innocent Palestinian civilians in Gaza,

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Speaker 6: making sure that while the US says Israel does have

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Speaker 6: a right to go after Hamas, that they are taking

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Speaker 6: every measure they can to protect civilian and innocent lives.

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Speaker 6: And then of course there is just kind of the

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Speaker 6: broader deterrent effect of him being there. They do not

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Speaker 6: want this crisis to expand beyond just Israel and Gaza.

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Speaker 6: It as a warning to other countries like Iran, for example,

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Speaker 6: other groups like Hesbelah not to widen this conflict any further.

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Speaker 6: And that's also why we're seeing the President traveling to

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Speaker 6: Jordan after he is in Israel to meet with the

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Speaker 6: leaders of Egypt and the Palestinian authority, in addition to

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Speaker 6: King Abdullah.

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Speaker 2: The administration's attentions on the Middle East, Kayley, but also

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Speaker 2: at home, we have this House vote on the speakership.

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Speaker 2: What are we expecting to happen imminently, Well.

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Speaker 6: It is literally going to take place any minute. The

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Speaker 6: House convened at noon, and we're going to see if

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Speaker 6: Jim Jordan has the numbers. He of course is the

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Speaker 6: speaker designate of the Republican Conference, but when he was

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Speaker 6: given that on Friday and we're seeing what's happening here

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Speaker 6: in the House underway, it's just not clear that he

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Speaker 6: is going to have the votes that he needs. Two

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Speaker 6: hundred and seventeen is the magic number. He can only

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Speaker 6: afford to lose four votes. There were more than fifty

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Speaker 6: who on Friday suggested they would not vote for him

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Speaker 6: on the floor, But he's been whittling away at those

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Speaker 6: numbers over time. He had a number of key flips,

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Speaker 6: the likes of Mike Rogers, Ken Calvert and Wagner, all

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Speaker 6: of these kind of defense appropriations hawks that he was

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Speaker 6: able to bring onto his side. But there's still a

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Speaker 6: handful of Republicans Carlos Semenez, Mike Lawler, Mike Kelly, Mario

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Speaker 6: Diez Blart who still have said that they will vote

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Speaker 6: know for him. So it's going to be a matter

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Speaker 6: of whether he can actually get there on the first ballot,

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Speaker 6: and if not, if he can do it on any ballot,

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Speaker 6: he's going to have to try to bring more people

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Speaker 6: onto his side, knowing of course that we are working

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Speaker 6: with a number of clocks here ISRAELIID the need to

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Speaker 6: give funding to Israel with congressional approval on the one hand,

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Speaker 6: but also trying to avoid a government shutdown come November

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Speaker 6: seventeenth on the other.

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Speaker 3: And I think to that point you sort of shift

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Speaker 3: the conversation back from the imminency of this vote on

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Speaker 3: the House and also what that does mean for the

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Speaker 3: current direction of travel with Israel at the moment. Just

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Speaker 3: take us to what we know in terms of the

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Speaker 3: latest to thinking, certainly from Anthony Blinkn as well.

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Speaker 2: Well.

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Speaker 6: Obviously there is bipartisan support Caroline for giving Israel what

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Speaker 6: it needs and for Congress really passing that aid if

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Speaker 6: it needs to, Knowing there is existing authorities that the

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Speaker 6: Biden administration already has money that has already been appropriated

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Speaker 6: resources they can give to Israel without congressional approval. But

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Speaker 6: if there is something that requires congressional approval, like supplemental

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Speaker 6: funding request, that's where it's going to get tricky if

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Speaker 6: we still have no Speaker of the House. And keep

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Speaker 6: in mind that it's not just Israel funding. The administration

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Speaker 6: is pushing for and trying to secure its others as well,

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Speaker 6: including funding for Ukraine, which is a much more difficult

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Speaker 6: topic among Republicans, specifically in the House of Representatives. And

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Speaker 6: there's been growing talks here in Washington about the idea

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Speaker 6: that Israel and Ukraine funding could be tied together. But

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Speaker 6: that is something that Jim Jordan, if he does indeed

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Speaker 6: get the speaker's gavel, could have a hard time getting

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Speaker 6: through the House, knowing there are so many members of

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Speaker 6: his party that are opposed to any additional funding going

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Speaker 6: to Ukraine. So it's going to be a thorny subject

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Speaker 6: to navigate. If Ukraine and Israel do get lumped together

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Speaker 6: even though that is that support there for Israel.

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Speaker 3: Kayleie lyons, thank you across all of the moving parts

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Speaker 3: that are currently occurring in Washington.

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Speaker 1: And I mean we've been talking about.

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Speaker 3: Israel, of course from the politics, from the conflict, but

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Speaker 3: at the moment also the implications within technology. And actually

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Speaker 3: there's a notable news out that we understand Israel as

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Speaker 3: and talks to Elon Musk SpaceX right to set up

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Speaker 3: Starlink satellite network to Bossal Communications.

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Speaker 2: Yeah, this is an announcement from Israel's communications ministry. It's

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Speaker 2: important to know if you go on the starlink website

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Speaker 2: and look at the map of coverage, Starlink is not

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Speaker 2: currently available in Israel or indeed in the Gaza Strip

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Speaker 2: or the West Bank. We have not heard from SpaceX

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Speaker 2: or received comment from them on this story, but the

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Speaker 2: idea that the israelis a routelining is it will keep

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Speaker 2: those towns on the front line with a reliable Internet

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Speaker 2: connection as this war with her mass continues. The other

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Speaker 2: story that we're continuing to follow related to the Israel

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Speaker 2: mass war, Why Combinators, Gary tan Sequoia Capital's Ravi Gutter

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Speaker 2: and several other prominent bench capitalists canceled plans to attend

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Speaker 2: Web Summit, the biggest technology conference in Europe, and it

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Speaker 2: follows comments by the conference's CEO that slammed Western support

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Speaker 2: for Israel after the Hams attacks and Caroline important to

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Speaker 2: note that this morning Paddy Cosgrave, the CEO of Web Summit,

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Speaker 2: through a blog post and issued an apology for those

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Speaker 2: original comments that he'd made. I think on X.

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Speaker 3: Yeah, he certainly didn't walk back from some of his

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Speaker 3: initial viewpoints, and I think it was notable that they

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Speaker 3: do say that what some vcs have stepped back also

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Speaker 3: some areas the European venture capitalists as well from attending

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Speaker 3: the event. But I think actually Web Summit came out

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Speaker 3: and said actually Monday had a lot of people signing

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Speaker 3: up to attend the event, the busiest Monday that they'd

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Speaker 3: had in terms of attendance registrations, and indeed some vcs

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Speaker 3: had signed up to attend as well. But overall this

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Speaker 3: really does just show that people having to navigate really

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Speaker 3: how they communicate with indeed their own customer base, how

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Speaker 3: they communicate with the broader world on X at the moment,

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Speaker 3: as Indy, Paddy Cosgrove himself as having to.

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Speaker 2: Do Yeah, I think he posted onto that platform Max

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Speaker 2: saying he's going to be taking a time out from

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Speaker 2: the platform where he'd originally made his views known.

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Speaker 3: Nishad Singh, now he's the former director of engineering at FTX,

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Speaker 3: is facing cross examination at the Sam Bangun Freed trial today.

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Speaker 3: Over the course of earlier questioning, Singh said that he

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Speaker 3: was intimidated by Bangland freed and at times humiliated by him.

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Speaker 3: Let's bring in Hannah Miller for more on really the

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Speaker 3: way in which these testimonies are unfolding, and at the

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Speaker 3: moment it really feels as this was pretty rocky relationships.

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Speaker 3: Certainly towards the end of ftx's well fallout, it would

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Speaker 3: have seen.

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Speaker 5: Yeah, we're getting an inside look at what happened in

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Speaker 5: FTX during the collapse, both in the offices and in

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Speaker 5: the thirty million dollar penthouse that Sam bankman Fried shared

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Speaker 5: with his close friends and executives.

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Speaker 2: Kind Of one interesting piece, particularly from the sort of

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Speaker 2: the prosecution standpoint, is what Nishad Singh is saying about

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Speaker 2: when he learned about the financial difficulties that FTX was in.

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Speaker 2: What do we learn in the courtroom.

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Speaker 5: We know that it was an extremely stressful situation for him,

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Speaker 5: that this was really devastating. We know, did he made

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Speaker 5: a plead deal pretty early on? He did flip early

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Speaker 5: on Bankman Freed. So we also know that he had

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Speaker 5: a close personal relationship with Sam Bakman, Fried's younger brother.

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Speaker 5: You know, this was more than professional, This was a

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Speaker 5: personal connection.

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Speaker 2: Between the two. What's interesting to me is the timing

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Speaker 2: of this that in his Testame Singh says he only

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Speaker 2: learned about the eight billion dollar hole in the company's

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Speaker 2: balance sheet two months before everything fell apart. Where are

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Speaker 2: we at in this trial? You know, it's hard as

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Speaker 2: a reporter. I've been in those courtrooms, I know to

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Speaker 2: kind of weigh the evidence. But are we near the

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Speaker 2: end of the process, at least of what we expect

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Speaker 2: to come. Yeah.

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Speaker 5: So our latest updated estimate for the verdict is around

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Speaker 5: November eighth, So again, this is an evolving situation.

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Speaker 1: Things can change.

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Speaker 7: You know.

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Speaker 5: We do have that potential witness list, but that could

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Speaker 5: be adjusted. There are still many colorful characters and people

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Speaker 5: close to Sam Bankman Freed who are set to testify.

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Speaker 3: And I think what we're also getting is a story

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Speaker 3: of it seems as though whether the prosecution is trying

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Speaker 3: to identify so called flashiness excess done by Sam Magmunfried,

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Speaker 3: and it feels as though perhaps we're hearing from seeing

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Speaker 3: some corroboration of that. But he's saying that Sam Mamunfried's

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Speaker 3: approached to spending on investments in real estate and celebrity

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Speaker 3: endorsements was excessive. But also just the fact that they

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Speaker 3: were kind of left out of the loop on many

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Speaker 3: of these deals until after the fact.

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Speaker 5: Yeah, So a lot of what the prosecution has been

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Speaker 5: doing has been showing, you know, the luxe lifestyle that

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Speaker 5: Sam Bankman Freed and the other FTX executives pursued. Meanwhile,

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Speaker 5: the defense has tried arguing that, you know, Sam Bankman

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Speaker 5: Freed was your regular math nerd, that he didn't like

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Speaker 5: this life of luxury. But really we've seen with Singh's

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Speaker 5: testament about living in this thirty million dollar penthouse in

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Speaker 5: the Bahamas, that really all of these executives got to

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Speaker 5: enjoy a life of riches.

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Speaker 2: All right, Blue most Hella Miller terrific up to the

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Speaker 2: minute reporting here in SF. Thank you very much. Just

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Speaker 2: keep the conversation going with Sandra Rowe see EO of

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Speaker 2: the Global Blockchain Business Council, a Swiss based nonprofit with

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Speaker 2: more than five hundred institutional members. And essentially you're dedicated

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Speaker 2: to furthering adoption of blockchain technology, which this trial kind

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Speaker 2: of puts a macro spotlight on. It's kind of an

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Speaker 2: interesting real time play on the rule of law. Right

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Speaker 2: we are seeing that happen in this country. As you

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Speaker 2: sit there representing your industry, what do you think the

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Speaker 2: outcome will mean for your industry?

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Speaker 7: So is fraud and the trial underscores the importance of

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Speaker 7: enforcement being able to do its job to read out

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Speaker 7: financial crimes. And as the adult meant, if it's proven

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Speaker 7: that in this trial that financial crimes have been permitted,

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Speaker 7: the US is based on rule of law and that

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Speaker 7: is a good thing and we will see the outcome

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Speaker 7: of that shortly, it seems. And for the industry, I

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Speaker 7: will say this, less hype, less noise, less bad actors,

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Speaker 7: the better for the good innovators and those who are

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Speaker 7: trying to do the right thing, which includes responsible innovation

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Speaker 7: and consumer protection going hand in hand.

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Speaker 3: Talking of noise, though, there was a bit of noise

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Speaker 3: surrounding well. Future sign offs of spot ETFs yesterday made

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Speaker 3: for a little bit of volatility in the og of

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Speaker 3: the crypto world that is bitcoin, because there was some

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Speaker 3: expectation that the SEC might sign off on black rocks

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Speaker 3: etf proposal, and of course that was dumped down by

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Speaker 3: the SEC itself saying, you know, don't believe everything on

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Speaker 3: the internet, Sondra, how much are you navigating this current

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Speaker 3: noise and expectation in the market.

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Speaker 7: So with the organization that we have, which has fortune

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Speaker 7: five hundreds across to layer one blockchains, to crypto firms,

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Speaker 7: to startups, we have to navigate a world where we

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Speaker 7: focus on what is the problem people are solving for,

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Speaker 7: how is this technology actually useful for society, and frankly,

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Speaker 7: what is the positive impact to society. So for us,

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Speaker 7: it's really about getting down to bread and butter, what

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Speaker 7: real world problems are being solved for and how can

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Speaker 7: these technology tools be used for furthering solutions that are

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Speaker 7: positive impact.

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Speaker 2: Cassandra. In parallel, we have this sort of industry defining

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Speaker 2: trial that will have ramifications for your industry, and we

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Speaker 2: also wait to learn about approval right for products that

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Speaker 2: expand digital asset reach. Give us your sort of state

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Speaker 2: of the industry health check right now when all of

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Speaker 2: you and all of your members gather these positive conversation

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Speaker 2: you're having or are you all down in the doulgens

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Speaker 2: right now about the health of your industry.

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Speaker 7: So as you can imagine, with the group as large

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Speaker 7: as ours, one size does not fit all. The focus

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Speaker 7: is really widening the aperture of discussion from our point

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Speaker 7: of view, which is every industry sector is likely to

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Speaker 7: be affected by things going digital. And in a world

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Speaker 7: where everything is going digital, including money and financial products,

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Speaker 7: what does that mean and what are the implications for

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Speaker 7: each industry sector, whether we're talking about supply chain to

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Speaker 7: digital identity, to wallets and ultimately investing.

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Speaker 3: Do you think ultimately that the amid all the noise,

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Speaker 3: you are able to show real world applications that do

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Speaker 3: problem solve You sit on so many boards. I'm looking

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Speaker 3: high on the World Economic Forums, digital currency governance. You're

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Speaker 3: also on file coins for example. You're doing things within

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Speaker 3: the EU Public funds and new green economy. What problems

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Speaker 3: need to be resonated to be solved here? For basically

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Speaker 3: crypto and decentralized finance to sort of win hearts and

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Speaker 3: minds a little bit more.

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Speaker 7: I think it's getting back to basics. Are you actually

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Speaker 7: helping to solve real world problems. I'll give one example

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Speaker 7: of a project we have going on right now with

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Speaker 7: the UN World Food Program. Billions of dollars of donor

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Speaker 7: funds go into the system across the development world, and

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Speaker 7: there is very little visibility around making sure that there

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Speaker 7: is a three hundred and sixty degree accountability on the

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Speaker 7: fact that wherever it was supposed to go, it actually

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Speaker 7: went to that city or village or community. And I

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Speaker 7: think we need to think about how we design systems

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Speaker 7: to allow for that accountability.

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Speaker 2: It is not about being big brother.

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Speaker 7: There needs to be human rights and consumer protection built

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Speaker 7: into design, but ultimately we need to think about how

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Speaker 7: we affect positive turns and currency bill.

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Speaker 3: Trust Sandra Rowe great to have some time with the

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Speaker 3: CEO of the Global Blockchain Business Council. We thank you

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Speaker 3: so much from New York and San Francisco. This is

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Speaker 3: Blue Meg Technology.

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Speaker 2: All right. Time for talking tech. First up, TSMC is

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Speaker 2: axing plans to build an advanced chip plant in North Taiwan.

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Speaker 2: The pullback comes after reports of growing local protests and

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Speaker 2: Ali Barbera and ten Cent participated in a three hundred

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Speaker 2: million dollars round for ai startup by two on, one

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Speaker 2: of the more prominent startups hoping to compete with the

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Speaker 2: likes of Microsoft and OpenAI. Plus Apple CEO Tim Cook

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Speaker 2: made a special appearance at a ten Cent gaming tournament

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Speaker 2: in China. This comes mid reports of slower than expected

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Speaker 2: sales of the iPhone fifteen and in increased competition from

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Speaker 2: China's Huawei.

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Speaker 3: Caroline Meanwhile, we're going to be talking about well tech,

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Speaker 3: but right here in the city of New York, it's

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Speaker 3: Tech Weeks upon us. We're going to sit down with

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Speaker 3: some of the participants from Everywhere Ventures.

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Speaker 1: That's next watching shares.

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Speaker 3: Meanwhile, of Amazon, Jeff Bezos regains his spot the second

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Speaker 3: richest person in the world, passing lvmhco Bernard. Oh no,

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Speaker 3: of course, we're trading flat on the day. He's now

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Speaker 3: worth one hundred and fifty six billion. This is Bloomberg.

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Speaker 3: Welcome back to Bloomberg Technology. I'm Caroline Head in New York.

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Speaker 2: I med love Loo in San Francisco. Quick check on

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Speaker 2: the markets, because in the last few minutes literally then,

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Speaker 2: as that one hundred has turned positive, up just a

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Speaker 2: tenth of one percent, We've got stronger than expected retail

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Speaker 2: data in the month of September. The logic the market's

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Speaker 2: following is that strong economic data raises bets on the

439
00:22:58,400 --> 00:23:01,200
Speaker 2: FED holding interest rates higher for longer. And we all

440
00:23:01,200 --> 00:23:03,879
Speaker 2: know the story what higher rates mean for the technology

441
00:23:03,920 --> 00:23:06,959
Speaker 2: sector looking at them as that one hundred around seventy

442
00:23:07,040 --> 00:23:09,800
Speaker 2: names in the green, still around thirty in the red.

443
00:23:09,840 --> 00:23:11,920
Speaker 2: We continue to track that. Of course, one big movie

444
00:23:11,960 --> 00:23:14,720
Speaker 2: to the downside is in Vidio after the US expanded

445
00:23:14,800 --> 00:23:19,240
Speaker 2: curbs on CHIT technology exports, and that's specifically impacted in video.

446
00:23:19,480 --> 00:23:22,480
Speaker 2: But names movie to the upside Meta Adobe, Tesla, all

447
00:23:22,480 --> 00:23:25,280
Speaker 2: from a points perspective, moving in as that one hundred higher,

448
00:23:25,280 --> 00:23:26,639
Speaker 2: a lot of FED speak this week, and then we

449
00:23:26,680 --> 00:23:30,120
Speaker 2: get China GDP Wednesday. We've got a lot to think

450
00:23:30,119 --> 00:23:31,080
Speaker 2: about carat we do.

451
00:23:31,320 --> 00:23:33,359
Speaker 3: And actually there's also the micro to think about if

452
00:23:33,359 --> 00:23:34,960
Speaker 3: you're living right here in New York City at the moment,

453
00:23:34,960 --> 00:23:37,800
Speaker 3: because Tech Week's actually upon us bsially underway and the

454
00:23:37,840 --> 00:23:41,240
Speaker 3: industry is gathering for so many hundreds of events and

455
00:23:41,320 --> 00:23:43,919
Speaker 3: panels all week long. To kick off this event, we

456
00:23:43,960 --> 00:23:46,000
Speaker 3: sat down with members of A sixteen Z to hear

457
00:23:46,040 --> 00:23:49,639
Speaker 3: about well why Andrewsen and Horowitz in New York remains

458
00:23:49,680 --> 00:23:50,600
Speaker 3: an important tech hub.

459
00:23:52,840 --> 00:23:56,119
Speaker 8: I've always believed that opportunities live between fields of expertise,

460
00:23:56,400 --> 00:23:59,200
Speaker 8: and I really enjoy exploring those intersections. And I think

461
00:23:59,560 --> 00:24:01,639
Speaker 8: it really is a metaphor for New York City because

462
00:24:01,680 --> 00:24:05,080
Speaker 8: technology has a tendency of cunning across industries. And I

463
00:24:05,119 --> 00:24:07,280
Speaker 8: think the companies that really represent New York best or

464
00:24:07,359 --> 00:24:11,159
Speaker 8: those that really live at the intersection between technology and

465
00:24:11,280 --> 00:24:13,920
Speaker 8: many of the large incomeenty industries that exist here in

466
00:24:13,920 --> 00:24:17,720
Speaker 8: New York. Whether that's media, advertising, fashion, or financial services.

467
00:24:19,280 --> 00:24:20,000
Speaker 1: Let's get more.

468
00:24:19,920 --> 00:24:23,760
Speaker 3: Thoughts from the New York tech scene and ecosystem involve itself.

469
00:24:23,880 --> 00:24:26,560
Speaker 3: Jenny Fielding's here with us managing partner Everywhere Ventures. And

470
00:24:26,600 --> 00:24:30,080
Speaker 3: what's so fascinating is your whole mo of Everywhere Ventures

471
00:24:30,119 --> 00:24:32,879
Speaker 3: is that technology is everywhere, founders are everywhere. But you

472
00:24:32,920 --> 00:24:35,479
Speaker 3: have based yourself here in New York and you've been

473
00:24:35,520 --> 00:24:38,200
Speaker 3: growing tech businesses. It's two thousand and seven here. How

474
00:24:38,240 --> 00:24:39,800
Speaker 3: has it changed from your perspective?

475
00:24:40,040 --> 00:24:42,720
Speaker 9: Yeah, well, I'm a born and raised New Yorker and

476
00:24:42,800 --> 00:24:44,640
Speaker 9: so when I set out to start my first tech

477
00:24:44,640 --> 00:24:47,280
Speaker 9: company in two thousand and seven, everyone said to me,

478
00:24:47,400 --> 00:24:51,120
Speaker 9: this is a terrible place to start a software company.

479
00:24:51,240 --> 00:24:54,399
Speaker 9: And I looked around and I said, really, there's incredible

480
00:24:54,440 --> 00:24:56,840
Speaker 9: talent here. We have some of the best engineering schools.

481
00:24:57,080 --> 00:24:57,800
Speaker 1: We have capital.

482
00:24:57,840 --> 00:25:00,000
Speaker 9: Maybe we don't venture capital, but we have Wall Street,

483
00:25:00,119 --> 00:25:03,440
Speaker 9: we have real estate, we have every multinational is here.

484
00:25:03,560 --> 00:25:05,879
Speaker 9: And so I dug in my keels and I built

485
00:25:05,880 --> 00:25:09,480
Speaker 9: my company here while everyone really was heading out west. Now,

486
00:25:09,520 --> 00:25:12,360
Speaker 9: it's taken a long time for our ecosystem to develop,

487
00:25:12,400 --> 00:25:15,920
Speaker 9: but it really is such a thriving ecosystem. But it's

488
00:25:15,920 --> 00:25:18,200
Speaker 9: taken time from two thousand and seven to now more

489
00:25:18,240 --> 00:25:20,320
Speaker 9: than fifteen years to get where we are.

490
00:25:20,480 --> 00:25:21,080
Speaker 1: It is now.

491
00:25:21,119 --> 00:25:24,200
Speaker 3: I think in terms of number of venture capital deals

492
00:25:24,240 --> 00:25:27,720
Speaker 3: being signed, it's like second, just behind San Francisco and

493
00:25:27,800 --> 00:25:28,960
Speaker 3: the Bay Area.

494
00:25:29,440 --> 00:25:31,160
Speaker 1: What has been sort of a real catalyst.

495
00:25:31,200 --> 00:25:33,760
Speaker 3: We know that there has been the data dogs, the MNGO, DB's,

496
00:25:33,840 --> 00:25:37,240
Speaker 3: the exits that we put money back into New York

497
00:25:37,280 --> 00:25:38,040
Speaker 3: where they were grown.

498
00:25:38,160 --> 00:25:40,520
Speaker 1: Has that particularly helped or has that carved too much

499
00:25:40,520 --> 00:25:42,400
Speaker 1: of a niche in data in particular?

500
00:25:42,640 --> 00:25:44,880
Speaker 9: Yeah, I mean it's been really amazing to see how

501
00:25:44,920 --> 00:25:49,840
Speaker 9: the IPOs have catalyzed our ecosystem. So, for example, those founders,

502
00:25:50,160 --> 00:25:52,520
Speaker 9: they make a bunch of money, and not just the founders.

503
00:25:52,560 --> 00:25:55,400
Speaker 9: Think about the founding teams and what do they do. Sure,

504
00:25:55,520 --> 00:25:57,359
Speaker 9: maybe they buy a nice house, but they put it

505
00:25:57,480 --> 00:26:00,000
Speaker 9: right back into the startup ecosystem. We see that every day.

506
00:26:00,600 --> 00:26:03,199
Speaker 9: What's interesting about our fund is we raise all of

507
00:26:03,240 --> 00:26:06,760
Speaker 9: our capital from LPs, who are all founders and operators.

508
00:26:06,760 --> 00:26:10,280
Speaker 9: So while most people are investing or raising from institutions,

509
00:26:10,400 --> 00:26:13,680
Speaker 9: we're raising from our community. And so that's a real

510
00:26:13,840 --> 00:26:15,879
Speaker 9: kind of new ethos here. We've seen it in the

511
00:26:15,880 --> 00:26:18,879
Speaker 9: Bay Area for many generations, and now it's really starting

512
00:26:18,920 --> 00:26:21,720
Speaker 9: to come here. We call it this kind of founder flywheel.

513
00:26:23,040 --> 00:26:26,199
Speaker 2: Jenny, what's the New York City found a playbook? You know?

514
00:26:26,240 --> 00:26:29,360
Speaker 2: The story in Silicon Valley in San Francisco is you've

515
00:26:29,359 --> 00:26:31,800
Speaker 2: gone to Stanford or Berkeley, you may drop out that

516
00:26:31,840 --> 00:26:34,760
Speaker 2: you can find yourself a garage or a space, get

517
00:26:34,800 --> 00:26:39,159
Speaker 2: capital from vcs here, and grow quite quickly. Explain to

518
00:26:39,160 --> 00:26:40,840
Speaker 2: me what's happening in real terms on the ground in

519
00:26:40,880 --> 00:26:42,760
Speaker 2: New York City, in the wider New York area.

520
00:26:43,119 --> 00:26:43,359
Speaker 1: Yeah.

521
00:26:43,400 --> 00:26:46,440
Speaker 9: Well, again, I really want to stress this word ecosystem.

522
00:26:46,520 --> 00:26:49,240
Speaker 9: So it's not just about what the venture capitalists are doing,

523
00:26:49,280 --> 00:26:51,960
Speaker 9: but what about the University. So I am an adjunct

524
00:26:52,000 --> 00:26:55,840
Speaker 9: professor at both Cornell Tech and Columbia University, who have

525
00:26:56,000 --> 00:27:00,399
Speaker 9: incredible programs that are supporting entrepreneurship, that are incura uraging

526
00:27:00,440 --> 00:27:03,960
Speaker 9: students to not just go to the traditional places. When

527
00:27:04,000 --> 00:27:06,800
Speaker 9: I was a student, everyone went to Goldman and JP

528
00:27:06,920 --> 00:27:11,640
Speaker 9: Morgan and McKinsey. Now we're encouraging students to come out

529
00:27:11,680 --> 00:27:14,520
Speaker 9: and start companies. It's a very different culture here in

530
00:27:14,560 --> 00:27:16,840
Speaker 9: New York than it was when I started, and it's

531
00:27:17,000 --> 00:27:19,720
Speaker 9: quite exciting, is.

532
00:27:19,720 --> 00:27:22,560
Speaker 2: What we're seeing happen in AI here on the West

533
00:27:22,600 --> 00:27:25,679
Speaker 2: Coast happening in New York. There are companies being founded

534
00:27:25,720 --> 00:27:29,360
Speaker 2: in this city every day. The pitch book data shows

535
00:27:29,920 --> 00:27:33,240
Speaker 2: fifty percent of the capital going to San Francisco based startups.

536
00:27:33,680 --> 00:27:37,480
Speaker 2: But is there still some energy being created by AI

537
00:27:37,600 --> 00:27:38,200
Speaker 2: in New York.

538
00:27:38,880 --> 00:27:41,919
Speaker 9: Listen again, getting back to universities, we have incredible labs

539
00:27:41,920 --> 00:27:44,639
Speaker 9: here across our universities and that's spawning some of the

540
00:27:44,640 --> 00:27:49,160
Speaker 9: best technologists, up and coming technologists. I just hosted a

541
00:27:49,200 --> 00:27:52,720
Speaker 9: pre seed founder breakfast with AWS and I would say

542
00:27:52,760 --> 00:27:55,800
Speaker 9: seventy five percent of the founders there pitched me an

543
00:27:55,800 --> 00:27:59,560
Speaker 9: AI startup or AI powered So it is happening here.

544
00:27:59,760 --> 00:28:00,000
Speaker 1: Now.

545
00:28:00,080 --> 00:28:02,320
Speaker 9: It is true that some of the you know, larger

546
00:28:02,359 --> 00:28:06,080
Speaker 9: infrastructure plays, whether it's Open AI or Microsoft or Google

547
00:28:06,160 --> 00:28:08,280
Speaker 9: or on the West Coast. But I think we have

548
00:28:08,320 --> 00:28:09,760
Speaker 9: a real opportunity to catch up.

549
00:28:10,240 --> 00:28:14,600
Speaker 3: What's the state, what's the city doing to help perpetuate

550
00:28:14,640 --> 00:28:16,760
Speaker 3: this because some would say, oh, New York's actually pushing

551
00:28:16,800 --> 00:28:20,040
Speaker 3: back against Airbnb, it's looking at regulating AI at least

552
00:28:20,080 --> 00:28:22,400
Speaker 3: in the application of jobs and hiring.

553
00:28:22,760 --> 00:28:25,160
Speaker 1: How do they managed to do that balancing act? Yeah,

554
00:28:25,200 --> 00:28:26,439
Speaker 1: so it's a great question.

555
00:28:27,119 --> 00:28:30,520
Speaker 9: I happen to chair the advisory board of New York Ventures,

556
00:28:30,560 --> 00:28:32,639
Speaker 9: so that is the venture fund for the state of

557
00:28:32,680 --> 00:28:35,320
Speaker 9: New York, and they have just announced one hundred million

558
00:28:35,400 --> 00:28:38,239
Speaker 9: dollar fund to invest in emerging managers. So these are

559
00:28:38,320 --> 00:28:41,280
Speaker 9: new managers who are out there supporting the next generation

560
00:28:41,360 --> 00:28:44,880
Speaker 9: of entrepreneurs. And so they're putting money into these new

561
00:28:44,960 --> 00:28:48,960
Speaker 9: innovators who are then again investing in companies in New York.

562
00:28:49,120 --> 00:28:52,080
Speaker 9: So I think the state is really across the state,

563
00:28:53,080 --> 00:28:55,560
Speaker 9: you know, making a big impact. I just came from

564
00:28:55,720 --> 00:28:59,480
Speaker 9: a competition called forty three North up in Buffalo where

565
00:28:59,520 --> 00:29:03,360
Speaker 9: they just gave about five million dollars to five companies

566
00:29:03,360 --> 00:29:06,440
Speaker 9: that are moving to Buffalo starting their new company. It's

567
00:29:06,440 --> 00:29:10,160
Speaker 9: many actually in AI. So we're excited to see all

568
00:29:10,240 --> 00:29:12,800
Speaker 9: of the catalyzing across the state.

569
00:29:13,040 --> 00:29:14,400
Speaker 1: Yeah, so it is a state element.

570
00:29:14,440 --> 00:29:17,480
Speaker 3: What's interesting Tech NYC who's sort of helping Galvanize this

571
00:29:17,560 --> 00:29:20,560
Speaker 3: week alongside Andrews and Horowitz, and then they've got some

572
00:29:20,600 --> 00:29:23,160
Speaker 3: interesting data when it comes to the breakdown of founders.

573
00:29:23,560 --> 00:29:25,240
Speaker 1: I'm interested whether or not it's anecdotal.

574
00:29:25,240 --> 00:29:26,920
Speaker 3: It seems to be from the data Tech NYC is

575
00:29:26,960 --> 00:29:29,800
Speaker 3: showing it's actually has happen to be more diverse here

576
00:29:29,800 --> 00:29:32,520
Speaker 3: in New York. That's, of course a reflection of what

577
00:29:32,600 --> 00:29:34,720
Speaker 3: the city looks like the people it makes up, but

578
00:29:35,040 --> 00:29:35,880
Speaker 3: is it diverse enough?

579
00:29:35,960 --> 00:29:37,600
Speaker 1: You seeing improvements in that respect.

580
00:29:38,160 --> 00:29:41,040
Speaker 9: I'm hosting a female founder lunch on Friday. We had

581
00:29:41,120 --> 00:29:45,280
Speaker 9: one thousand women apply. Unfortunately we have fifty spots for lunch,

582
00:29:45,440 --> 00:29:48,000
Speaker 9: but it is absolutely incredible. You know what we're seeing

583
00:29:48,040 --> 00:29:51,680
Speaker 9: here in New York. We're seeing incredible diversity across all,

584
00:29:52,000 --> 00:29:54,080
Speaker 9: you know, walks of life, and we're really excited about it.

585
00:29:54,120 --> 00:29:55,520
Speaker 1: I don't think it's just talk.

586
00:29:55,720 --> 00:29:58,120
Speaker 9: I think you know, women are coming out of incredible

587
00:29:58,840 --> 00:30:03,280
Speaker 9: universities and company and you know there's capital there for them.

588
00:30:03,880 --> 00:30:07,200
Speaker 2: Jenny, what your industry colleagues at Indries and Horroritz outlined

589
00:30:07,200 --> 00:30:10,200
Speaker 2: for us on yesterday's show was New York being good

590
00:30:10,240 --> 00:30:15,400
Speaker 2: at applying technology to mature industries like finance, in other words, fintech,

591
00:30:15,720 --> 00:30:19,360
Speaker 2: but also biotech. Are there any examples where you've experienced

592
00:30:19,400 --> 00:30:23,000
Speaker 2: that technology offering a solution for a legacy or long

593
00:30:23,040 --> 00:30:24,000
Speaker 2: standing industry.

594
00:30:24,520 --> 00:30:27,400
Speaker 9: Yeah, I mean we're those are two of our large areas,

595
00:30:27,920 --> 00:30:30,960
Speaker 9: both fintech healthcare. I think the other one that we're

596
00:30:31,000 --> 00:30:33,760
Speaker 9: focused on is future of work and automation. And so

597
00:30:34,040 --> 00:30:36,600
Speaker 9: oftentimes this plays out in what we call vertical SaaS.

598
00:30:36,640 --> 00:30:40,320
Speaker 9: So these are antiquated industries, whether it's around supply chain

599
00:30:40,400 --> 00:30:43,880
Speaker 9: and the like, where new technologies AI are coming in

600
00:30:43,960 --> 00:30:47,200
Speaker 9: to make everything more efficient. So the areas again that

601
00:30:47,240 --> 00:30:50,880
Speaker 9: we focus on fintech that you spoke to David about yesterday,

602
00:30:51,160 --> 00:30:55,480
Speaker 9: healthcare and future of work automation, these are critical to

603
00:30:55,600 --> 00:30:58,400
Speaker 9: the city and these are old, antiquated industries that are

604
00:30:58,400 --> 00:30:59,680
Speaker 9: being updated through tech.

605
00:31:00,200 --> 00:31:02,920
Speaker 3: Jenny Fielding of Everywhere Ventures really great to have you

606
00:31:02,960 --> 00:31:04,200
Speaker 3: back on the show. We thank you.

607
00:31:04,200 --> 00:31:06,000
Speaker 1: Go get busy with some of your breakfast.

608
00:31:05,680 --> 00:31:06,000
Speaker 2: And din as.

609
00:31:06,000 --> 00:31:06,800
Speaker 1: It would seem ed.

610
00:31:07,960 --> 00:31:09,880
Speaker 2: Yeah, busy week out in New York City. Coming up

611
00:31:09,880 --> 00:31:12,120
Speaker 2: here on the show, Today's VC Spotlight, we're going to

612
00:31:12,120 --> 00:31:14,640
Speaker 2: talk all things fintech. As we were just discussing the

613
00:31:14,680 --> 00:31:18,000
Speaker 2: CEO of Coterie, Ethan Agowl. Coming up next, this is

614
00:31:18,000 --> 00:31:37,200
Speaker 2: Bloomberg Technology. Today's VC Spotlight, we're going to take a

615
00:31:37,280 --> 00:31:39,800
Speaker 2: look at the Coteri, a fintech company with five hundred

616
00:31:39,800 --> 00:31:44,240
Speaker 2: million dollars assets under management. It helps individual investors manage

617
00:31:44,240 --> 00:31:47,560
Speaker 2: their investments in alternatives like bench capital funds, but also

618
00:31:47,600 --> 00:31:51,040
Speaker 2: private equity more and as of today, they also offer

619
00:31:51,120 --> 00:31:55,120
Speaker 2: performance data, capital care payments, and tax reporting services. CEO

620
00:31:55,600 --> 00:31:58,360
Speaker 2: Ethan Agowell joins us here in San Francisco. That was

621
00:31:58,360 --> 00:32:02,000
Speaker 2: the origin, right, allowing individuals to write small to checks,

622
00:32:02,080 --> 00:32:04,440
Speaker 2: get in on those rounds that you've never been able

623
00:32:04,480 --> 00:32:05,720
Speaker 2: to get in on. Exactly.

624
00:32:05,760 --> 00:32:07,280
Speaker 10: So, if you take a step back, like why do

625
00:32:07,400 --> 00:32:09,360
Speaker 10: we invest in the first place, we have a vision

626
00:32:09,400 --> 00:32:11,520
Speaker 10: for the future. We think the future can be better

627
00:32:11,560 --> 00:32:13,760
Speaker 10: than today. We don't want to say we want to invest.

628
00:32:14,000 --> 00:32:17,120
Speaker 10: We think investors are optimists, savers or pessimists. And so

629
00:32:17,160 --> 00:32:20,320
Speaker 10: what we started to do is say, let's democratize access

630
00:32:20,360 --> 00:32:23,880
Speaker 10: to an asset class that has been previously limited to

631
00:32:24,600 --> 00:32:27,320
Speaker 10: really large pension plans or really large endowments. Let's make

632
00:32:27,360 --> 00:32:30,480
Speaker 10: that available to an average retail investor. That's what we

633
00:32:30,480 --> 00:32:32,560
Speaker 10: started on, that's what we focused on. In the last

634
00:32:32,560 --> 00:32:34,800
Speaker 10: twenty four months, we've seen that proliferate. There's a lot

635
00:32:34,840 --> 00:32:36,800
Speaker 10: of different companies that are offering access.

636
00:32:37,120 --> 00:32:38,200
Speaker 2: What we realized though.

637
00:32:38,120 --> 00:32:40,560
Speaker 10: When we got really deep into it, is that it's

638
00:32:40,600 --> 00:32:44,520
Speaker 10: actually the tooling that is completely broken. So as an

639
00:32:44,520 --> 00:32:48,400
Speaker 10: individual investor, it's basically impossible to manage your capital calls,

640
00:32:48,640 --> 00:32:52,239
Speaker 10: your performance reporting, your tax documents, and if you're an

641
00:32:52,240 --> 00:32:55,600
Speaker 10: individual investor in multiple funds, logging into multiple portals, it's

642
00:32:55,640 --> 00:32:56,720
Speaker 10: an absolute disaster.

643
00:32:57,280 --> 00:33:00,160
Speaker 2: But what does an individual invest to look like? A

644
00:33:00,440 --> 00:33:03,200
Speaker 2: private equity aside which has kind of been hurt by rates,

645
00:33:03,600 --> 00:33:06,160
Speaker 2: everyone's kind of clamoring for the private investor as an

646
00:33:06,280 --> 00:33:09,640
Speaker 2: LP high networth individual. Who are you talking about here,

647
00:33:09,680 --> 00:33:12,240
Speaker 2: the everyday person or the bow we're alienaire? Yeah, we're

648
00:33:12,240 --> 00:33:13,840
Speaker 2: talking about a credit investors and above.

649
00:33:13,880 --> 00:33:15,920
Speaker 10: So the SEC defines that as a million dollars of

650
00:33:15,960 --> 00:33:18,720
Speaker 10: networth or two hundred thousand dollars of income. And what's

651
00:33:18,760 --> 00:33:21,760
Speaker 10: beautiful about this is the demand is coming on both sides.

652
00:33:21,800 --> 00:33:24,760
Speaker 10: So not only are individual investors looking to allocate more

653
00:33:24,760 --> 00:33:28,880
Speaker 10: capital to alternative asset classes, the funds themselves are looking

654
00:33:28,960 --> 00:33:31,880
Speaker 10: for more retail investors. So if you look at KKR,

655
00:33:32,160 --> 00:33:35,200
Speaker 10: day said they expect forty percent of their subsequent capital

656
00:33:35,280 --> 00:33:38,840
Speaker 10: raisers to come from individuals. Same with Carlisle, same with Blackstone,

657
00:33:38,880 --> 00:33:42,239
Speaker 10: same with TPG, and so the funds are looking for

658
00:33:42,320 --> 00:33:44,920
Speaker 10: a match on the retail side. But our view is

659
00:33:44,960 --> 00:33:48,000
Speaker 10: that the products, the tools, the solutions need to be

660
00:33:48,120 --> 00:33:51,360
Speaker 10: dramatically improved in order for retail investors to be able

661
00:33:51,360 --> 00:33:53,840
Speaker 10: to invest in these alternative asset classes.

662
00:33:54,080 --> 00:33:56,600
Speaker 3: So you're talking to individual investors, you're also talking though

663
00:33:56,640 --> 00:33:59,440
Speaker 3: to gps and in the administrators of the funds.

664
00:33:59,480 --> 00:34:01,440
Speaker 1: What do you hear from them? How quickly are they

665
00:34:01,480 --> 00:34:02,200
Speaker 1: onboarding with you?

666
00:34:04,160 --> 00:34:06,520
Speaker 2: So far, very quickly. It's incredible.

667
00:34:06,560 --> 00:34:09,120
Speaker 10: The GPS, you know, the LPs, Like, I'm an LPN

668
00:34:09,160 --> 00:34:11,279
Speaker 10: five different funds, but I have a full time day job.

669
00:34:11,520 --> 00:34:14,680
Speaker 10: People who are gps and funds, they have their entire

670
00:34:14,760 --> 00:34:16,839
Speaker 10: net worth tied up in the carry of their own

671
00:34:16,920 --> 00:34:19,760
Speaker 10: fund and they have no idea what is that fund

672
00:34:19,840 --> 00:34:22,640
Speaker 10: marked at? What are the significant companies, what are the

673
00:34:22,680 --> 00:34:25,000
Speaker 10: marks of those individual companies. And these are people that

674
00:34:25,040 --> 00:34:27,920
Speaker 10: are saving for their you know, kids college tuition in

675
00:34:27,920 --> 00:34:30,719
Speaker 10: the future, but don't know what those portfolios look like.

676
00:34:30,760 --> 00:34:32,400
Speaker 10: And so what we did is we built a product

677
00:34:32,640 --> 00:34:36,759
Speaker 10: that helps GPS, that helps LPs understand what exactly they're

678
00:34:36,800 --> 00:34:39,759
Speaker 10: exposed to, what are their moycs, and helps them look

679
00:34:39,760 --> 00:34:42,520
Speaker 10: at analysis that they have never seen before when they

680
00:34:42,520 --> 00:34:45,200
Speaker 10: were just downloading a PDF for a capital account statement

681
00:34:45,440 --> 00:34:46,680
Speaker 10: from an antiquated portal.

682
00:34:47,440 --> 00:34:50,480
Speaker 3: You have raised money, of course, yourself, not only managing

683
00:34:50,480 --> 00:34:53,680
Speaker 3: the money of others. How is you know your own

684
00:34:53,719 --> 00:34:55,640
Speaker 3: business been going in this what has been a more

685
00:34:55,680 --> 00:34:57,960
Speaker 3: difficult environment. Have you been having to focus on and

686
00:34:58,040 --> 00:35:02,480
Speaker 3: showing that your revenue positive, profitability and focus and indeed

687
00:35:02,480 --> 00:35:03,880
Speaker 3: that you're looking to raise more money.

688
00:35:05,640 --> 00:35:07,359
Speaker 2: We have managed quite well.

689
00:35:07,440 --> 00:35:09,560
Speaker 10: I mean, look, this is my second time around, so

690
00:35:10,239 --> 00:35:12,640
Speaker 10: and we have a team of exceptional founder co founders

691
00:35:12,680 --> 00:35:15,160
Speaker 10: I have and investors, so we have lots of runway.

692
00:35:16,040 --> 00:35:18,440
Speaker 10: You know, the company has been performing very well. My

693
00:35:18,560 --> 00:35:20,360
Speaker 10: view on raising capital is raised as much as you

694
00:35:20,360 --> 00:35:22,480
Speaker 10: can whenever you can, but in the market today it

695
00:35:22,560 --> 00:35:25,759
Speaker 10: just doesn't make sense. So when the market warms up

696
00:35:25,800 --> 00:35:28,000
Speaker 10: a little bit, you know, obviously with a tenure at

697
00:35:28,120 --> 00:35:30,879
Speaker 10: four seven is where are we going to get VC

698
00:35:31,040 --> 00:35:34,080
Speaker 10: dollars from that are not obscenely expensive? Right, so our

699
00:35:34,160 --> 00:35:37,279
Speaker 10: view is perform really well, the market will warm up,

700
00:35:37,360 --> 00:35:40,160
Speaker 10: and then we'll go raise capital opportunistically. You never want

701
00:35:40,160 --> 00:35:41,840
Speaker 10: to raise capital when you need to. You raise it

702
00:35:41,880 --> 00:35:44,239
Speaker 10: when you want to, and right now we neither need

703
00:35:44,280 --> 00:35:45,040
Speaker 10: to nor want to.

704
00:35:46,120 --> 00:35:50,360
Speaker 2: Ethan, what is it the coterie has technologically speaking beyond

705
00:35:50,360 --> 00:35:52,200
Speaker 2: the database? Are you a tech company?

706
00:35:53,200 --> 00:35:57,239
Speaker 10: We are only a tech company. We don't employ advisors.

707
00:35:57,239 --> 00:36:00,600
Speaker 10: For example, we don't employ anybody who is not a

708
00:36:00,640 --> 00:36:06,279
Speaker 10: software engineer. The advisory model in even in fintech, in

709
00:36:06,360 --> 00:36:09,799
Speaker 10: new wealth tech doesn't really work because people are not

710
00:36:09,880 --> 00:36:12,800
Speaker 10: looking for a commission based structure or even an aum

711
00:36:12,880 --> 00:36:14,960
Speaker 10: based structure. Well you'll find with a lot of wealth

712
00:36:14,960 --> 00:36:16,920
Speaker 10: advisors or even some of the larger folks you saw

713
00:36:16,960 --> 00:36:20,200
Speaker 10: Goldman report earnings this morning, what they're saying is, we

714
00:36:20,239 --> 00:36:22,160
Speaker 10: are going to try to get you to give us

715
00:36:22,239 --> 00:36:25,080
Speaker 10: your alternatives as a management so that we can charge

716
00:36:25,080 --> 00:36:27,080
Speaker 10: you fifty BIPs on it. But there's no need to

717
00:36:27,160 --> 00:36:30,000
Speaker 10: charge fifty BIPs on something where you're paying capital calls

718
00:36:30,000 --> 00:36:33,480
Speaker 10: and reporting on PDFs. That's why our payment structure is fixed.

719
00:36:33,600 --> 00:36:35,920
Speaker 10: We charge at fixed hundred dollars per year per fund,

720
00:36:36,200 --> 00:36:38,759
Speaker 10: regardless of how big the structure is. So the way

721
00:36:38,760 --> 00:36:40,920
Speaker 10: that we can do that is by having software. Right,

722
00:36:41,000 --> 00:36:44,200
Speaker 10: if we had people behind us, it would be incredibly

723
00:36:44,200 --> 00:36:46,360
Speaker 10: expensive and there's no way that we could deliver that product.

724
00:36:46,400 --> 00:36:48,799
Speaker 10: The only way we can do that with the significant

725
00:36:48,800 --> 00:36:52,719
Speaker 10: margins that we have is through software like it.

726
00:36:53,080 --> 00:36:55,560
Speaker 3: The coach y CEO talking how much they are indeed

727
00:36:55,560 --> 00:36:56,280
Speaker 3: tech ethan.

728
00:36:56,120 --> 00:36:58,040
Speaker 1: Og, Well, thanks so much for your time today. We

729
00:36:58,120 --> 00:37:04,759
Speaker 1: appreciate it.

730
00:37:06,520 --> 00:37:09,640
Speaker 2: Swedish electric truck company Volta Trucks is planning to file

731
00:37:09,719 --> 00:37:13,400
Speaker 2: for bankruptcy following a breakdown in its supply chain. The

732
00:37:13,480 --> 00:37:16,240
Speaker 2: company said. The decision comes roughly two months after Volta's

733
00:37:16,280 --> 00:37:20,360
Speaker 2: battery supply pro terror failed, causing the truck maker to

734
00:37:20,440 --> 00:37:23,040
Speaker 2: fall short of its production targets, bringing Bloomberg New Energy

735
00:37:23,040 --> 00:37:25,719
Speaker 2: finance analyst Maini Yang for more out of London and

736
00:37:25,840 --> 00:37:30,120
Speaker 2: many simple story supply chain broke down, volter can't go

737
00:37:30,200 --> 00:37:33,840
Speaker 2: into production. How difficult is it in your assessment to

738
00:37:33,960 --> 00:37:36,000
Speaker 2: quickly pivot to a new battery supplier.

739
00:37:38,600 --> 00:37:42,040
Speaker 4: I think it really depends if the company has any

740
00:37:42,239 --> 00:37:47,160
Speaker 4: existing relationships. Of course, a lot is uncertain at the moment.

741
00:37:47,600 --> 00:37:51,000
Speaker 4: I guess. We see that battery costs are a major

742
00:37:51,120 --> 00:37:54,520
Speaker 4: factor in the high upfront cost of electric trucks, which

743
00:37:54,600 --> 00:38:00,480
Speaker 4: is kind of the major factor deterring wider adoption present

744
00:38:00,760 --> 00:38:04,400
Speaker 4: because TCO costs are lower for trucks. But in terms

745
00:38:04,400 --> 00:38:08,960
Speaker 4: of batteries, we kind of see two major segues globally.

746
00:38:09,360 --> 00:38:12,880
Speaker 4: Uh For example, al a lot of the market source

747
00:38:12,920 --> 00:38:17,880
Speaker 4: from Chinese battery makers that typically do cheaper LFP batteries worries.

748
00:38:18,680 --> 00:38:22,000
Speaker 4: Another part of the market sources from Korean battery makers

749
00:38:22,360 --> 00:38:26,480
Speaker 4: doing NCM and NCAA, which is higher in energy density

750
00:38:26,520 --> 00:38:33,680
Speaker 4: but also higher in cost. So previously, Yeah, Volta was

751
00:38:33,719 --> 00:38:38,960
Speaker 4: supplying from Protero, which was sourcing from Samsung in but

752
00:38:39,920 --> 00:38:43,839
Speaker 4: with NCM and NCAA chemistry. But we're seeing more companies

753
00:38:44,200 --> 00:38:48,000
Speaker 4: in the market, for example, gravitate towards LFP in order

754
00:38:48,040 --> 00:38:49,040
Speaker 4: to reduce costs.

755
00:38:49,520 --> 00:38:52,040
Speaker 1: Fascinating supply chain story. We thank you so much.

756
00:38:52,080 --> 00:38:54,560
Speaker 3: Bring the new energy finance analyst Mayni Yang staying late

757
00:38:54,560 --> 00:38:55,200
Speaker 3: for us in London.

758
00:38:55,239 --> 00:38:56,279
Speaker 1: We really appreciate it.

759
00:38:56,520 --> 00:38:57,960
Speaker 3: Maybe we'll get you a bit of a hard pivot,

760
00:38:58,000 --> 00:39:00,200
Speaker 3: but I guess there is certainly AI within EV and

761
00:39:00,239 --> 00:39:02,040
Speaker 3: self driving trucks, So let's do it AI.

762
00:39:02,160 --> 00:39:03,440
Speaker 1: Next BYD's founder.

763
00:39:03,160 --> 00:39:06,600
Speaker 3: Robin Lee declaring his company's large language model was finally

764
00:39:06,680 --> 00:39:09,560
Speaker 3: caught up with open AI's advanced GPT four. In fact,

765
00:39:09,680 --> 00:39:12,040
Speaker 3: he's claiming that the lead in his country's race to

766
00:39:12,080 --> 00:39:15,280
Speaker 3: develop AI, they can rival the United States. Let's bringing

767
00:39:15,280 --> 00:39:18,960
Speaker 3: in now resident expert Rachel Metz for more and what

768
00:39:19,000 --> 00:39:21,600
Speaker 3: sort of data, what proof points, what show and tell

769
00:39:21,800 --> 00:39:23,120
Speaker 3: is what been using to prove this.

770
00:39:24,680 --> 00:39:24,879
Speaker 2: Well?

771
00:39:24,920 --> 00:39:28,239
Speaker 11: They did a presentation live, and that's often a good

772
00:39:28,280 --> 00:39:31,120
Speaker 11: test of these systems, But because they're planning in advance

773
00:39:31,160 --> 00:39:33,239
Speaker 11: what they're going to do in these tests, that can

774
00:39:33,280 --> 00:39:35,359
Speaker 11: make it a little bit hard to tell exactly how

775
00:39:35,400 --> 00:39:39,400
Speaker 11: well it works, right, unless something goes horribly wrong, then

776
00:39:39,600 --> 00:39:41,560
Speaker 11: you would know it's not working well. But one thing

777
00:39:41,560 --> 00:39:44,719
Speaker 11: that I think is super interesting about this is you

778
00:39:44,840 --> 00:39:47,839
Speaker 11: have so many of these large language models and chatbots

779
00:39:48,040 --> 00:39:51,680
Speaker 11: that are trained on so much of the Internet that

780
00:39:51,760 --> 00:39:55,280
Speaker 11: is written in English, and it's really interesting to see

781
00:39:55,560 --> 00:39:59,720
Speaker 11: companies working on models that are trained more and meant

782
00:39:59,719 --> 00:40:03,359
Speaker 11: more for non English speaking markets. So that's something that

783
00:40:03,680 --> 00:40:06,400
Speaker 11: we're starting to see increasingly and I think it'll be

784
00:40:06,480 --> 00:40:09,400
Speaker 11: very interesting to watch and see how people are using

785
00:40:09,440 --> 00:40:12,960
Speaker 11: this and how well they're finding it works for all

786
00:40:13,040 --> 00:40:13,760
Speaker 11: kinds of things.

787
00:40:13,960 --> 00:40:18,280
Speaker 3: How much consumer enthusiasm has there been for these, well,

788
00:40:18,320 --> 00:40:20,880
Speaker 3: in your hand viral chat bots, I mean, there's more

789
00:40:20,920 --> 00:40:23,480
Speaker 3: than one hundred and eighty million or something using chatchbto

790
00:40:23,520 --> 00:40:25,719
Speaker 3: in the US. What are the likes and demands for

791
00:40:25,840 --> 00:40:26,800
Speaker 3: Ernie for example.

792
00:40:28,120 --> 00:40:31,719
Speaker 11: I mean, I think that it's something that people want

793
00:40:31,719 --> 00:40:33,920
Speaker 11: to use for a range of things, and some of

794
00:40:33,960 --> 00:40:35,840
Speaker 11: it kind of reminds me of the early days of

795
00:40:35,960 --> 00:40:38,480
Speaker 11: the app store with the iPhone, for instance, with the

796
00:40:38,480 --> 00:40:42,080
Speaker 11: early days of Android phones and apps, where you're not

797
00:40:42,200 --> 00:40:44,000
Speaker 11: entirely sure what you're going to do with it, but

798
00:40:44,200 --> 00:40:46,920
Speaker 11: you'll probably figure out some interesting things that might not

799
00:40:46,960 --> 00:40:50,080
Speaker 11: have even been what was expected. One of the interesting

800
00:40:50,160 --> 00:40:54,160
Speaker 11: and cool things about putting these onto phones is that

801
00:40:54,360 --> 00:40:57,080
Speaker 11: it encourages people to use them in more context where

802
00:40:57,080 --> 00:41:00,240
Speaker 11: you might not be in front of a computer, like

803
00:41:00,239 --> 00:41:03,360
Speaker 11: like a laptop or even an iPad, like when you're driving,

804
00:41:03,360 --> 00:41:06,000
Speaker 11: for instance, or if you're in the kitchen making some food.

805
00:41:06,400 --> 00:41:08,960
Speaker 2: It's worth noting that BAYD is down significantly in this

806
00:41:09,040 --> 00:41:11,440
Speaker 2: session four percent, but that's largely to do with the

807
00:41:11,480 --> 00:41:16,040
Speaker 2: expanded US chip Technology Export Curves, which ultimately have the

808
00:41:16,040 --> 00:41:20,319
Speaker 2: goal of blocking access to technology related to AI. What

809
00:41:20,440 --> 00:41:23,640
Speaker 2: Lee said was that Ernie is not inferior to GPT

810
00:41:23,880 --> 00:41:27,200
Speaker 2: four from open Ai. Okay, what is it that GPT

811
00:41:27,320 --> 00:41:29,600
Speaker 2: four can do if we're to compare.

812
00:41:29,320 --> 00:41:32,959
Speaker 11: Them, If we're to compare them, I mean, that's part

813
00:41:33,000 --> 00:41:36,560
Speaker 11: of what's really fascinating here is that open ai keeps

814
00:41:36,880 --> 00:41:41,480
Speaker 11: elevating GPT four, or sorry, keeps elevating chat GPT. I mean,

815
00:41:41,480 --> 00:41:45,400
Speaker 11: it's gained capabilities that they had announced previously, but you know,

816
00:41:45,440 --> 00:41:49,080
Speaker 11: they hadn't been laid out initially. Like you can now

817
00:41:49,160 --> 00:41:51,840
Speaker 11: give it an image and say, describe what's in this image.

818
00:41:52,320 --> 00:41:53,480
Speaker 1: Things like that could.

819
00:41:53,280 --> 00:41:55,240
Speaker 11: Be really helpful for a range of uses, from helping

820
00:41:55,280 --> 00:41:59,000
Speaker 11: people with visual disabilities to helping.

821
00:41:58,840 --> 00:42:01,640
Speaker 1: You pick out an outfit. So if they can do

822
00:42:01,680 --> 00:42:02,239
Speaker 1: something like.

823
00:42:02,239 --> 00:42:05,000
Speaker 11: That with Ernie bart, that would be that could be

824
00:42:05,080 --> 00:42:08,000
Speaker 11: potentially useful. What I'm not sure about, though, is there

825
00:42:08,000 --> 00:42:10,359
Speaker 11: are also lots of problems with chat GPT, and it's

826
00:42:10,400 --> 00:42:13,799
Speaker 11: also hard to know when it's telling the truth, so

827
00:42:13,880 --> 00:42:16,200
Speaker 11: to speak, how often it's making things up, So it

828
00:42:16,239 --> 00:42:19,520
Speaker 11: remains to be seen how accurate Ernie Bart is and

829
00:42:19,560 --> 00:42:20,400
Speaker 11: I guess we're just going to.

830
00:42:20,400 --> 00:42:20,799
Speaker 1: Have to wait.

831
00:42:21,480 --> 00:42:24,839
Speaker 2: Yep chat GPT is a wardrobe assistant. Interesting use case

832
00:42:24,840 --> 00:42:28,240
Speaker 2: Bloomboats Rachel Metz, Thank you very much, Carot, No end.

833
00:42:28,160 --> 00:42:31,440
Speaker 1: Of applications, not doing yours yet their ED Meanwhile, that

834
00:42:31,480 --> 00:42:33,480
Speaker 1: does it be? This anitition of Bloomberg Technology.

835
00:42:34,160 --> 00:42:36,160
Speaker 2: Don't forget to check out the podcast. Thank you for

836
00:42:36,200 --> 00:42:38,160
Speaker 2: listening to the podcast those of you that tuneame. We're

837
00:42:38,200 --> 00:42:42,400
Speaker 2: on Apple, Spotify, and also of course all the Bloomberg platforms.

838
00:42:42,440 --> 00:42:44,399
Speaker 2: Also check out the show on YouTube. Watch it back.

839
00:42:44,680 --> 00:42:46,600
Speaker 2: A lot of information in there from What's a busy

840
00:42:46,640 --> 00:42:49,600
Speaker 2: news kind of day? From New York City and San Francisco.

841
00:42:49,840 --> 00:42:52,560
Speaker 2: This is Bloomberg Technology.