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Hedge Funds, Eco, and AI · Bloomberg Intelligence

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Speaker 2: Welcome to the Bloomberg Markets Podcast. I'm Paul Sweeney. Alongside
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Speaker 1: Every business day we bring you interviews from CEOs, market pros,
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Speaker 2: podcast catch funds. You know them, you love them? How
0:57
Speaker 2: is performance in twenty twenty three? What to look for
1:00
Speaker 2: in twenty twenty four? Elana Weinstein Joints and she's the
1:02
Speaker 2: founder and CEO of the IDW Group and Bloomberg. Shanali Basset,
1:07
Speaker 2: who covers all of Wall Street, joins, is how cool
1:09
Speaker 2: is that Shanale that talks in hedge funds.
1:12
Speaker 3: I've been waiting to have this conversation all week because
1:14
Speaker 3: what a weird year, Paul in hedge funds, and Alana
1:17
Speaker 3: is so plugged into this universe. Let's talk about performance first, though,
1:21
Speaker 3: because what's stunning is you've seen this massive melt up
1:23
Speaker 3: in markets, and the hedge funds, by and large across
1:27
Speaker 3: the industry really have not kept up. Bloomberg's All Hedge
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Speaker 3: Index is only up about four point eight percent through
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Speaker 3: the year so far, and the multi strategies are supposed
1:35
Speaker 3: to be the kings of the castle here are only
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Speaker 3: up less than three percent on the year. Alana, what's
1:41
Speaker 3: going on?
1:42
Speaker 4: Okay, So let me unpack those numbers. First off, the
1:46
Speaker 4: hedge fund index, I think, is a blend of everything,
1:48
Speaker 4: So we need to kind of go strategy by strategy
1:50
Speaker 4: to really pull out what the themes are. Long short equities,
1:54
Speaker 4: which had a really tough twenty one and twenty two. Finally,
1:58
Speaker 4: Shanali had performance. I am please to sit here and
2:01
Speaker 4: say something positive, which I have not been able to do.
2:03
Speaker 4: For the last couple of years, those funds, which are
2:06
Speaker 4: a big percentage of the hedge fund universe, the directional
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Speaker 4: concentrated Tiger cubs and similar are up as much as
2:13
Speaker 4: twenty percent, thirty percent, even forty percent. The issue there,
2:18
Speaker 4: which is really important is even though they're up that much,
2:22
Speaker 4: they still have for the most part, an enormous high
2:24
Speaker 4: watermark to have to get out of. And let's just
2:27
Speaker 4: say it's a fund that's up thirty five percent this year. Okay,
2:31
Speaker 4: you may think, and they were down about fifty percent
2:34
Speaker 4: between twenty one and twenty two. You may think, okay,
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Speaker 4: ye'ar one this year, up thirty five they can get
2:40
Speaker 4: out of that remaining fifteen or twenty next year and
2:43
Speaker 4: then it's smooth sailing. But the reality is their AUM
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Speaker 4: maybe was thirteen billion at the beginning of twenty one,
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Speaker 4: it's six and a half billion now, So that thirty
2:53
Speaker 4: five percent is on a much smaller base of capital,
2:57
Speaker 4: and it's actually as a result, so there may very
2:59
Speaker 4: much fewer dollars made than it would have been had
3:03
Speaker 4: they made that money back up before they had the losses,
3:06
Speaker 4: And as a result, there's really another sixty five percent
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Speaker 4: to go, So that's a huge headwind for that strategy.
3:16
Speaker 3: How much more excitement is there around the industry, especially
3:20
Speaker 3: because many of them have not met the market performance still,
3:24
Speaker 3: and so even if they're up, they have two issues
3:26
Speaker 3: here to your point the high water mark and the
3:28
Speaker 3: issue is you could just invest in the S and
3:30
Speaker 3: B or the Nasdaq or even the socks up sixty
3:32
Speaker 3: five percent this year, how does that set them up
3:35
Speaker 3: into appetite investor appetite for new hedge fund allocations next year.
3:39
Speaker 4: Let me also touch on the multi managers which you cited.
3:42
Speaker 4: It is true that blended it's not a great result,
3:45
Speaker 4: but unpacking that, there's a lot of dispersion in that result.
3:49
Speaker 4: If you look at the more established multi managers that
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Speaker 4: have been around a while and have built a mouse
3:56
Speaker 4: trap that is very difficult to compete with. Fun like
4:00
Speaker 4: Citadel leading the pack up fifteen percent, which is a
4:04
Speaker 4: very different number than what you cited, or Millennium point
4:08
Speaker 4: seventy two up double digits, and then the rest are struggling,
4:12
Speaker 4: and that has a lot to do. So when we
4:14
Speaker 4: to answer your question LP appetite, you know, the reality
4:18
Speaker 4: is the reason the other multi managers grew so quickly
4:21
Speaker 4: is because the more established players were either closed or
4:26
Speaker 4: very deliberate about how they grew. And if you can't
4:30
Speaker 4: allocate to the more established guys, or at least not
4:32
Speaker 4: at the level you'd like, then you end up pouring
4:34
Speaker 4: money into all these other funds that grew in the
4:38
Speaker 4: last two years hand over fist. And when I say quickly,
4:41
Speaker 4: I mean between three and eight x. Think about that
4:46
Speaker 4: over a twenty four to thirty six month period. It
4:49
Speaker 4: is very difficult to deploy that kind of capital growth
4:54
Speaker 4: and hire a winning team. In order to do that,
4:58
Speaker 4: talent is really fugual to hire and attract. No one
5:02
Speaker 4: knows that better than myself and my team, and so
5:06
Speaker 4: you can't get from one billion to eight billion, hire
5:09
Speaker 4: one hundred and fifty pms and expect a great result.
5:13
Speaker 4: There's a lot more that goes into this.
5:15
Speaker 5: Okay, well, let's talk about talent, because I feel like
5:18
Speaker 5: it was, you know, pandemic era where all we were
5:20
Speaker 5: talking about was the competition to talent and compensation wars
5:24
Speaker 5: who can offer the best starting salaries and the biggest bonuses.
5:27
Speaker 5: We know that it has been a more difficult year
5:29
Speaker 5: in terms of actually people getting paid, and we're probably
5:33
Speaker 5: finding that out here at the tail end of the year.
5:35
Speaker 5: So what is your view here on compensation and how
5:39
Speaker 5: these firms are making themselves attractive.
5:42
Speaker 4: I think compensation kind of falls into one of two buckets.
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Speaker 4: It's either formulaic and for example, if you're at a
5:49
Speaker 4: multi manager with a pass through, you know exactly what
5:52
Speaker 4: you're getting paid. There's no mystery there. Or you're at
5:55
Speaker 4: a fund which is like a single manager, where if
6:00
Speaker 4: you're a senior person, you have points in the fund
6:02
Speaker 4: and then there's maybe a jump ball with respect to
6:05
Speaker 4: being able to reward you on top of that, but
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Speaker 4: to the extent it's a fund that has a high
6:10
Speaker 4: high water mark. No, there hasn't been a performance fee,
6:14
Speaker 4: for example, the long short equity managers in twenty one
6:17
Speaker 4: for the most part, there wasn't one in twenty two,
6:20
Speaker 4: and even though they put up this incredible performance in
6:23
Speaker 4: twenty three, they don't have a performance fee with which
6:27
Speaker 4: to pay those people. And so to answer your question,
6:30
Speaker 4: I think there's going to be a lot more frustration
6:35
Speaker 4: this year than there even has been the last couple
6:37
Speaker 4: of years. Those people are going to get paid more
6:40
Speaker 4: because the manager is going the founder is going to
6:43
Speaker 4: feel he or she needs to reach more deeply into
6:46
Speaker 4: the management fee to pay them. But when you're someone
6:48
Speaker 4: who's put up hundreds of millions of dollars, even billions
6:51
Speaker 4: of dollars, the dispersion between what you're actually going to
6:54
Speaker 4: get paid this year and what you've produced is going
6:57
Speaker 4: to be very frustrating versus in previous Here is where
7:00
Speaker 4: there wasn't performance for the fund. I didn't put up
7:03
Speaker 4: performance as an individual, So whatever I get paid, I'm
7:06
Speaker 4: kind of okay with because that's the ethos of this industry.
7:08
Speaker 4: It's paid for performance. Now I've put up tremendous performance,
7:12
Speaker 4: and my founder isn't really paying me something that feels
7:15
Speaker 4: in any way proportionate to what I should get paid.
7:18
Speaker 4: And I want to also highlight as much as some
7:21
Speaker 4: of these funds lost a significant amount of AUM, we're
7:24
Speaker 4: still talking about falls from Grace of thirty billion to
7:27
Speaker 4: twenty billion, or in the case of Tiger Global, one
7:31
Speaker 4: hundred billion to fifty five billion. But think about the
7:34
Speaker 4: management fee. On fifty five billion, that's still a billion
7:37
Speaker 4: of fees, or on twenty billion, that's four hundred million
7:41
Speaker 4: of fees. So and these teams are relatively lean, particularly
7:45
Speaker 4: at senior levels, and everyone knows that. So it's it's early,
7:49
Speaker 4: still a visa vcamp. But what we're hearing, even though
7:52
Speaker 4: the number is better, is an increased level of frustration,
7:55
Speaker 4: and I think there's going to be more vulnerability at
7:58
Speaker 4: these funds as a result.
8:00
Speaker 2: When I left the street in the mid two thousands,
8:01
Speaker 2: I studied long and hard about whether to transition to
8:03
Speaker 2: the hedge fund business. And what I concluded then was
8:06
Speaker 2: that long short equity, no alpha left done game had
8:11
Speaker 2: been played out, so I can go Bloomberg.
8:13
Speaker 4: So my question is how lucky we are?
8:16
Speaker 2: And I was absolutely correct that the numbers bear that out.
8:19
Speaker 2: My question is if I'm a really good trader, I
8:21
Speaker 2: don't know, bonds, currency, something at Morgan, Stanle There, Goldman, Sachs.
8:24
Speaker 2: Back in the day, I could just leave and go
8:26
Speaker 2: raise a couple of billion dollars and then boom. That
8:28
Speaker 2: was my path. Does that still exist or does a
8:31
Speaker 2: lot of the new money coming into hedge funds go
8:34
Speaker 2: to the point seventy two's and the citadels.
8:37
Speaker 6: Well.
8:37
Speaker 4: As I said earlier, some of those established managers are
8:40
Speaker 4: closed or very carefully accepting new capital. I believe me,
8:44
Speaker 4: there's a line around the block to allocate to those.
8:46
Speaker 4: But two things. One the days of leaving the cell
8:50
Speaker 4: side to go start a hedge fund, I think you'd
8:51
Speaker 4: have to be completely nuts to try to attempt to
8:54
Speaker 4: do that. Good luck getting a job at a hedge
8:56
Speaker 4: fund period, because you've spent all this time on the
8:58
Speaker 4: cell side and back in the day. Sorry not to
9:01
Speaker 4: age you, but we got there. You could take risks,
9:04
Speaker 4: sure right, you could take risk. You can't do that
9:07
Speaker 4: post the financial crisis. So if you're still sitting on
9:10
Speaker 4: the cell side, the reality is you're in more of
9:12
Speaker 4: a managerial role than you are a risk taking role.
9:14
Speaker 4: At a senior level, I think it's candidly become more
9:18
Speaker 4: difficult to even launch coming from most hedge funds. Now,
9:22
Speaker 4: coming from a top flight hedge fund which has a
9:26
Speaker 4: great established track record and is doing well today, that's
9:30
Speaker 4: exciting to LPs, but that group of funds has become
9:32
Speaker 4: fewer and fewer. And yes, coming out of a fund
9:35
Speaker 4: like a Citadel or a point seventy two sets you
9:38
Speaker 4: up in good stead to be able to launch successfully,
9:41
Speaker 4: But think about coming out of some of the tiger
9:45
Speaker 4: cubs are related now that are still well below their
9:47
Speaker 4: high water mark. That's not exactly an exciting value proposition
9:51
Speaker 4: to Lpece to say, oh, I'm going to be different,
9:53
Speaker 4: you know, and don't worry about the last twenty one
9:56
Speaker 4: and twenty two. You know, we're doing better now and
10:01
Speaker 4: my approach to risk management and managing volatility is better
10:06
Speaker 4: than what you've experienced.
10:07
Speaker 3: Also em bettered in Paul's question here is there's a
10:10
Speaker 3: long short equation has been doing better, but macro has
10:14
Speaker 3: been such an exciting prospect. Currencies, fixed income, the interest
10:17
Speaker 3: rate environment so drastically changing. When you're looking at the
10:21
Speaker 3: types of managers. How much is the macro story part
10:25
Speaker 3: of twenty twenty four and what does that mean for
10:27
Speaker 3: the talent story.
10:28
Speaker 4: That's a good question, Shanali, because every year I feel
10:31
Speaker 4: like it's a different story in macro. Twenty two is great,
10:35
Speaker 4: twenty three has not been so great, So we'll see
10:38
Speaker 4: what twenty four holds. It's a strategy which embodies as
10:42
Speaker 4: we've seen a lot of volatility, so I think it's
10:47
Speaker 4: TBD in terms of how they will perform. And you know,
10:53
Speaker 4: talent follows where there is an ecosystem which can navigate
11:00
Speaker 4: that volatility best.
11:02
Speaker 2: We're now in an environment, an entry environment that haven't
11:05
Speaker 2: been in a long time where rates went up so
11:07
Speaker 2: much now they're going to be coming down. Is there
11:09
Speaker 2: a feeling within the hedge fund community that certain strategies
11:11
Speaker 2: are going to work better in twenty four than maybe
11:14
Speaker 2: the past couple of years.
11:15
Speaker 4: Well, I think the reality is the uh, you know,
11:22
Speaker 4: the bar has gone up in terms of not just
11:27
Speaker 4: just the market environment, but also what LPs expect for
11:30
Speaker 4: what they're paying. And it's really the focus is of
11:33
Speaker 4: course on alpha and running in a way which neutralizes
11:38
Speaker 4: a lot of the market risk inherent right, that has
11:41
Speaker 4: whip sawed a lot of the return for funds. Factor
11:46
Speaker 4: rotations really has obscured great fundamental stock picking and so
11:52
Speaker 4: being somewhere which can isolate what is value, growth, momentum,
12:02
Speaker 4: macro cross currents and hedge those things out so that
12:05
Speaker 4: great idiosyncratic alpha driven stock picking can shine through. That
12:10
Speaker 4: that's the most important thing, because then it doesn't matter
12:13
Speaker 4: what the market's doing.
12:14
Speaker 2: You know.
12:14
Speaker 3: Interestingly, I want to comment on something you had talked
12:17
Speaker 3: about a little earlier. We were talking about the success of
12:19
Speaker 3: sit it out in multi strat but it's also worth
12:21
Speaker 3: talking about the undertone of the other side of that story.
12:25
Speaker 3: You had mentioned that some firms grew so fast, so quickly,
12:29
Speaker 3: and the poster child of that this year was really
12:31
Speaker 3: Sean Feld. This idea that a lot of money was pulled,
12:34
Speaker 3: billions of dollars was pulled from the firm. You know,
12:37
Speaker 3: they really had to look to raise capital to really
12:40
Speaker 3: fill that whole. They even considered merging with another large
12:44
Speaker 3: multi strategy firm. Is Seanfeld alone? Is there other struggles
12:49
Speaker 3: that we're seeing in firms like Schonfeld and how does
12:51
Speaker 3: that play out into next year?
12:52
Speaker 7: Totally?
12:53
Speaker 4: You know, all these funds that grew so quickly, whether
12:56
Speaker 4: I mean, I'm just not to just to talk about
13:00
Speaker 4: who's grown hand over fist. These funds are multiples aum
13:04
Speaker 4: wise where they were even two years ago. Lmr Hudson
13:08
Speaker 4: Bay sinctive Schoenfeld, as you mentioned, fruition, and you can't
13:13
Speaker 4: do that. You have to be far more deliberate with
13:16
Speaker 4: respect to thinking about what is the end state, how
13:18
Speaker 4: many pms do I want so that I can maximize
13:22
Speaker 4: idea generation and minimize crowding risk and then execute against
13:27
Speaker 4: that and only grow as you've been able to attract talent,
13:31
Speaker 4: and I don't mean bodies, I mean talent, and talent
13:34
Speaker 4: always has options, right if you're that good. The reality is,
13:40
Speaker 4: as one of those multimanagers that grew very quickly, you're
13:44
Speaker 4: up against the Citadels, the point seventy two's, the Ballyasns
13:47
Speaker 4: of this world, the millenniums competing for those people. So
13:50
Speaker 4: what are you offering that's really a differentiated value proposition?
13:54
Speaker 4: And when I hear of a fund and this is
13:56
Speaker 4: an actual fund that grew eight x in that period
14:00
Speaker 4: and hired and is now has one hundred and fifty
14:02
Speaker 4: pms with no real team underneath any of those pms
14:06
Speaker 4: and the pms they attracted or really science experiments. Most
14:10
Speaker 4: of them have not been pms before, don't know how
14:12
Speaker 4: to run risk in a market neutral model, and there's
14:15
Speaker 4: no real resources at the firm to make them better.
14:18
Speaker 4: That's a recipe for disaster. And what we've learned is
14:22
Speaker 4: being a successful multi manager is not as simple as capital,
14:26
Speaker 4: a pass through and PMS. It is far more nuanced
14:29
Speaker 4: than that.
14:31
Speaker 5: All right, really great to have you join us today,
14:33
Speaker 5: Alana and Shanali Basik as well. Thank you so much.
14:35
Speaker 5: We really appreciated. Alana Einstein there from IWDIDW group. It's
14:44
Speaker 5: the holiday week, guys, We're almost through it. We're like
14:46
Speaker 5: almost at the end of the year. Thank you very much.
14:50
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15:04
Speaker 2: I want to pivot to Cam Harvey. He's professor finance
15:07
Speaker 2: at the Fuqua School of Business at Duke University, my
15:11
Speaker 2: alma mater. I took a couple classes from Professor Harvey.
15:14
Speaker 2: I survived. I'm proud to say I can't claim any
15:17
Speaker 2: more success than survival, but some good stuff there. Hey, Cam,
15:21
Speaker 2: I look at the ten year treasury. I mean, I'm
15:23
Speaker 2: not a bond guy, but I mean, just a couple
15:25
Speaker 2: of coffee ago, the ten year treasury was at five percent.
15:27
Speaker 2: Now we're at three point eighty two percent. What's going
15:30
Speaker 2: on out there?
15:32
Speaker 9: Yeah, So it overall is very good news that that
15:36
Speaker 9: rate has gone down, and I think that that investors
15:41
Speaker 9: and consumers have revised their expectations of inflation and this
15:47
Speaker 9: is good news. So it means that the Fed has
15:50
Speaker 9: stopped and is now talking about decreasing rates, and that
15:53
Speaker 9: pressure on the long term rates seems to abate it.
15:59
Speaker 2: So I mean the market's pricing in multiple rate cuts
16:04
Speaker 2: for twenty twenty forty. I think the market's maybe a
16:07
Speaker 2: little over at skis here or is that something that
16:09
Speaker 2: the Fed should be considering?
16:12
Speaker 6: Well?
16:13
Speaker 9: Last time, Ozon I was making the case that the
16:16
Speaker 9: cuts should have begun in twenty twenty three. So the
16:21
Speaker 9: Fed overshot by pushing the short rates up so high.
16:26
Speaker 9: And the sooner that they take down some of these cuts,
16:30
Speaker 9: the better, because it does cause a lot of stress
16:34
Speaker 9: in our economy, and that stress is unnecessary given that inflation,
16:39
Speaker 9: according to my calculations, is running well below two percent.
16:43
Speaker 10: And professor, let's dig into those calculations because they're fascinating.
16:46
Speaker 10: I love reading your work, whether it's across LinkedIn or
16:49
Speaker 10: more broadly, and for you, it's housing, right, This is
16:52
Speaker 10: where the misinterpretation is coming in.
16:56
Speaker 6: Exactly.
16:56
Speaker 9: So housing is operating with the lag, so it's not
17:01
Speaker 9: like current rents or current housing prices. We change the
17:05
Speaker 9: way that inflation is calculated back in nineteen eighty two,
17:09
Speaker 9: so before eighty two, it was real time inflation and housing,
17:14
Speaker 9: but now it operates with the LAG. So the housing
17:18
Speaker 9: inflation that's reported in the CPI is inflation that happened
17:24
Speaker 9: a year ago, and that component of inflation is thirty
17:28
Speaker 9: five percent of the overall inflation. And the reason inflation
17:33
Speaker 9: has been high is that the shelter component has been
17:36
Speaker 9: running at seven percent. That's what goes into the CPI,
17:41
Speaker 9: but we know that's not the case. If you look
17:43
Speaker 9: in real time rental inflation or house price inflation is
17:48
Speaker 9: near zero or one percent, And if you recalculate the
17:53
Speaker 9: CPI with real time shelter costs, then what you see
17:59
Speaker 9: is a real time inflation rate below two percent. And
18:04
Speaker 9: this has been very frustrating because this shelter component caused
18:11
Speaker 9: the FED to make a mistake early on in declaring
18:14
Speaker 9: that housing was no big deal and inflation was transitory,
18:20
Speaker 9: and it caused them not to move to keep rates
18:23
Speaker 9: so low for so long, and then the same mistake
18:27
Speaker 9: was made in twenty twenty three. It was obvious that
18:32
Speaker 9: the only reason inflation was high was because of the
18:36
Speaker 9: shelter inflation that had happened in the past. Policy needs
18:40
Speaker 9: to be executed based upon real time data, not on
18:45
Speaker 9: data that happened like a year ago.
18:48
Speaker 10: In the world I cover more which is AI we
18:50
Speaker 10: say a lot garbage in, garbage out. So how are
18:54
Speaker 10: you having conversations as a professor of course over there?
18:57
Speaker 10: Do you trying to get this message across to use
19:00
Speaker 10: hearing that it's falling on death is or more is
19:04
Speaker 10: that are willing to listen to some of the data
19:06
Speaker 10: that should be taken into account when it comes to
19:07
Speaker 10: in flrastory pressures.
19:10
Speaker 9: So this has been a more than a year long
19:13
Speaker 9: campaign for me, and again I'm very pleased that the
19:16
Speaker 9: FED has changed the conversation. And the sooner they move
19:20
Speaker 9: the better. There is still a lot of risk out there.
19:24
Speaker 9: So like I know, people are patting the FED on
19:27
Speaker 9: the back, congratulations, mission accomplished. No, it's way way too early.
19:34
Speaker 9: My inverted Yell curved indicator which is eight out of
19:38
Speaker 9: eight in predicting recessions, that's the nineteen sixties. We are
19:43
Speaker 9: at the average lead time to a recession. So if
19:47
Speaker 9: you look at the last four recessions, the Yell curve
19:50
Speaker 9: inverted on average thirteen months before a recession, and we
19:55
Speaker 9: are at month thirteen breakdown. We're at the average, So
19:59
Speaker 9: again it's too early. There are significant headwinds. The FED
20:04
Speaker 9: can help things by reducing the FED funds rate as
20:08
Speaker 9: soon as possible.
20:10
Speaker 2: Hey, Kim, I know you also do a lot of
20:12
Speaker 2: work on blockchain, crypto fintech. You teach a course down
20:16
Speaker 2: there at DO Innovation and Crypto Ventures. What's the theme
20:19
Speaker 2: that you think we should be on the lookout for
20:22
Speaker 2: for twenty twenty four in this space.
20:24
Speaker 9: So it's interesting that we've got the two simultaneous disruptions happening.
20:29
Speaker 9: So one is then decentralized finance to change our payment
20:34
Speaker 9: system and to allow for functionality that we've never had before,
20:40
Speaker 9: and we've got AI going on at the same time.
20:43
Speaker 9: So I look at this in kind of the big picture,
20:47
Speaker 9: and the big picture the thing that worries me a
20:50
Speaker 9: lot is just the size of the US debt. So
20:55
Speaker 9: the service on that debt is about seven hundred billion
20:59
Speaker 9: dollars a year, and that service will increase in twenty
21:03
Speaker 9: twenty four to be the second largest spending category for
21:07
Speaker 9: the government. So the way to get out of this
21:11
Speaker 9: problem is, well, there's three different ways. One way is
21:16
Speaker 9: to increase taxes, and that just kills growth and nobody
21:20
Speaker 9: wants increased taxes. The second way is to print money
21:25
Speaker 9: and to inflate our way out. So you print the
21:27
Speaker 9: money to pay off the debt, and that is just
21:30
Speaker 9: like a tax also, so nobody really wants that. Nobody
21:33
Speaker 9: wants to go back to that inflation. The third way
21:37
Speaker 9: is with growth. So if we increase our growth rate,
21:42
Speaker 9: then it naturally increases the tax revenue and allows us
21:46
Speaker 9: to pay down some of that debt. So we are
21:49
Speaker 9: at a cusp of a pivot point, in my opinion,
21:52
Speaker 9: in the economy with these two disruptions going on, and
21:57
Speaker 9: they potentially allow us to get on a different growth path.
22:02
Speaker 9: And it's really important that we do not fumble these
22:05
Speaker 9: opportunities by overregulating either decentralized finance or AI. We need
22:12
Speaker 9: to embrace these disruptions and to look at the benefits,
22:17
Speaker 9: not just the costs. And I'm not saying this is
22:20
Speaker 9: without risk. There is risk, but the key thing is
22:24
Speaker 9: to get on a higher growth path. I don't think
22:27
Speaker 9: it's unreasonable, all.
22:30
Speaker 2: Right, Kim, that's great stuff. As always, Campbell Harvey, Professor
22:33
Speaker 2: of Finance at the Fuqual School of Business at Duke University,
22:39
Speaker 2: Great great Place, highly recommend it.
22:41
Speaker 8: You're listening to the tape. Can's our live program Bloomberg
22:44
Speaker 8: Markets weekdays at ten am Eastern on Bloomberg Radio, the
22:48
Speaker 8: tune in app, Bloomberg dot Com, and the Bloomberg Business App.
22:51
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22:54
Speaker 8: flagship New York station, Just say Alexa Play Bloomberg eleven thirty.
23:00
Speaker 10: We dig into the geopolitical news of the week of
23:03
Speaker 10: the month. Of course, the narrative continues to build about
23:06
Speaker 10: the Red Sea, and of course Suthi Rebel has been
23:09
Speaker 10: seen to me attacking certain vessels and it basically redirecting.
23:13
Speaker 10: We understand now half of all containership fleets now currently
23:17
Speaker 10: no longer going through the Red Sea. They're avoiding the route.
23:20
Speaker 10: This is according to new industry data that overall is
23:24
Speaker 10: one that we can probably cooperate with. Our next guest,
23:26
Speaker 10: we're please to welcome to the show. Anton Post, who
23:28
Speaker 10: CEO Mercury Resources, and you're all about negotiating skills. You're
23:32
Speaker 10: about professionals from an industry basis helping you plot out
23:36
Speaker 10: your dry cargo issues. When you are looking at such
23:40
Speaker 10: a difficult supply chain management conundrum, What do you advise
23:43
Speaker 10: at this moment Anton.
23:44
Speaker 11: Yeah, thanks Carolyn. So at this point it's a lot
23:48
Speaker 11: of wait and see in what's happening with the international coalition.
23:54
Speaker 11: We are partners at have Court Gallbery's Melory Alexander. On
23:57
Speaker 11: the container side, it's right now a lot of handholding
24:01
Speaker 11: with our client base on the commodities sector to guide
24:06
Speaker 11: them through what's happening in the markets at this point.
24:10
Speaker 11: So we're seeing of course increased freight, increased insurance, a
24:15
Speaker 11: lot of uncertainty and mixed signals from ship owners, container
24:20
Speaker 11: lines and from governments on what's happening to basically mitigate
24:27
Speaker 11: the risk and the threats that are out there from
24:28
Speaker 11: these many art groups.
24:30
Speaker 10: I mean, yeah, talk to us about some of the
24:32
Speaker 10: mitigation of the risks of how the US Navy is
24:34
Speaker 10: leading this military partnership. You are out there talking to
24:36
Speaker 10: the brocus the ship is the government support authorities. Do
24:39
Speaker 10: they take this as some sort of easing of concern
24:43
Speaker 10: or are they still wanting to hold back.
24:46
Speaker 6: Yeah, we're seeing some easing of concern.
24:49
Speaker 11: Chip operators on the container side, like Marrisk CGM are
24:53
Speaker 11: starting to signal a return to going into the Red
24:55
Speaker 11: Sea and the Suez Canal. Some ship operators on the
25:00
Speaker 11: container side like HAPAG Lloyd are still holding back and
25:04
Speaker 11: not even announcing any kind of return to that to
25:09
Speaker 11: that market on the dry bulk side, which is a
25:11
Speaker 11: huge part of a huge part of our.
25:13
Speaker 6: Business dry commodities ship owners.
25:16
Speaker 11: Right now, it's naturally a time of year where it's
25:19
Speaker 11: where things have slowed down. Uh, So we're seeing ship
25:23
Speaker 11: owners of the dry bulk side diverting ships that are
25:26
Speaker 11: already en route and ship raiding new cargos.
25:31
Speaker 6: For January February.
25:33
Speaker 11: Timing is more of a let's see what happens after
25:37
Speaker 11: New Year's and what's happening on the h on the
25:40
Speaker 11: side to U, you know, on the on the news
25:42
Speaker 11: to mitigate what's happening there with the with with the
25:46
Speaker 11: military response. So of course we've seen the Navy move
25:49
Speaker 11: the usswy D Eisenhower into the Gulf of Baden and
25:53
Speaker 11: off them Andy Coast.
25:55
Speaker 6: Uh.
25:55
Speaker 11: This twenty nation coalition that the United States it's announced
26:01
Speaker 11: is seemingly coming together, but there's been some hesitancy from
26:05
Speaker 11: a couple of you know, some of the US allies
26:07
Speaker 11: and some nations have been reluctant to even put their
26:10
Speaker 11: name attached to it. Yet so definitely some still some
26:13
Speaker 11: concerns and not a lot of comfort.
26:17
Speaker 2: Anton. Who ultimately decides whether ship does transit the Red
26:21
Speaker 2: Sea and the Suez Is it the insurance company, the
26:25
Speaker 2: ship owner, maybe the captain himself or herself. I mean,
26:28
Speaker 2: who really at theen today makes that decision?
26:31
Speaker 11: Yes, yes, and yes, right, it's a it's a very
26:34
Speaker 11: much a combined situation. Ultimately, the master of the ship,
26:37
Speaker 11: the capture of the ship has the as the ultimate say, right,
26:41
Speaker 11: but they're taking instructions from the ship owner. But in
26:44
Speaker 11: this situation, really in all situations regarding commercial and merchant shipping,
26:48
Speaker 11: you have many layers on top, right, you have the
26:50
Speaker 11: ultimate ship owner, the company that owns the ship. You
26:53
Speaker 11: have the master that has ultimate responsibility for the ship.
26:56
Speaker 11: And then you have the ship operator, the company that's
26:59
Speaker 11: often time chartering the vessel and has some say over it.
27:03
Speaker 11: So it's very much a combined decision. So even if
27:06
Speaker 11: a ship owner wants to order that ship to transit
27:10
Speaker 11: through the through the Suez Canal and the Red Sea,
27:13
Speaker 11: if the master is not comfortable, right, the master can
27:16
Speaker 11: basically say we're not taking We're not taking her through.
27:19
Speaker 2: You know, I just kind of learned today through some
27:21
Speaker 2: other discussions that while yes, the having a aircraft strike
27:25
Speaker 2: carrier group in the area is certainly intimidating, certainly represents
27:28
Speaker 2: a tremendous show of force, at the end of the day,
27:31
Speaker 2: what can it really do against a bunch of terrorists?
27:35
Speaker 2: You know, what's the what's the belief in the industry
27:37
Speaker 2: about what it can really achieve?
27:40
Speaker 11: Yeah, I mean right now, without having the international will
27:44
Speaker 11: to do something, and the geopolitics going on over over
27:49
Speaker 11: being seen to align you know, for some of our
27:53
Speaker 11: NATO allies in this case, right to see themselves to
27:55
Speaker 11: align with the United States on the mission to deal
27:59
Speaker 11: with it's been it's been walking a tight tightrope, right,
28:03
Speaker 11: So we're not even seeing strong rhetoric from.
28:06
Speaker 6: Some nations on the issue, let.
28:07
Speaker 11: Alone, let alone deploying actual military assets, enable assets to
28:12
Speaker 11: the situation. You know, some of what's been written about this,
28:16
Speaker 11: about the about the coalition that's coming together, as some
28:19
Speaker 11: NATO allies have instead of deploying a destroyer of frigate
28:24
Speaker 11: let alone, you know, any kind of hardcore military assets,
28:27
Speaker 11: they're deploying one staff officer to the team, right, So
28:31
Speaker 11: what signal is that sending to ye many armed groups here.
28:37
Speaker 6: Operas I mean.
28:38
Speaker 10: To that end, I mean what's fascinating is just how
28:42
Speaker 10: global and interconnected the shipping world is. I think in
28:45
Speaker 10: some of your notes you were talking about one vessel
28:47
Speaker 10: which is Liberia flagged, Dutch operated, Japanese owned. To that end,
28:53
Speaker 10: how does do politics in and of itself affect the
28:57
Speaker 10: business of shipping? Are people having to decide whether or
29:01
Speaker 10: not they work alongside certain alliances that they've always usually done,
29:05
Speaker 10: So how is that playing out in the world in
29:07
Speaker 10: which you work?
29:08
Speaker 11: Yeah, absolutely, Caroline, And what we're seeing is situations in
29:14
Speaker 11: hardcore examples now of ship owners and dry cargo market.
29:18
Speaker 11: One example that comes to mind, right, a dry cargo
29:21
Speaker 11: ship operator that's working on a voyage of a dry
29:26
Speaker 11: cargo a dry commodity is actually asking a large international
29:31
Speaker 11: trading firm that's their counterparty on that if there's any
29:35
Speaker 11: Israeli involvement in the trade, let alone, put aside the
29:41
Speaker 11: ownership of the vessel, the operations of the vessel, where
29:45
Speaker 11: the ship is going to, put that all aside, just
29:47
Speaker 11: whether or not there's any involvement by Israeli companies in
29:51
Speaker 11: the actual trade of the commodity in that particular sense.
29:55
Speaker 11: So this is really really reach far reaching, right, something
30:00
Speaker 11: else that does always researching and getting ready for today.
30:03
Speaker 11: Interestingly enough, we're seeing ships now transiting through the Red
30:07
Speaker 11: Sea that are using their AIS system that's usually used
30:11
Speaker 11: to transmit data on the ship's position and load port
30:16
Speaker 11: and discharge port and ETA. They're using that instead of
30:21
Speaker 11: showing a discharge port of let's say Peaeus Grease, they've
30:25
Speaker 11: replaced that with information that says armed security aboard or
30:32
Speaker 11: no Israeli involvement in the ship in the in the
30:37
Speaker 11: slot where you would put the discharge port or the
30:39
Speaker 11: destination port, so that it transmits through to the MNY
30:43
Speaker 11: armed groups, right, that they could see that information as
30:48
Speaker 11: they're tracking the ship. In addition to what's allegedly an
30:52
Speaker 11: Iranian spy vessel you know, that's been lingering there too, and.
30:56
Speaker 2: Touch about thirty seconds left. I mean, is there any
30:59
Speaker 2: realistics solution here other than I guess the cessation of
31:03
Speaker 2: hostilities in the region.
31:05
Speaker 6: Yeah, I think the others.
31:07
Speaker 11: The other solution is potentially in very unsavory, right, a
31:11
Speaker 11: military solution to dealing with what's going on on the
31:16
Speaker 11: ground in Yemen, and of course, I'm no expert in
31:21
Speaker 11: military matters in terms of how to deal with that,
31:24
Speaker 11: so I wouldn't even I wouldn't even vent venture that.
31:27
Speaker 6: But you could.
31:28
Speaker 11: You can imagine if we're dealing with a situation where
31:30
Speaker 11: we're United States NATO allies are not even willing to
31:35
Speaker 11: send more than a staff officer to a joint naval
31:38
Speaker 11: task force, what's gonna you know, where's the will to
31:42
Speaker 11: deal with this on the situation on the ground where
31:45
Speaker 11: the attacks are originating from.
31:47
Speaker 10: Well, you as an officer in the US Naval Reserve,
31:49
Speaker 10: so you know a bit more than we do here
31:51
Speaker 10: in the radio studio. But we really appreciate your time. Anton,
31:55
Speaker 10: absolutely fascinated to get and on the ground feel of
31:57
Speaker 10: all the negotiations you're currently having. Anton Posners, of course,
32:00
Speaker 10: the CEO of Mercury Resources.
32:03
Speaker 8: You're listening to the tape Kent Live program Bloomberg Markets
32:07
Speaker 8: weekdays at ten am Eastern on Bloomberg Radio, the tune
32:10
Speaker 8: in app, Bloomberg dot Com, and the Bloomberg Business App.
32:13
Speaker 8: You can also listen live on Amazon Alexa from our
32:16
Speaker 8: flagship New York station, Just say Alexa play Bloomberg eleven thirty.
32:22
Speaker 10: We want to get some expertise in this area where
32:23
Speaker 10: the risks are also where the opportunities are to be
32:26
Speaker 10: investing in this sort of technology. We'll please to welcome
32:29
Speaker 10: Jake Sapo's general partner at Emergence Capital, and Jake, you know,
32:34
Speaker 10: the retort coming from the likes of open ai and
32:36
Speaker 10: the other foundational models has been fair use, and ultimately
32:39
Speaker 10: also the fact that they've been trying to get ahead
32:41
Speaker 10: of this in some way by striking deals with the
32:44
Speaker 10: actual springer. I think the key publicists over in Germany
32:47
Speaker 10: where they've sort of licensed some of their particular use
32:50
Speaker 10: of publications and writings. What will the New York Times
32:57
Speaker 10: case mean do you think for the training of these
32:59
Speaker 10: models when you put the genie back in, can you
33:02
Speaker 10: in any way take out New York Times's own articles
33:05
Speaker 10: from the training of open AI's model.
33:09
Speaker 6: Yeah, it's a great question.
33:10
Speaker 7: It's great to be here. What I'd say is this
33:13
Speaker 7: is going to create a lot of movement towards exploring
33:17
Speaker 7: open source models. So open ai is the champion of
33:21
Speaker 7: the kind of closed source model ecosystem, which means that
33:24
Speaker 7: the data that they're training on and the code that
33:26
Speaker 7: they actually generate from it is not publicly available, and
33:29
Speaker 7: so there's lots of questions now around transparency, what data
33:31
Speaker 7: are they using? What can we use as a business
33:34
Speaker 7: if we're going to use their opena models. What is
33:36
Speaker 7: happening now is an increased interest by people that consume
33:39
Speaker 7: models to explore open source models, where the data that
33:43
Speaker 7: is used to train those models is clearer and you,
33:46
Speaker 7: as the user of the model, have the ability to
33:47
Speaker 7: manipulate the model themselves. So we think that twenty twenty four,
33:51
Speaker 7: and certainly the advent of this lawsuit is going to
33:53
Speaker 7: push businesses who are using this technology to consider open
33:56
Speaker 7: source models more seriously.
33:58
Speaker 2: So I think I'm getting comfortable with what AI is,
34:03
Speaker 2: and that's a big leap for me because it took
34:04
Speaker 2: me in most of the year. Here now my question.
34:06
Speaker 7: The last time we talked about it.
34:07
Speaker 2: Yeah, I just need some help on what do you
34:10
Speaker 2: think in twenty twenty four, Jakes might be some of
34:12
Speaker 2: the use cases that maybe will help the general public
34:16
Speaker 2: get a better feel for what generative AI is and
34:19
Speaker 2: what it can mean.
34:20
Speaker 6: Yeah.
34:20
Speaker 7: Well, I think the good news is in twenty twenty four,
34:23
Speaker 7: we're going to move from kind of prototyping land into production.
34:27
Speaker 7: A lot of these applications are going to actually get
34:29
Speaker 7: launched and are going to have real impacts for consumers,
34:32
Speaker 7: you know. As you know, we focus on B to
34:34
Speaker 7: B software investing in emergence, and we think there's going
34:36
Speaker 7: to be a bunch of exciting applications of AI in
34:39
Speaker 7: twenty twenty four. Give you one example, we work with
34:42
Speaker 7: a company called Docimity, which is shorthand is LinkedIn for doctors,
34:47
Speaker 7: and they provide a whole suite of tools for doctors
34:49
Speaker 7: in addition to just a social networking application, but they
34:52
Speaker 7: help doctors serve their patients. One of the things that
34:54
Speaker 7: they're using AI to do is to help doctors draft
34:57
Speaker 7: letters to insurance companies to get approval for treatments.
35:00
Speaker 6: Right.
35:01
Speaker 7: That has massive implications for not just the doctors, but
35:04
Speaker 7: also obviously consumers and getting you know, much more efficient.
35:07
Speaker 7: That type of thing wasn't possible a year ago and
35:09
Speaker 7: is increasingly possible today. So you're going to see those
35:12
Speaker 7: types of things.
35:12
Speaker 6: Come to fruition.
35:13
Speaker 7: We have worked with a company called Ironclade that's in
35:16
Speaker 7: the legal contracting space and they help they help companies
35:19
Speaker 7: draft contracts using AI more effectively, which allows people to
35:22
Speaker 7: process contracts more quickly and ensure they're correct. So you're
35:25
Speaker 7: going to see them kind of seep into all sorts
35:27
Speaker 7: of applications across the business ecosystem.
35:31
Speaker 2: A new phrase for me, and there's a lot of
35:32
Speaker 2: new phrases I'm learning as it relates to AI co
35:35
Speaker 2: pilots that ensure humans stay engaged. Here explain what that
35:39
Speaker 2: concept is and of what are some interesting companies that
35:42
Speaker 2: maybe have seen with that tech.
35:44
Speaker 7: Yeah, so imagine that you are on your computer and
35:50
Speaker 7: you're searching for some piece of information. The idea is
35:54
Speaker 7: historically you would go, you know, to Google and look externally,
35:58
Speaker 7: or you would kind of scour all your documents internally,
36:01
Speaker 7: a copilot will actually pop up and give you not
36:03
Speaker 7: just a link to something, but actually an answer. We
36:06
Speaker 7: work with a company called Guru that does this exact thing.
36:09
Speaker 7: So the idea is, instead of searching across all of
36:11
Speaker 7: your applications, the information has actually serviced to you directly.
36:14
Speaker 7: So the concept of a copilot, to boil it down, is,
36:16
Speaker 7: as you're doing your job, you have an assistant that
36:19
Speaker 7: is kind of next to you that helps coach you
36:21
Speaker 7: on the right direction to go. Now, critically, there's a
36:24
Speaker 7: difference between a copilot and an autopilot. Autopilot is dangerous, right,
36:29
Speaker 7: because that's when the human shuts off their brain and
36:31
Speaker 7: the plane flies itself, and that could be bad, or
36:34
Speaker 7: you know, it could be good. As you're building these
36:37
Speaker 7: co pilots, As you're building these coaches, you need to
36:39
Speaker 7: ensure that the human stays engaged and is actually in
36:42
Speaker 7: putting their new their thoughts and creativity and double checking
36:45
Speaker 7: into the software. Because, as we all know, AI is
36:48
Speaker 7: not perfect. There are errors that are committed all the time.
36:51
Speaker 7: That's okay in consumer applications. You know, if you're chatting
36:54
Speaker 7: with a dead celebrity using AI, it's okay if it's wrong, right,
36:58
Speaker 7: But if I'm drafting a important legal contract or if
37:01
Speaker 7: I'm communicating with an insurance company, I need to be
37:05
Speaker 7: ensured that it's a bulletproof. And a core way to
37:07
Speaker 7: do that today is to ensure that the human is
37:09
Speaker 7: engaged with the copilot and not just clicking accept, accept,
37:12
Speaker 7: accept on whatever it suggests.
37:14
Speaker 10: When you're looking at the valuations of the companies that
37:17
Speaker 10: you're ruying in the B to B space, or more broadly,
37:19
Speaker 10: when we're talking of the latest one hundred billion dollar
37:22
Speaker 10: valuation of open AI. When we're thinking of Vanthropic reaching
37:25
Speaker 10: a run rate revenue run rate of eight hundred and
37:27
Speaker 10: fifty million and potentially being valued more than eighteen billion.
37:31
Speaker 10: Are those valuations realistic if open source is going to
37:35
Speaker 10: become more of the valued foundational model direction of choice
37:41
Speaker 10: or do you think, really still these valuations are going
37:44
Speaker 10: to be the right source of.
37:45
Speaker 7: Amount for them. It's a really great question. There are
37:50
Speaker 7: lots of great closed source companies like the ones you named.
37:53
Speaker 7: As open source becomes more and more viable in twenty
37:57
Speaker 7: four and twenty twenty four and beyond, work with a
37:58
Speaker 7: company called together that helps you know companies actually use
38:02
Speaker 7: closed source model open source models more effectively. There is
38:05
Speaker 7: going to be pressure put on these open source models,
38:07
Speaker 7: and so the key thing to check as you're evaluating
38:09
Speaker 7: an investment in a close source or really any a
38:12
Speaker 7: opportunity is retention.
38:14
Speaker 6: You want.
38:15
Speaker 7: These things are getting incredible adoption right initial adoption. People
38:19
Speaker 7: are playing with this stuff, experimenting with their prototyping, et cetera.
38:22
Speaker 7: But the core thing that will matter in twenty twenty
38:23
Speaker 7: four and AI is retention. Are people that start using
38:28
Speaker 7: the product continuing to use the product, and the key
38:30
Speaker 7: questions you alluded to is in these foundational models, it's
38:34
Speaker 7: easiest to start with the closed source model because it's
38:35
Speaker 7: all packaged for you and you can just kind of
38:37
Speaker 7: get it up and running quickly. But if open source
38:40
Speaker 7: models become more preferred, either because they're more easily manipulable
38:45
Speaker 7: or because of the New York Times, you know, driven
38:48
Speaker 7: concerns around where's your data coming from, there is going
38:51
Speaker 7: to be some downward pressure on these close source models,
38:54
Speaker 7: which could put pressure on retention, which could ultimately pu
38:56
Speaker 7: pressure on some of those valuations.
38:57
Speaker 10: And Jake, how are you trying to add analyze the
39:00
Speaker 10: regulatory outlook for twenty to twenty four as you make
39:03
Speaker 10: these investment decisions? How you trying to preempt It feels
39:07
Speaker 10: sort of like crypto all over again. Everyone's trying to
39:09
Speaker 10: get ahead of where the SEC or indeed, more broadly,
39:12
Speaker 10: you know, we've had an executive order here in the US,
39:14
Speaker 10: but this is going to come down to global regulation.
39:16
Speaker 10: We've seen the EU with its AI Act. How do
39:20
Speaker 10: you front run that?
39:22
Speaker 7: Yeah, well, I think transparency is really important, Like understanding
39:25
Speaker 7: where you get your data from is really important. You
39:27
Speaker 7: don't want to be using copyrighted data to train your models, right,
39:30
Speaker 7: that's like it's obvious, But I think people are going
39:33
Speaker 7: to be paying much more attention to where that data
39:35
Speaker 7: comes from. I think similarly, trust is going to become
39:37
Speaker 7: much more important, not just in terms of where your
39:39
Speaker 7: data comes from, but is that data actually believable? You know,
39:44
Speaker 7: bad data going into a good model is going to
39:46
Speaker 7: create a bad output. I work with the CEO of Guru,
39:50
Speaker 7: Rick Nucci, calls this truth washing, which is where, Okay,
39:54
Speaker 7: I'm using data that comes in and the model spits
39:56
Speaker 7: out an answer that sounds really confident.
39:59
Speaker 6: What's wrong.
40:01
Speaker 7: I think going forward there's going to be a much
40:03
Speaker 7: greater impetus put on how do you validate the data
40:05
Speaker 7: that went into training the model is not only legally
40:07
Speaker 7: for you, legal for you to use, but also accurate
40:10
Speaker 7: so that the input or the output that comes out
40:12
Speaker 7: of the model can be trusted. So as we think
40:15
Speaker 7: about evaluating investment opportunities, we're thinking about it from a
40:18
Speaker 7: first principle's perspective, which is a belief that regulators are
40:21
Speaker 7: going to move in the direction. Thank you Apple for
40:23
Speaker 7: the use of the thumbs up there. This technology is
40:26
Speaker 7: going to move in a direction where regulators are concerned about. Okay,
40:30
Speaker 7: is the data? Are you allowed to use the data
40:32
Speaker 7: that you are using? And is the output that's coming
40:35
Speaker 7: out of these models trustworthy such that good things can
40:37
Speaker 7: come from it?
40:38
Speaker 2: Thirty seconds Jake, if I bring a cool AI idea
40:41
Speaker 2: to Sandhill Road, can I raise money?
40:44
Speaker 6: Well?
40:45
Speaker 7: As we talked about last time, Paul, Standhill Road is
40:47
Speaker 7: that's the past. The future is San Francisco, the Embarcadero.
40:50
Speaker 7: That's where the question nice.
40:52
Speaker 2: I like that.
40:55
Speaker 7: But to answer your question, can you raise money? Well, first,
40:58
Speaker 7: I would look at your background, and I think your
41:01
Speaker 7: an incredible interviewer. I don't know how oh technically savvy, you.
41:04
Speaker 2: Are, right, but good.
41:06
Speaker 7: I mean the reality is there is going to be
41:09
Speaker 7: more media and companies twenty four yeah, exactly, covering your
41:12
Speaker 7: the media company, I'll writ a check all day long.
41:14
Speaker 7: There is going to be more scrutiny of AI investments
41:18
Speaker 7: going forward, and I think the key thing people are
41:20
Speaker 7: going to be looking for is that retention point. In
41:22
Speaker 7: twenty twenty three, so many AI applications, we're getting so
41:25
Speaker 7: much tire kicking, and lots of people were using the
41:27
Speaker 7: product for a week, two weeks, three weeks and then
41:29
Speaker 7: they would get bored or try the next hot thing,
41:31
Speaker 7: et cetera. What investors are going to be increasingly looking
41:34
Speaker 7: for in twenty twenty four is Okay, yeah, you've got
41:36
Speaker 7: a lot of people to start using your thing, but
41:38
Speaker 7: are people continuing to use the thing indefinitely and continue
41:40
Speaker 7: to get value out of it?
41:42
Speaker 6: Right?
41:42
Speaker 2: All right, Jake, once again, thanks so much for joining us.
41:44
Speaker 2: Really appreciate getting your insight there. Jake Sayper, general partner
41:48
Speaker 2: at Emergency Capital, Thanks.
41:51
Speaker 1: For listening to the Bloomberg Markets podcast. You can subscribe
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Speaker 1: platform you prefer. I'm Matt Miller. I'm on Twitter at
42:02
Speaker 1: Matt Miller nineteen seventy three.
42:04
Speaker 2: And I'm Paul Sweeney. I'm on Twitter at pt Sweeney.
42:07
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42:09
Speaker 2: Bloomberg Radio