Speaker 1: Welcome to the Bloomberg Surveillance Podcast. I'm term Keene Jay Leye.
Speaker 1: We bring you insight from the best in economics, finance, investment,
Speaker 1: and international relations. Find Bloomberg Surveillance on Apple Podcasts, SoundCloud,
Speaker 1: Bloomberg dot Com, and of course on the Bloomberg. In
Speaker 1: the bond market, we shape up as follows treasuries tens
Speaker 1: yields unchanged two point six three two on a two
Speaker 1: year note two point four six three percent. That's where
Speaker 1: I want to start this morning, at the front end
Speaker 1: of the yield curve, and we have a great gust
Speaker 1: to do it with Jerum Schneider, PIMCO, Head of short
Speaker 1: term bond Portfolios. Good morning to Jerome, Good morning, Good morning.
Speaker 1: Let's just start with two lines that I picked up
Speaker 1: from the notes I saw in your most recent research.
Speaker 1: Short term bond strategy to manage two things, potential defense
Speaker 1: in volatile markets and the optionality to move to higher
Speaker 1: risk allocations opportunistically. Let's just walk through those two issues
Speaker 1: right now. Why do I need the potential defense in
Speaker 1: volatile markets with VOLTSI love so. The question that remains
Speaker 1: for investors is how long is this economic cycle going
Speaker 1: to persist for and admittedly the financial conditions have eased
Speaker 1: quite a bit since the concerns of the fourth quarter,
Speaker 1: but monetary policy is only one ingredient to to the
Speaker 1: market conditions that helped perpetuate positive returns going forward. Ultimately,
Speaker 1: what we're gonna be dealing with is continued bouts of illiquidity,
Speaker 1: continued increases of volatility within the marketplace. And what's really
Speaker 1: happened is investors, whether your retail or investors or institutional
Speaker 1: have to be thinking about returns or expected returns from
Speaker 1: the construct of not only thinking about, hey, I could
Speaker 1: earn five seven percent or even more obviously historically in
Speaker 1: equities or emerging markets those higher higher beta allocations, but
Speaker 1: doing so with higher volatility expectations. In other words, we
Speaker 1: need to calibrate expectations for returns on a risk adjusted
Speaker 1: basis taking into account more volatility due to the uncertainty
Speaker 1: within the marketplace. So at the moment, volatility is really
Speaker 1: loud cross asset exactly what binds effects, et cetera. But
Speaker 1: think about how quick that healing process happened, and think
Speaker 1: how quickly how many bouts of illiquity we've had simply
Speaker 1: over the past three years and illiquidity. I'm using as
Speaker 1: a proxy here for volatility. But the volatility could emanate
Speaker 1: from politics. It could it could emanate from left tail
Speaker 1: risks such as China trade. And while these risks have
Speaker 1: actually been elongated, the runways of these risks, whether from
Speaker 1: monetary policy, trade policy, or even Brexit, they've elongated. The
Speaker 1: uncertainty could actually persist for quite some time over the
Speaker 1: over the next few years. So while we have a
Speaker 1: relative period of warmth as as spring approaches, don't be
Speaker 1: don't be fooled, and we should be prepared for that
Speaker 1: higher volatility. I just figured this out. Are you here
Speaker 1: to do a double? Is he gonna be on the
Speaker 1: real yield today? One television at least? But you're just
Speaker 1: this is your power, This is the power of feraoh
Speaker 1: booking the brightest guy in the world. Short term paper. Yeah,
Speaker 1: what the commercial paper used to be the thing we
Speaker 1: looked at the pulse. What's the new commercial paper? Guys
Speaker 1: like you look at every day. I'll tell your story, Tom,
Speaker 1: it's really interesting. So two years ago, when I was
Speaker 1: sitting in these seats, we're talking about the evolution of
Speaker 1: money market funds. Money market fund reform and putting people
Speaker 1: to sleep, telling him that the end of the money
Speaker 1: market fund world was coming soon, and we saw a
Speaker 1: trillion dollars worth of prime money market fund assets. Those
Speaker 1: that buy commercial paper go and buy government only money
Speaker 1: organt funds, those buy T bills de risking. So the
Speaker 1: story now has actually changed over the past few months.
Speaker 1: People have been lulled to sleep that they want to
Speaker 1: de risk. They're de risking out of these higher volatility
Speaker 1: classes equities, and they're putting their money, ironically back into
Speaker 1: prime money market funds. There's been a hundred billion dollars
Speaker 1: of new assets put into prime money market funds for
Speaker 1: an incremental return of just a few basis points over
Speaker 1: the safety of T bills. So why would you do that?
Speaker 1: And I think ultimately the world of commercial paper has
Speaker 1: once again become rather complacent to the to the notion
Speaker 1: of any type of credit risk, and we have to
Speaker 1: be more discerning in terms of credit risk. Clearly, you
Speaker 1: can steal that for the real appreciating seeds. So let's
Speaker 1: go to the next line to to have the optionality
Speaker 1: to move to higher risk allocations opportunistically. Are you looking
Speaker 1: for another December kind of moment, not an end of
Speaker 1: cycle moment, but a moment where that risk aversion builds,
Speaker 1: the faith in the cycle fades rapidly, and you get
Speaker 1: to deploy some capital into risk assets. So the starting
Speaker 1: point of analysis and portfolio management is diversification, but more importantly,
Speaker 1: managing downside risks. And we've really viewsed that managing downside
Speaker 1: risk is beginning in two thousand eighteen at Pimcoe, where
Speaker 1: we were really thinking about focusing on corporate credit and
Speaker 1: differentiating corporate credit from the data the index, picking specific
Speaker 1: stories that we liked, under accentuating those that we didn't,
Speaker 1: and diversizing. Now, granted, this was a process that began
Speaker 1: in late two thousand seventeen early two eighteen, and we
Speaker 1: didn't know when when actually the opportunity would would persist,
Speaker 1: but we thought, you know, there would be some some
Speaker 1: tail risks along the way, maybe some rude awakenings, but
Speaker 1: ultimately the growth, the slowing growth that we were seeing
Speaker 1: in the globe economy would translate into opportunity. When it
Speaker 1: happened in the fourth quarter, we had access liquidity. We
Speaker 1: saw some inclinations that liquidity was being dampened back in
Speaker 1: October off of our short term team at PIMCO, and
Speaker 1: that there was. As a result, we became more cautious
Speaker 1: from a liquidity standpoint when those opportunities pent became opportunistic.
Speaker 1: We found that the recalibration in in in UH spreads
Speaker 1: wider actually made things pretty good on a risk adjusta basis.
Speaker 1: To take some of our underweights back to market weight.
Speaker 1: In other words, some of the richness in the market
Speaker 1: was not really attractive. We sold it, and then as
Speaker 1: an active manager, we found an opportunity to actually redeploy
Speaker 1: capital when it became cheap, and more importantly, earned a
Speaker 1: liquidity premium or excess return by providing the market liquidity
Speaker 1: when traditional equity providers like banks, etcetera. Weren't there. So
Speaker 1: you've played it really well the last few months. You
Speaker 1: bought the weakness of December. I just wanted to what
Speaker 1: degree you're fighting the strength of the first quarter. So
Speaker 1: we've seen credits move in dramatic fashion. Some credits that
Speaker 1: were used at Libor plus forty six to nine months
Speaker 1: ago and blew out to Lybra plus three hundred or
Speaker 1: more are back to Libra plus fifty. So there's been
Speaker 1: almost a round trip. So you're right. This is a
Speaker 1: this is a market where you want to be trading
Speaker 1: simply focusing on credit work from the bottom up, and
Speaker 1: and that's what we're doing on our corporate credit side.
Speaker 1: So there is a there's basically a momentum now to
Speaker 1: take a breath. Let's find some opportunities to potentially be
Speaker 1: more defensive. At this point in time, in two thousand
Speaker 1: and six, people were screaming for seven basis points, ten
Speaker 1: basis points. Are we back to that silliness? No, where
Speaker 1: people are just trying to find the next ten basis points.
Speaker 1: It's hundreds of a percentage point. It's more fundamental now.
Speaker 1: So that was more structured, the leverage in the system.
Speaker 1: With structured now it's more fun fundamental, whereby we have
Speaker 1: to differgiate, you know, the you know, the cream from
Speaker 1: the from the rest of from the rest of the product.
Speaker 1: And as a result, that just takes homework, it takes resources.
Speaker 1: And as a result, having diversification, finding other opportunities to
Speaker 1: earn spread an income as we're doing, and mortgages some
Speaker 1: high quality ASSETBAC securities that actually offers your plenty of
Speaker 1: plenty of avenues. More importantly, I think this is The
Speaker 1: thing time is there's no real reason to reach for
Speaker 1: yield when you have portfolios they can yield between three
Speaker 1: and three and a half percent. Those are actually pretty
Speaker 1: attractive in a world where dividends are less than two percent,
Speaker 1: So why take the why take equity risk of this
Speaker 1: than you Pimco as well? What a joy for John
Speaker 1: Farrell and me always have Brian Weezer in our studios
Speaker 1: with pivotal research and of course brilliant work on the
Speaker 1: linkage of advertising into social We learned a few weeks
Speaker 1: ago that he had gone to the dark side and
Speaker 1: returned to the death start the sound side of group
Speaker 1: EM where he is helping them not so much with
Speaker 1: messaging but just thinking about what's out there. And the
Speaker 1: first we've got to talk about is absolute brilliance. Is
Speaker 1: there's not one office dog a group M is there?
Speaker 1: How many are there? Well? It? I work out of
Speaker 1: the Portland, Oregon office of one of our agency's mind
Speaker 1: Share and we have three dogs. You have a three
Speaker 1: dog night. We need a dog in the office. And
Speaker 1: and to be clear, the one of the dogs wears
Speaker 1: a bow tie every day. Tell me a code him
Speaker 1: Tom No, his name is Cooper. I think Cooper, that's cute,
Speaker 1: but it's a wonderful environment. It really is. What told
Speaker 1: you about how different it is. You used to cover
Speaker 1: these companies on the South Side, thinking about a sad
Speaker 1: on w p P. Once upon a time I had cells,
Speaker 1: I had buys. My position on the durability the agency
Speaker 1: model never changed, I'd argue, even when I had cell
Speaker 1: ratings from every agency holding company, I argued I was
Speaker 1: probably the greatest long term champion in the sense that
Speaker 1: I believed in the durability in a way that I
Speaker 1: think very few people, uh in equity markets. Yeah, I
Speaker 1: heard that. Yeah, absolutely. What's the state of advertising right now?
Speaker 1: I mean it is Facebook, Google, Facebook, Google, Facebook Google.
Speaker 1: Do you go in and try to change that with
Speaker 1: a new w PP after sir Martin or do you
Speaker 1: live with Facebook? No? Well, I mean here's the thing,
Speaker 1: And I think when I joined I worked for another
Speaker 1: holding company in two thousand three ten, and when I
Speaker 1: showed up, they're also coming from all street. The weird
Speaker 1: thing was how everyone's complaining about how dependent they were
Speaker 1: on television, how bad it was alternatives. Well, they have
Speaker 1: alternaate exactly. And but the point is that even then,
Speaker 1: every advertiser needed to think what was our alternative. In cinema,
Speaker 1: for example, was something that was held out as a hope, right,
Speaker 1: the idea that you could put it put money into
Speaker 1: on screen advertising in different minds, and then of course
Speaker 1: the Internet was considered an alternative. There will be alternatives,
Speaker 1: and every advertiser needs to think of the best alternative
Speaker 1: negotiating agreement. You have been more than anyone I know,
Speaker 1: strongest on you know what TV will survive, etcetera. Now
Speaker 1: there's certain networks I'll lead with NBC Universal who are
Speaker 1: saying we need fewer ads in prime time or on YouTube.
Speaker 1: They have those silly ads where you hit skip ad
Speaker 1: to get through them. That's a guy like you're it's
Speaker 1: your fault we're seeing those ads. What is the new Brian?
Speaker 1: We'ser attention span? Well for seconds? To be clear, I
Speaker 1: think that clutter is a significant problem, and I think
Speaker 1: that individuals. It doesn't take thought leadership to know that
Speaker 1: John and I are living in it it. I know, but
Speaker 1: I think every advertiser has to think differently about whether
Speaker 1: or not they should be allocating as much money to
Speaker 1: UH spots and dots for lack of a better do
Speaker 1: you guys know how much we hate that garbage cluttering
Speaker 1: up everything out there. We're not going to a commercial
Speaker 1: break now, are we, No, I know, But it's people.
Speaker 1: I mean, can you put any more ads on the uniforms?
Speaker 1: And English question? To what degree? Halfway established a bit
Speaker 1: of a false economy web by the advertiser believes that
Speaker 1: they're getting clicks and each month, but actually there's nothing
Speaker 1: behind it. So this is arguably the most important thing
Speaker 1: when it comes to UH. Well, a lot of the
Speaker 1: people I work with things that are focusing on it's
Speaker 1: things like viewability of ads. It's things like, uh, knowing
Speaker 1: that ads were actually engaging with consumers. Unfortunately, the industry
Speaker 1: is really good at optimizing trees and not so good
Speaker 1: at optimizing forests. And what that means practically is, uh,
Speaker 1: there's a focus on keeping costs down, which means quality
Speaker 1: may also go down. It's really hard to justify that.
Speaker 1: Let's just say you're you could own the entirety of
Speaker 1: an AD block, and maybe that AD block maybe a
Speaker 1: thirty second block instead of two minutes. That might be
Speaker 1: worth five times or ten times as much. The problem
Speaker 1: is so much of the industry so focused on the
Speaker 1: cost per unit, and that focus on the individual unit
Speaker 1: is a big problem and we actually need to in
Speaker 1: my position, we need to help marketers think more holistically
Speaker 1: about how to optimize the entirety of what they're doing.
Speaker 1: So it is a problem, and I think people might
Speaker 1: try to helps is that the Pluck go the distance
Speaker 1: radio is a really strong media. Actually all seriousness, I mean,
Speaker 1: but that's a good example that radio and audio more
Speaker 1: generally speaking, is something that more markers should be thinking of.
Speaker 1: Stop they're doing. I mean, we have been humbled by
Speaker 1: the success of our podcast. John and I collectively fell
Speaker 1: off the chair when Bank of America first stepped up
Speaker 1: and said we believe in your project, Apple Music, Spotify
Speaker 1: and the whole thing. There's Brian, They're doing audio because
Speaker 1: they don't have tough time to score around with video. Right. Well,
Speaker 1: I think that frankly that because television and video based
Speaker 1: advertising it is expensive at a per unit basis, is
Speaker 1: perceived as being cluttered. Uh. There is a real problem,
Speaker 1: especially with younger audiences, in terms of reaching them on
Speaker 1: traditional TV. You're reaching frequency curves look all out of whack.
Speaker 1: There's a lot of interest in audio. Now that said,
Speaker 1: I could have said that five years ago, and radio
Speaker 1: broadly to find early grew right. There's a shift to
Speaker 1: spend to Spotify, Pandora to some degree, but the industry
Speaker 1: collectively didn't grow. That said, we can still advocate for Hey, Marketer,
Speaker 1: if you haven't thought of this, you really need to.
Speaker 1: Let's talk about the privacy scandal that has engulfed the
Speaker 1: likes of Facebook over the last twelve months. How does
Speaker 1: that change things for your clients? So every brand has
Speaker 1: to think whether they think or not they should be
Speaker 1: thinking about whether or not risks and rewards of working
Speaker 1: with any given media partner are worthwhile, right, and so
Speaker 1: when it comes to the privacy issues with Facebook in particular,
Speaker 1: but more generally, we call it brand safety, right, Uh,
Speaker 1: brands have to consider if their association with a media
Speaker 1: owner has a negative effect or if because the consumer
Speaker 1: might see that they might be self loathing essentially, and
Speaker 1: while they're consuming the medium, think I hate being on
Speaker 1: this medium and I hate the advertisers who are making
Speaker 1: this possible. I mean, that can happen, but more generally, UH,
Speaker 1: there's a risk of association with media owners too, in
Speaker 1: the mind of people who are not using the platform right,
Speaker 1: enabling bad behaviors, enabling societal problems, whatever. Every brand has
Speaker 1: to consider whether or not their brand is tarnished by
Speaker 1: any association. The vast majority of advertisers have not considered
Speaker 1: that they are negatively impacted at this point in time.
Speaker 1: But that is the way to think about it. Again,
Speaker 1: even in my prior role, I still would have said
Speaker 1: Facebook and the lights are going to keep growing, because
Speaker 1: that's not a connection. That's let's think about private data
Speaker 1: as a currency. At some point, private datoris a currency
Speaker 1: is going to become so expensive that the advertiser and
Speaker 1: advertising incrementally is going to have to get more expensive.
Speaker 1: Let's say, yes, Okay, now I see what you're saying.
Speaker 1: So I would argue that every brand needs to make
Speaker 1: sure that if they can't persuade a consumer to supply
Speaker 1: willingly their data to the brand for use in targeting,
Speaker 1: they probably don't deserve it. And that goes back to
Speaker 1: the whole idea. What is a brand? Of brand is
Speaker 1: supposed to be a mark of trust. Of brand is
Speaker 1: supposed to be a mark of why a consumer should
Speaker 1: want to engage. You think, Feral thinks this is an interview.
Speaker 1: You're here to consult. What does radio need to do
Speaker 1: to stay red. It's fiber right now. I mean, come on,
Speaker 1: give me some thought leadership on how to drive Bloomberg
Speaker 1: surveillance forward over the next five years. Oh yeah, I know,
Speaker 1: i'd focus. Well, I mean, I'm going to bridge these
Speaker 1: two comments here because to the extent that if you
Speaker 1: can imagine a world where concerns around privacy are enhanced,
Speaker 1: where laws and regulations are more pronounced with respect how
Speaker 1: data is shared, and the relative advantage of using different
Speaker 1: media will evolve. Radio doesn't quite have that issue, at
Speaker 1: least traditional audio. Now that said, I think that every
Speaker 1: advertiser wants to find ways to use data that they have.
Speaker 1: I would argue an advertiser's best position to do gather
Speaker 1: a ton of data on the insights of consumers using
Speaker 1: a given media, use a ton of data on the
Speaker 1: output of an impact, and then let the art take
Speaker 1: the work in the middle. Yeah, we did all that
Speaker 1: and we come up with John's TV platform. The real yield.
Speaker 1: I mean, they saw a pure fixed income. That's all
Speaker 1: that one of the Brian Weezer. This has been painful.
Speaker 1: Thank you so much as well. Congratulations. Do you know
Speaker 1: what I'm you have no idea. Yeah, Field of Dreams, okay,
Speaker 1: Radiota out of the corn field. No, no idea, Okay,
Speaker 1: thank you, I mean it works. Brian Weezer, thank you
Speaker 1: so much. I'm sorry, but I think this. Yeah, that's
Speaker 1: a baseball movie. You have seen that movie. Okay, But anyways,
Speaker 1: just as really the association is is you just you
Speaker 1: work into it. It's like you don't it's heaven. No,
Speaker 1: it's Bloomberg surveillance. And we almost went with that phrase.
Speaker 1: I have been so so so waiting for this conversation.
Speaker 1: We're gonna go for you two hours NonStop. I'm kidding,
Speaker 1: of course, but we're gonna carve out on a Friday,
Speaker 1: clear language on what's all the rage. And it may
Speaker 1: be one you're in nanotechnology and this, that and the other,
Speaker 1: but once again it is the use and abuse of
Speaker 1: the phrase artificial intelligence. All of this goes back to
Speaker 1: a meeting in nineteen at Dartmouth College where the the
Speaker 1: brains of Pittsburgh showed up from the University of Pittsburgh
Speaker 1: in a small school called Carnegie Mellon University and Allen
Speaker 1: Newell and her Herbert Simon and other giants. Actually, he
Speaker 1: tried to figure out how we would handle computers and machines.
Speaker 1: Flash forward and out of Pittsburgh at n y U
Speaker 1: as vacant dar and he joins us this morning. We
Speaker 1: are honored to have you here, professor. There's so much
Speaker 1: to straighten out here. What is most wrong in the
Speaker 1: new vogue of artificial intelligence is it's covered by the media.
Speaker 1: What drives you nuts the most? Um? Really happy to
Speaker 1: be here, Tom, And incidentally, Hope Simon was one of
Speaker 1: my mentors and graduate school and on my thesis committee,
Speaker 1: so I was honored to have him um and get
Speaker 1: to know him. I think AI has seen several hype
Speaker 1: cycles lost four decades full disclosure, my brother was in
Speaker 1: one of them. Continued, So you know we've so so
Speaker 1: I've seen several of these hype cycles during my career,
Speaker 1: and h we're seeing another one at the moment. What
Speaker 1: do we get wrong? What's the hype that drives you nuts? Well,
Speaker 1: you know the by the way, I think this one
Speaker 1: is different, right, So as just want to qualify that.
Speaker 1: But I think the there's a lot of misunderstanding that
Speaker 1: AI will solve everything that machines have, you know, will
Speaker 1: have become incredibly intelligent and they'll replace us. And you
Speaker 1: know that may well happen in the very long term,
Speaker 1: but I think that we ought to have some somewhat
Speaker 1: muted expectations. I mean, we've certainly come a long way,
Speaker 1: but I think we have a really long way to
Speaker 1: go go. Jack Clark, writing for Bloomberg four years ago, says,
Speaker 1: this time is different. You just alluded to that what's
Speaker 1: different now within artificial intelligence or these machines running our lives.
Speaker 1: So I think what's what's different now is that we've
Speaker 1: made a dent in solving perception kinds of problems. So
Speaker 1: machines have gotten a lot better at seeing, hearing, getting
Speaker 1: better at reading um And I think what that does
Speaker 1: is it changes the nature of interaction with the machine.
Speaker 1: The machine can now ingest inputs directly from the environment
Speaker 1: instead of them being formatted in a way and structured
Speaker 1: in the way that it can understand. Right, So it's
Speaker 1: able to deal with more instructured kind of input like
Speaker 1: humans are. And and that's interesting in many domains, including healthcare.
Speaker 1: But you can look at images and stuff like that.
Speaker 1: But in your high school math in India, I'm sure
Speaker 1: you got to this quickly. Linear regressions and you've got
Speaker 1: a signal on the back end, which is that risk
Speaker 1: that's out there, that unknowable that's out there. We're all
Speaker 1: living this right now with the emotion of two plane
Speaker 1: crashes over software in a cockpit that just flat out
Speaker 1: didn't work. That's certainly what the FAA is getting too quickly.
Speaker 1: Is there a new reliance on machines and on computer
Speaker 1: technology where that risk, that sigma it becomes too unknowable. Well,
Speaker 1: you know, you're you're raising an incredibly important question. And
Speaker 1: you know, one of my questions really is when do
Speaker 1: we trust machines? And the way I look at trust
Speaker 1: is in terms of risk. In my mind, it boils
Speaker 1: down to how often will the machine be wrong? And
Speaker 1: what are the consequences when the machine is wrong? Things
Speaker 1: like drive a less cars, autopilot. The consequences of era
Speaker 1: are severe. Uh. And so those kinds of decisions tend
Speaker 1: to be particularly sensitive. When they talk about handing control.
Speaker 1: You're in class throwing chalk at somebody at n WANT.
Speaker 1: You're the dumbest kid in engineering n y U. And
Speaker 1: if you look at the risk distribution, we all understand
Speaker 1: it's not gaussy and it's not a normal bell curve
Speaker 1: like the height of our high school class. It can
Speaker 1: be a goofy distribution or whatever, which is like if
Speaker 1: I paint ten thou BMW's one of them will be wrong.
Speaker 1: That's a lot different than airplanes crash exactly. What's what's
Speaker 1: different about airplanes and driver a less cars is you're
Speaker 1: not really interested in their distribution. You're not exactly gonna
Speaker 1: really interested in the average case. You're interested in the
Speaker 1: worst case. Right, it's that worst case Rumsfeldian unknown that
Speaker 1: you're really concerned about. That you may not have counter
Speaker 1: guy like you with the privileges studying with the CMU
Speaker 1: guys at Pittsburgh a million years ago. If if you
Speaker 1: look at these tech boys out and still these children
Speaker 1: out in Silicon Valley saying we're gonna do driverless cars,
Speaker 1: you've got in your head all those risks out there,
Speaker 1: When do we actually get driverless cars? Given how each
Speaker 1: of us perceives the next traffic accigen accident very slowly,
Speaker 1: is my prediction. I don't think this is going to
Speaker 1: happen overnight. I think we're going to have to get
Speaker 1: used to living with these new entities on the on
Speaker 1: the road. I think they'll be highly restricted to begin with,
Speaker 1: and we'll just have to wait and see what kinds
Speaker 1: of mistakes they make in the wild, which we haven't
Speaker 1: seen yet. Right, those are the unknowns that we have
Speaker 1: yet to see, and unless we see them, we're not
Speaker 1: going to trust them. The wild is the potholes on
Speaker 1: fifty nights. Exactly here, Anderic, if you're just joining us,
Speaker 1: v Sandar with us with an important conversation on all
Speaker 1: this uproar over AI. Okay, so we're gonna have driverless cars,
Speaker 1: and we've established the risks that are out there. There's
Speaker 1: a whole financial thing where now we're extrapolating out billions
Speaker 1: of dollars of equity value on hopes and dreams of
Speaker 1: the technology you're actually expert in, how do you respond
Speaker 1: to finance? This has a timeline of two years, where
Speaker 1: you've got a timeline at twenty years well in you know,
Speaker 1: in in finance. Um, it's you know, as strange as
Speaker 1: it may sound, this this is a an easier problem
Speaker 1: than uh than you know, automated and and and and
Speaker 1: uh you know, autopilot on cockpits, where the consequences of
Speaker 1: EA are really large. In finance, you can actually look
Speaker 1: at their you know, coming back to those distributions, they
Speaker 1: become important, right because you have to have expectations about
Speaker 1: how how often the machine will be wrong. But the
Speaker 1: time this is critical. The timelines, Professor are so different
Speaker 1: from experienced, grizzled guys like you versus what I hear
Speaker 1: from the tech crew. You're you're working on two different
Speaker 1: two regimes of time, aren't you. Yes. I think that
Speaker 1: it takes time to get used to looking at the
Speaker 1: behavior of these machines in any kind of domain. Um,
Speaker 1: And I think that one has to have expectations that,
Speaker 1: you know, when you build a machine to predict financial markets,
Speaker 1: you have to you had there's gonna be some time
Speaker 1: over which you have to observe its behavior to get
Speaker 1: comfortable with it as well. So I think, uh, you know,
Speaker 1: I think expectations have to be realistic. You can't just
Speaker 1: think about we're gonna have these intelligent machines making investment decisions.
Speaker 1: What's your timeline on self driving cars? You're starting with
Speaker 1: Mari Barr of GM who's all pumped up about this.
Speaker 1: She's a legit engineer. She gets the math. What's your
Speaker 1: timeline on self driving cars? To Mary Bar like I said,
Speaker 1: I think it depends on the evidence that we get
Speaker 1: from the wild right when when we actually start looking
Speaker 1: at these vehicles, uh, you know, we'll get some data.
Speaker 1: But if I were to sort of throw out a
Speaker 1: you know, a number out there, I'd say that we'll
Speaker 1: be looking at least five years before we can get
Speaker 1: comfortable that we have enough data to trust machines but
Speaker 1: driving us around. Thank you so so much. I would
Speaker 1: kill to have you together with one of that. But
Speaker 1: bring Jolson up at m I t the two of
Speaker 1: you together would just be lights out. It's dark. There's
Speaker 1: some n y you truly expertise in all the rage
Speaker 1: the vogue that is artificial intelligence. I think you can
Speaker 1: tell from my question, you know right right, maybe no
Speaker 1: artificial intelligence to tie a bow tie, Professor dar, thank
Speaker 1: you so much. Uptown into the west and it has
Speaker 1: been a flat lands for well over twelve fifteen years.
Speaker 1: Is called Hudson Yards for those you globally on the
Speaker 1: shores of the Hudson River, our Viviana hurtado is that
Speaker 1: the newly acclaimed Hudson Yards with six beautiful skyscrapers and
Speaker 1: a lot of hopes. Viviana, what is the major hope
Speaker 1: of this development of Hudson Yards. Well, you know it
Speaker 1: has been said Tom that this development Hudson Yards could
Speaker 1: very well shift the culture, the arts. Uh. You know,
Speaker 1: so much of the economic vibrancy of Manhattan to the
Speaker 1: West Side. And so today we are just about a
Speaker 1: less than an hour away from the real big kickoff
Speaker 1: half happening. Um. Certainly a lot of excitement. There has
Speaker 1: been music in my chest. But that's really the hope
Speaker 1: and the vision particularly so many people involved, as you
Speaker 1: were saying, over the course of fifteen plus years, but
Speaker 1: really today the show, the vision is going to belong
Speaker 1: to related in Oxford, Viviana. How much is still the
Speaker 1: vision and how much is actually actuality at this point?
Speaker 1: How much commerce? How much a residential space has been killed? Yeah, definitely.
Speaker 1: So right now what we're seeing is just about half
Speaker 1: of what is going to be the full Hussant Yards
Speaker 1: complex opening, So the public square and gardens is going
Speaker 1: to open. We know that there's residential half of that
Speaker 1: is going to be for sale, half of it is
Speaker 1: going to be rental. Uh, and there's going to be
Speaker 1: the commercial space as well that opens today with global
Speaker 1: brands being located there. Loreal USA, one of those big
Speaker 1: names that's taken up shop here. Speaking of taking up shop,
Speaker 1: we do have the shops and that's being anchored by
Speaker 1: Neiman Marcus, migrating from the big d of Dallas to
Speaker 1: the big Apple of New York City. But again, today
Speaker 1: marks what is only the half opening in many ways
Speaker 1: and opening, but only half the project. It's going to
Speaker 1: still be several more years until the full project is
Speaker 1: built and ringing in. By the way, guys, at twenty
Speaker 1: five billion dollars, Vivianna, I have to wonder, given all
Speaker 1: of the development in Long Island City, given all of
Speaker 1: the development downtown, is there enough demand for this? Well,
Speaker 1: that's the question on everybody's mind, right, Lisa, because the
Speaker 1: truth of the matter is we are living in a
Speaker 1: time where you have retail. We're just talking about retail
Speaker 1: and the shops opening up here anchored by Neiman. Well,
Speaker 1: this has not been a good retails season, has it, uh?
Speaker 1: And we know that here at least in Manhattan we
Speaker 1: saw the iconic Lord and Taylor Clothes Henry Bendel as well.
Speaker 1: They are making a very bold and a very big
Speaker 1: pitch here opening a bricks and mortar store when the market,
Speaker 1: certainly and the conventional wisdom is saying that that customers
Speaker 1: are migrating online, uh, and so that is going to
Speaker 1: be the big pitch what they are hoping, of course,
Speaker 1: and that with this shift uh that's going to come
Speaker 1: to the West Side, it's going to bring in a
Speaker 1: lot of foot traffic, uh, tourists who are going to
Speaker 1: be nearby at the high Line, as well as the
Speaker 1: people who are going to work and live here. And
Speaker 1: that it's going to really give uh this vibrancy and
Speaker 1: economic vibrancy to what some people are calling a vertical
Speaker 1: retail space. But that Lisa, you and I may remember
Speaker 1: as just being called them all Vivian or Toto, thank
Speaker 1: you so much to Hudson Yards overlooking the Hudson River.
Speaker 1: As well, I should tell you that Michael Bloomberg, the
Speaker 1: founder majority owner of Bloomberg LP, played a role in
Speaker 1: the development of the Hudson Yard project as Mayor of
Speaker 1: New York. Lisa Brown Winson, Tom Keenan, what we're gonna
Speaker 1: do here like I used to do a lot or
Speaker 1: and maybe we'll get back to it in two thousand
Speaker 1: nineteen as well, is find books where you go, you
Speaker 1: hate the author because you go, this looks so interesting,
Speaker 1: so good, I have to push seven other books aside
Speaker 1: and read it. You will do that with ten Caesar's
Speaker 1: because every time you've tried to do Roman history, your
Speaker 1: eyes have glazed over those high above Cayuga's waters in Ithaca.
Speaker 1: Have had the good fortune of ancient history for years
Speaker 1: with Barry Strauss. He's truly legendary within the study of
Speaker 1: Rome and bringing it to life, and he has succeeded
Speaker 1: in doing that with ten Caesar's. Roman Emperors from Augustus
Speaker 1: to Constantine. Barry, congratulations on the accessibility of ten Caesar's.
Speaker 1: But you've written seven other books or whatever on Rome.
Speaker 1: Why ten Caesar's. Well, thanks so much for the kind words.
Speaker 1: It's good to be hated, uh Tense Cazars. You know,
Speaker 1: I was interested in this subject ever since I saw
Speaker 1: I Claudius in the nineteen seventies, uh, and it really
Speaker 1: got me into the idea that there's something special about
Speaker 1: uh these Roman emperors, and they just had a remarkable
Speaker 1: ability to market themselves and make their own stories larger
Speaker 1: than anything else that was going on in the Roman
Speaker 1: world at the time. And I think that's one of
Speaker 1: the reasons we're still interested in them today. This is
Speaker 1: so important, But far more important is the fact Lisa
Speaker 1: Bramowitz has had forty seven cups of coffee in Rome
Speaker 1: and is completely up to speed on all this. She
Speaker 1: will read your book anxiously at waits the movie coming
Speaker 1: out in three years. Lisa jump in here with Professor Strauss. Well,
Speaker 1: it's it's it's not only fascinating from the personalities who
Speaker 1: made their stories larger than life, but this is the
Speaker 1: foundation of democracy as we know it. And I'm wondering
Speaker 1: with these ten Caesars, is there a unifying factor beneath
Speaker 1: their vibrant and diverse personalities. Oh yeah, I think that
Speaker 1: all of them were able to make change their friend.
Speaker 1: And you know, in a way, the model of the
Speaker 1: Roman Empire is one that comes from a more recent
Speaker 1: Italian novel, and that is, if we want things to
Speaker 1: stay the same, everything has to change. And these emperors
Speaker 1: really knew how to do it. They knew how to
Speaker 1: keep Rome Roman by making it less Roman. Ironically, is
Speaker 1: that may seem they moved the They're able to govern
Speaker 1: without Italy, without Rome, to bring new people into the
Speaker 1: elite um, and to accept change and I think that's
Speaker 1: one of the reasons why the empire lasted so long.
Speaker 1: One thing that I love about the book is the
Speaker 1: titles for each of the chapters, Vespassion, the Commoner, Nero
Speaker 1: the Entertainer, Tiberius the Tyrant. Which was your favorite Caesar
Speaker 1: to write about? I think Hadrian, you know, because he's
Speaker 1: so complicated. Uh he said, a combination of of good
Speaker 1: and evil, of you know, extraordinary talent and just cheer wickedness. Um,
Speaker 1: it's kind of hard to beat that. And also such
Speaker 1: a such a vast Kansas, from Hadrian's wall to Germany
Speaker 1: to Athens, to Jerusalem to North Africa. You know, he's
Speaker 1: just all over the place. Very stress for this. The
Speaker 1: book is tend Caesar's Roman Emperors from Augustus to Constantine.
Speaker 1: And of course we deliver this to your folks on
Speaker 1: March fifteen, The IDEs of March. Barry, when you teach
Speaker 1: the course, what is the thing that we get most
Speaker 1: wrong about the eyes of March? We use it, we
Speaker 1: say it, we do it constantly. Correct us, how should
Speaker 1: we interpret Roman IDEs of March? Oh? God, where to begin? Well,
Speaker 1: season wasn't killed on the capitol on the Capitol line,
Speaker 1: Hill um. And he wasn't killed in the senate as
Speaker 1: Shakespeare says. He wasn't killed in the senate house that
Speaker 1: we tourists see Rome. It all took place about half
Speaker 1: mile Oi and the law of Argentina if you're if
Speaker 1: you're walking around Rome. But I guess the biggest thing
Speaker 1: is that we think that Brutus and cash Us were
Speaker 1: the guys behind it, and Brutus is the one who
Speaker 1: has said who who betrayed Caesar? Well, you know, um,
Speaker 1: So I think the biggest thing actually is into Brute.
Speaker 1: Caesar never actually said it to Brute. He probably just
Speaker 1: groaned as he was being killeda said in Greek, you too,
Speaker 1: my son, which could have been a real insult if
Speaker 1: he actually said it. Because the room Caesar hadn't a
Speaker 1: head an affair with Brutus's mother, and the rumor was
Speaker 1: that Brutus was his illegitate son, and so Caesar saying
Speaker 1: in a way, you just killed your father and that's
Speaker 1: a terrible crime. According to Romo, just to see how
Speaker 1: stro just crushes our illusions. So much of this Lisa's
Speaker 1: Roman excitement. And I think of Darius Aria of the
Speaker 1: great filma film and photographer PBS who want me around
Speaker 1: Rome on. But for anybody who's not been to Rome
Speaker 1: your advantages read Barry Strauss ted Caesar's And what's so
Speaker 1: cool to me, Lisa is it just comes alive. It does.
Speaker 1: And of course these personalities are really colorful, Professor Strauss,
Speaker 1: I'd love to get your sins. As the Roman Empire
Speaker 1: progressed early Middle and then as it really was on
Speaker 1: the precipice of failure, how did some of the leaders
Speaker 1: fail to adapt to change in a way that gave
Speaker 1: it lasting power? How did they fail to adapt to change? Uh? Well,
Speaker 1: I you know, Diocletian would be a good example a
Speaker 1: failure to adapt. M He, like many Romans, after a
Speaker 1: half century of wars, invasions, defeats, epidemics, inflation, he thought
Speaker 1: there was a problem with the gods. You know, the
Speaker 1: gods just weren't on Rome side. And the way he
Speaker 1: looked at it is the way to save Rome was
Speaker 1: to get rid of the atheists, which is how he
Speaker 1: looked at the Christians, because they didn't believe in the
Speaker 1: Olympian gods. So he started the Great Prosecution of the Christians,
Speaker 1: which is quite terrible but also an utter failure. And
Speaker 1: in the end he had to admit defeat. He is
Speaker 1: succeeded by Constantine, who is the first Christian emperor, and
Speaker 1: turns it around and says, yeah, you're right, we do
Speaker 1: have a problem with the gods. But the solution is
Speaker 1: not doubling down on the old religion. It's accepting a
Speaker 1: new religion, UM and he sets the empire on the
Speaker 1: road to becoming Christian and also to surviving. So I
Speaker 1: think Clesia's an example of somebody who tried to dig
Speaker 1: his heels into the past and it just wasn't going
Speaker 1: to work. One other aspect that I love about the
Speaker 1: book is your highlighting of women and the relationships of
Speaker 1: some of the powerful women and the ten Caesar's throughout
Speaker 1: these three hundred plus years. Can you talk a little
Speaker 1: bit about that. Yeah, you know, we the Romans were
Speaker 1: definitely macho and sometimes misogynistic, and we tend to just
Speaker 1: focus on the men. But all of these emperors, beginning
Speaker 1: with Augustus, knew that in order to be successful, UH,
Speaker 1: they would also have to reach out to women. Augustus
Speaker 1: is married to Olivia for fifty four years. It's one
Speaker 1: of the most interesting partnerships between UM two powerful people
Speaker 1: in history. Um august Olivia was a Roman noble. She
Speaker 1: wasn't just Augustus's wife, but she was his advisor. He
Speaker 1: consulted her, he brought her with her when he traveled
Speaker 1: around the empire. She was very shrewd um and they were.
Speaker 1: They were a true power couple working together. Then we
Speaker 1: find some others like Vespasian, who rises from being a
Speaker 1: commoner to being emperor, and he's very much helped by
Speaker 1: the fact that his mistress is a slave woman who
Speaker 1: is working for UM, one of the top imperial women,
Speaker 1: UM caligulous grandmother, Claudius's mother and Antonia. She helps Vespasian
Speaker 1: and ultimately he becomes emperor. He's now a widower, she
Speaker 1: becomes his common law wife. So it's stories like that
Speaker 1: and like that. Who really gives we have more to
Speaker 1: talk about. We're gonna have to have you back here
Speaker 1: to get through another seven uh emperors as well ten
Speaker 1: Caesar's Roman Emperors from Augustus to Constantine. It is shockingly accessible.
Speaker 1: I think of Robert Hughes Classic Rome and many many
Speaker 1: other books, and you get through them. But Barry Strauss
Speaker 1: just said, does it incredibly well? In course, you remember
Speaker 1: him as author of the Death of Caesar, whos did
Speaker 1: so well as well ten Caesar's from Cornell's Barry Strauss.
Speaker 1: We thank him today. Thanks for listening to the Bloomberg
Speaker 1: Surveillance podcast. Subscribe and listen to interviews on Apple Podcasts, SoundCloud,
Speaker 1: or whichever podcast platform you prefer. I'm on Twitter at
Speaker 1: Tom Keane before the podcast. You can always catch us worldwide.
Speaker 1: I'm Bloomberg Radio.