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Speaker 2: Bloomberg Intelligence with Alex Steinel and Paul'sweeny on Bloomberg Radio.
Speaker 3: On Today's Bloomberg Intelligence Show, we dig inside the big
Speaker 3: business stories impacting Wall Street and the global markets.
Speaker 4: Each and every week, are going to provide in depth
Speaker 4: research and data on some of the two thousand companies
Speaker 4: and one hundred and thirty industries our analysts cover worldwide.
Speaker 3: Today, we'll look at why Apple says it's iPhone sales
Speaker 3: in China are falling.
Speaker 4: Plus we're going to dive into the world of art
Speaker 4: intelligence and how it's going to impact job organizations going forward.
Speaker 3: But first we'll begin in the retail sector. Earlier in
Speaker 3: the week, Target reported fourth quarter profit that beat analyst expectations.
Speaker 4: So this comes as the company reduced its stockpile of
Speaker 4: merchandise by about twelve percent during the quarter. So Target
Speaker 4: also confirmed it's going to launch a paid membership program,
Speaker 4: going up against rivals like Amazon and Walmart.
Speaker 3: For more, co host Bailey Lipschutz and I were joined
Speaker 3: by Jennifer bartashis Bloomberg's senior retail analysts. Were first asked
Speaker 3: Jennifer why investors are excited about Target.
Speaker 5: They've really revealed their plan for growth over the next
Speaker 5: several years and that is resonating well with investors, and
Speaker 5: it's all about recapturing top plane growth, traffic, market share,
Speaker 5: and they're a little bit more upbeat on where they
Speaker 5: see the consumer right now.
Speaker 6: And when we look at inventory being an issue that
Speaker 6: was such a big problem for Target during the pandemic,
Speaker 6: it does seem like that's being worked through. Kind of
Speaker 6: what's your expectation with how Target is handling their inventory
Speaker 6: ahead of schedule or not a head schedule.
Speaker 5: Yeah, they've done a major pivot with inventory, and obviously
Speaker 5: they had huge issues a couple of years ago with markdowns,
Speaker 5: and they've really been able to write size inventory that's
Speaker 5: shown up where inventory right now is actually lower than
Speaker 5: it was last year, and yet in stocks are better
Speaker 5: than they've been. That focus on those retail fundamentals of
Speaker 5: making sure that you have things in the stores and
Speaker 5: in stock has really been playing through and driving some
Speaker 5: of the results that they've seen, and a lot of
Speaker 5: that stems from inventory. And so right now they're very
Speaker 5: well positioned going into twenty twenty four and that should
Speaker 5: hopefully be a tailwind for them for the rest of
Speaker 5: this fiscal year.
Speaker 3: An Affinity Card, can you explain what's going on there?
Speaker 5: They're kind of reimagining their loyalty program. So the baseline
Speaker 5: was Target Circle, which was free to join, and they
Speaker 5: have one hundred million users that have joined it, and
Speaker 5: that's where you can go in and save different offers
Speaker 5: and you get an extra ten percent off your paper
Speaker 5: towels you know that week and that brand. What they're
Speaker 5: doing is they're making it so you don't have to
Speaker 5: search and save. You get the things automatically when you
Speaker 5: check out, and if you're a Red Card holder, for
Speaker 5: forty nine dollars, you can get unlimited free delivery, same
Speaker 5: day free delivery to your house and they're calling this
Speaker 5: Target three sixty. You can also subscribe to just that
Speaker 5: if you're not a Red Card holder. Also an introductory
Speaker 5: price of forty nine, but it will go up over time,
Speaker 5: although they didn't say to what. So it's a move
Speaker 5: where they're trying to get, you know, a little bit
Speaker 5: deeper into consumers' lives, you know, doing more home delivery.
Speaker 5: There's some additional perks in there where you can access
Speaker 5: all of what Ship does, which is their same day
Speaker 5: delivery service, and that includes being able to shop at
Speaker 5: other retailers. So that's kind of the differentiator here with
Speaker 5: regards to the membership program that once you have it,
Speaker 5: you could also have your Target run include something from
Speaker 5: Costco for example. But it's early days and we'll see
Speaker 5: how much appetite consumers have for yet another membership that
Speaker 5: they have to pay for.
Speaker 6: Well, what are your expectations on that? Because I feel
Speaker 6: like everyone pays for Amazon Prime and Walmart Plus I
Speaker 6: know has had a strong roll out and has partnerships
Speaker 6: with different credit cards. Like, what can Target really do
Speaker 6: to get people to pay another annual fee when it
Speaker 6: seems like, at least looking at the streaming platforms they're
Speaker 6: struggling to maintain users.
Speaker 5: It's a great question, and I think that's one of
Speaker 5: the big questions that we're going to need to see
Speaker 5: as they really talk about what differentiates this program, because
Speaker 5: you know, forty nine dollars is cheap, but it is
Speaker 5: an introductory price, and there are a lot of people
Speaker 5: out there that do delivery, and so you know, when
Speaker 5: I look at it, I think in order for it
Speaker 5: to be a successful program, they're going to have to
Speaker 5: really do something extraordinary that appeals to people to prompt
Speaker 5: them to pay extra And historically, you know, Target's formula
Speaker 5: for success has never been mimicking others. It's been about
Speaker 5: kind of forging their own path. And I think this
Speaker 5: is an example where it's going to be very very
Speaker 5: important for them to do that. But it's not clear
Speaker 5: yet how that's going to be realized.
Speaker 6: And how does Target play into a recession. Are they
Speaker 6: one of the companies that can weather the storm because
Speaker 6: of their loyalty or how does that play out just
Speaker 6: given their typical demographics.
Speaker 5: If there is a recession. With their typical demographics, Target's
Speaker 5: customer base is extremely loyal, but Target's product mix does
Speaker 5: skew to more discretionary items, and so whenever there's a
Speaker 5: pullback and spending, it tends to have an outsized impact
Speaker 5: on Target versus other big box retailers. Now, Target has
Speaker 5: been really focused in the last eighteen months, especially on value.
Speaker 5: They've launched some new private label brands that are meant
Speaker 5: to be the cheapest option in every category in the store.
Speaker 5: So they're trying to respond to that. So they have
Speaker 5: the breadth of category and they have the loyalty of
Speaker 5: consumers that they can weather a recession, but it will
Speaker 5: make it harder for them to get back to that
Speaker 5: top line growth and that expansion of margin that they're
Speaker 5: talking about if we find ourselves in the midst of
Speaker 5: a recession.
Speaker 3: Hey, Jen, how do I differentiate how much shopper between
Speaker 3: Target and Walmart?
Speaker 5: It's all about perception, right When you think about Walmart,
Speaker 5: it is usually about lowest price. Walmart is a EDLP.
Speaker 5: Every day you get the lowest possible price. They've got
Speaker 5: a very big assortment and they have some perks with
Speaker 5: regards to their Walmart Plus program. When people think of Target,
Speaker 5: they think a little bit more of discovery, They think
Speaker 5: a little bit more about inspiration than functionality, and that's
Speaker 5: where you really see the divergence between those two retailers.
Speaker 6: I will say, when I go to Target, I always
Speaker 6: end up buying more than I want, where if I
Speaker 6: go to Walmart, I'm kind of in and out. Jen
Speaker 6: question off of that comparison, I always talk up the
Speaker 6: fact that Walmart owned Sam's Club. When you look at
Speaker 6: the company makeup, how much does that differentiate Walmart versus
Speaker 6: some of the other peers, just given as you mentioned
Speaker 6: Target potentially partnering with Costco if you're using their membership card.
Speaker 5: Yeah, so obviously there's a great benefit to Walmart of
Speaker 5: having both it's US Walmart stores as well as the
Speaker 5: Sam's Club stores, because they really can capture spending by
Speaker 5: different groups of people and for different shopping reasons. Now,
Speaker 5: when I talked about shipped, it's not so much that
Speaker 5: you get the benefits of a Costco membership, for example,
Speaker 5: with Target. It's just more that you can have your
Speaker 5: delivery person pick up purchases from other retailers, which is
Speaker 5: something that isn't in vetted in a Walmart program, for example.
Speaker 5: But that Target membership fee is going to be competing
Speaker 5: with your Costco membership fee. It'll be you know, competing
Speaker 5: with a bjays membership fee along with all of your
Speaker 5: streaming services and everything else out there. So you know,
Speaker 5: Walmart definitely benefits from the scale of having both the
Speaker 5: course stores and Sam's Club, but it is a little
Speaker 5: bit of a different business model than what we're talking
Speaker 5: about with Target.
Speaker 7: Oh.
Speaker 3: Thanks to Jen Bartashis Bloomberg Intelligence senior retail analysts.
Speaker 4: All right, we turned out a big tech So this
Speaker 4: week we learned that Apple iPhone sales in China fell
Speaker 4: by a surprising twenty four percent. Now this was over
Speaker 4: the first six weeks of twenty twenty four. Those figures
Speaker 4: came from the Counterpoint Research firm.
Speaker 3: For more on this, co host Bailey Lipshaltz and I,
Speaker 3: we're joined by anaag Rana, Bloomberg Intelligence Senior technology analyst.
Speaker 3: We first asked Anurag what's causing this to decline in
Speaker 3: the early part of twenty twenty four.
Speaker 8: This is the same story that's been going on for
Speaker 8: the last six to nine months, ever since Wallwei released
Speaker 8: their higher end phone last year. So Apple's been losing
Speaker 8: market share there that has been you know, you could
Speaker 8: say opened or coupled with consumer weakness in China. And
Speaker 8: it's all that's you know, driving these problems right now.
Speaker 6: When I look at the PGEL function on the terminal,
Speaker 6: iPhone accounts for more than half of Apple's revenue China
Speaker 6: call it a fifth of their sales anak. When you
Speaker 6: look at those numbers, what does this actually mean for
Speaker 6: Apple if they're going to see that competition eating into
Speaker 6: their sales.
Speaker 8: Yeah, I think it's going to be a tough time
Speaker 8: for Apple in China for that at least this year
Speaker 8: and maybe into next year before they can, let's say,
Speaker 8: make some inroads in India and other markets. Emerging markets
Speaker 8: is the real growth driver for Apple, there is no
Speaker 8: two ways about it. And and you know iPhone is
Speaker 8: the big growth driver. So if phones are not selling
Speaker 8: in China, that's a problem for Apple. It means numbers
Speaker 8: need to come down even more for Apple this year.
Speaker 8: You know, we saw about double digit sales drop in
Speaker 8: China last quarter. I looked up on MDL consensus is
Speaker 8: about seven percent drop in China for this quarter. I
Speaker 8: think that number needs to creep up to someone in
Speaker 8: the low double digit decline going forward. It's a painful
Speaker 8: situation for Apple, and frankly, there aren't at many rosy
Speaker 8: things looking forward, at least for twenty twenty four.
Speaker 3: So I guess the biggest concern for Apple obviously is competition,
Speaker 3: because they haven't really had that robust of a competitor
Speaker 3: and they're part of the market. Are there any responses
Speaker 3: Apple can make here from a competitive landscape other than
Speaker 3: lowering the price point?
Speaker 8: Yeah, Paul, I think there is a little more hype
Speaker 8: in that competition news than reality only because Huahwei didn't
Speaker 8: release a phone for many years, So that you can
Speaker 8: think about it. If you have an install base of
Speaker 8: WAWE phones. I mean, let's say you know that's X
Speaker 8: and that hasn't been updated for four or five six years,
Speaker 8: and you just certainly get a brand new phone. All
Speaker 8: of those people are going to go and refresh that,
Speaker 8: So I think you should take that as a bigger factor,
Speaker 8: plus the subsidies they are getting in China from the
Speaker 8: local providers. So I think Apple will do okay in
Speaker 8: China over the long term. But I think that's not
Speaker 8: going to be a twenty twenty fourth story.
Speaker 6: And you mentioned emerging markets as the next driver. What countries,
Speaker 6: what regions are going to be able to pay up
Speaker 6: for what I would say, is quite an expensive phone.
Speaker 8: Yeah, I think that's the most important question, and I
Speaker 8: think you know, just by the sheer size of it,
Speaker 8: India is the next one. But frankly speaking, right now,
Speaker 8: Apple doesn't even operate in you know, five percent of
Speaker 8: the entire market because of the price point of the phone.
Speaker 8: I think the strategy India is going to be a
Speaker 8: mix of the lower phone the se as well as
Speaker 8: the refurbished phone where the price point is even lower.
Speaker 8: But having said that, I think India is a developing country.
Speaker 8: The middle class is getting more richer, so I think
Speaker 8: that's going to be the next big growth catalyst. But
Speaker 8: this is it's not going to play out in twenty
Speaker 8: four to twenty five. That's more of a I would
Speaker 8: submit to long term story.
Speaker 3: We've talked about this before that Apple might introduce a
Speaker 3: lower price phone into India for just that reason. Is
Speaker 3: that something they're still considering or will they just wait
Speaker 3: for the market to kind of move up to where
Speaker 3: the Apple phone price point is.
Speaker 8: I think it's going to be the latter. I've done
Speaker 8: a lot of analysis of how much share they can
Speaker 8: gain if they drop the S price by fifty dollars
Speaker 8: hundred dollars, and you know, when I publish that stuff,
Speaker 8: I think they actually raise the price by fifty bucks.
Speaker 8: So they don't believe in dropping prices. They are more
Speaker 8: on a margin story. So think of Apple more on
Speaker 8: the long term basis right now, not on the short term.
Speaker 8: I don't think they're going to you know, I would
Speaker 8: say swap margins for market share. They've never done that
Speaker 8: in their history, whether it was on the mac side
Speaker 8: or on the phone side.
Speaker 6: And quickly anorak, I look at the news, there's no
Speaker 6: more Apple car. There's tepid reception to the vision pro
Speaker 6: What actually drives the stock, what drives sales in the
Speaker 6: next twelve to eighteen months.
Speaker 8: Yeah, I think that's the most important question for Apple investors.
Speaker 8: And I think there's going to be an event in June,
Speaker 8: the World Wide Developers Conference, where they have pledged that
Speaker 8: they're going to show a lot of AI enhancements to
Speaker 8: the operating system. I think that really is the one
Speaker 8: wildcard that can completely change the sentiment of the company,
Speaker 8: both in terms of sales and the gloomy investor sentiment
Speaker 8: only because remember, Apple has a distribution network that stands,
Speaker 8: you know, next to nobody out there in terms of
Speaker 8: you know, affluent people using their phones. More than one
Speaker 8: billion devices connected just on the smartphone. I think that
Speaker 8: really is the big driver. One of the things I
Speaker 8: was thinking about was if you go back, you know,
Speaker 8: five years, seven years, there were apps such as trip
Speaker 8: Advisors an Yelp where people used to go for their
Speaker 8: you know, specialized functions for restaurant advices and tourism. But
Speaker 8: when you look at somebody like Google, a lot of
Speaker 8: that traffic has moved on to them because they control
Speaker 8: the distribution. I think Apple has the same ability, but
Speaker 8: they have to show up with some AI products otherwise
Speaker 8: that's not going to.
Speaker 3: Flow our Thanks to Ana rog Rana Bloomberg Intelligence Senior
Speaker 3: Technology Channels, I com.
Speaker 4: Going to bring a break down the role of AI
Speaker 4: in sports analytics.
Speaker 3: You're listening to Bloomberg Intelligence on Bloomberg Radio, providing in
Speaker 3: depth research and data on two thousand companies and one
Speaker 3: hundred and thirty industries. You can access Bloomberg Intelligence v
Speaker 3: A BI. I go in the terminal, I'm Paul Swimming and.
Speaker 4: Am Alex Steel and this is Bloomberg.
Speaker 2: You're listening to the Bloomberg Intelligence podcast. Catch us live
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Speaker 2: Android Auto with the Bloomberg Business App. Listen on demand
Speaker 2: wherever you get your podcasts, or watch us live on YouTube.
Speaker 4: Earlier in the week, Bloomberg Intelligence broadcasted live from the
Speaker 4: campus of the New Jersey Institute of Technology. Paul was
Speaker 4: pumped and the main topic of conversation was AI.
Speaker 3: We took a look at zealous Analytics and Austin based
Speaker 3: sports analytics company that evaluates, predicts, and improves player and
Speaker 3: team performance in sports.
Speaker 4: So one of our guests was Evana Serk, senior product
Speaker 4: scientist at Zealis Analytics, and we asked Havana how Zealos
Speaker 4: uses AI in sports.
Speaker 1: This field that has expanded in last maybe ten years
Speaker 1: of a lot in other sports. Even before that, it
Speaker 1: was in baseball that was one of the first sports.
Speaker 1: If you've seen Moneyball, that's that's really yes.
Speaker 4: Yeah, okay, the moneyball Okay. And so it's basically like
Speaker 4: how to position, like what players to put where combinations?
Speaker 4: Is it that kind of stuff?
Speaker 1: Correct? Correct? So, so player evaluation in game decision strategy,
Speaker 1: that's sort of sort of things. Yeah.
Speaker 3: So again, played for your starter for nja's basketball. You
Speaker 3: also represented your native Croatia and youth basketball. So you're
Speaker 3: great at basketball, but you're also a math nerd to
Speaker 3: the nth degree. She got a BS and a pH
Speaker 3: degree and applied mathematics from njiit focusing on computational fluid dynamics.
Speaker 4: I don't know what that means.
Speaker 3: I don't know what that means. That's art, but okay,
Speaker 3: I don't know. So a great mathematician, great basketball player.
Speaker 3: Let's put it all together. What are some of the
Speaker 3: really good applications for some of that technology we've seen?
Speaker 3: You mentioned moneyball for you know that we've seen it
Speaker 3: in baseball. What other applications are out there that you think?
Speaker 3: It seems like we're in the very early innings of that.
Speaker 1: Early on, it started with just using basic data, so
Speaker 1: box scores, play by play, and then a lot of
Speaker 1: sports in recent years have a what's called player tracking data,
Speaker 1: meaning we have locations of the players on the court
Speaker 1: or on a pitch, on a field, whichever sport we're
Speaker 1: talking about, at a high resolution. So from that data
Speaker 1: we can extract not only things that are counted in
Speaker 1: a box score, but also other things that happened during
Speaker 1: the game that you wouldn't see counted in like a
Speaker 1: basic box score for example.
Speaker 4: What are some of the common questions that like coaches
Speaker 4: or owners come to you with the.
Speaker 1: Biggest question is how do we value players? How do
Speaker 1: we find which players teams should sign, how long of
Speaker 1: a contract, how much money should be on a contract.
Speaker 1: That's one side, So that's the player evaluation side, and
Speaker 1: then the other side is coaching and in game decision making.
Speaker 1: So which situations are producing the most value for the teams?
Speaker 1: Which situations are creating better opportunities to score?
Speaker 3: I know, like in baseball, major league baseball and in
Speaker 3: minor league baseball. Now it's coming into all the other
Speaker 3: parts of baseball. The analytics people, the data people versus
Speaker 3: maybe some of the more traditionalists. They kind of butt
Speaker 3: heads on occasion. So how much chanalytics do you use
Speaker 3: versus just my gut I think this player will do well.
Speaker 3: How do you kind of bridge that topic?
Speaker 1: Yeah? Yeah, So that's that's a big important thing, because
Speaker 1: you can just have data without the domain expertise. And
Speaker 1: I think that's something that we Adzealas have a really
Speaker 1: good strength, is that we have the experts in data
Speaker 1: and statistics in AI in machine learning. But we also
Speaker 1: have a lot of people who worked in sports teams
Speaker 1: and have that sort of experience and know which questions
Speaker 1: the teams want to answer, what's useful for them, and
Speaker 1: how can we help them best.
Speaker 4: So yeah, because when you were saying what AI could
Speaker 4: help you do, it feels like that's not what a
Speaker 4: coach is supposed to do. But you're saying that you
Speaker 4: need someone to interpret how to manage that and stuff.
Speaker 1: Right, right, So you need like a bridge between the
Speaker 1: data and what's what's happening on the court.
Speaker 3: All right, If I'm an agent representing a player, now
Speaker 3: this is I got to learn this stuff because the
Speaker 3: team's gonna come at.
Speaker 4: Me and say, this is what the program tells me.
Speaker 3: That, Yeah, your client's worth blank because his or her
Speaker 3: OPS is this and blah blah blah blah blah, And
Speaker 3: you got to come back and say, no, I think
Speaker 3: he's better than that, and I think he's really more.
Speaker 3: So do you work with the agents and players themselves
Speaker 3: as well, because they better be smart on this stuff.
Speaker 1: Yeah, Yeah, that's it's a great area where where ZELS
Speaker 1: is growing as well in some of our sports. But
Speaker 1: but Yeah, an agent cannot learn all of this on
Speaker 1: their own, so having a company or a contractor who can.
Speaker 3: So do you guys work with agents and players directly.
Speaker 1: In certain sports?
Speaker 4: Yes, yeah, but not all across the board. So you also,
Speaker 4: as Paul was mentioned earlier, you got your BS and
Speaker 4: your PhD in applied mathematics and nj T. Because we're
Speaker 4: here and we're talking about NJIT kind of bridges the
Speaker 4: gap between learning stuff and then putting it out into
Speaker 4: the world. How did this help you evolve your career
Speaker 4: and leave you where you are today?
Speaker 3: Yeah?
Speaker 1: Even though I studied competitional fluidnamics, it's not exactly data science,
Speaker 1: but I've learned a lot of skills.
Speaker 4: There were transitions, by the way, so you can pretend
Speaker 4: it is.
Speaker 1: There's a little skills that transfer from from one field
Speaker 1: to the other, for example, coding, analyzing large data sets,
Speaker 1: creating visualizations, and communicating scientific results to regular audience.
Speaker 3: Are there some sports that are embracing AI or just
Speaker 3: technology analytics more than others?
Speaker 1: That's historically in baseball, particularly because they had more advanced
Speaker 1: data for the longest time, But other sports now also
Speaker 1: have the player tracking data and are starting to get
Speaker 1: more on that side.
Speaker 4: How did you wind up in this? Because if you
Speaker 4: played basketball, right, because you're originally from Croatia, right, So
Speaker 4: you played basketball and then you somehow wound up and
Speaker 4: deep into analytics. How did you do that?
Speaker 7: Well?
Speaker 1: I always loved math and I always loved basketball, and
Speaker 1: this was a perfect combination of the two.
Speaker 3: Where are we do you think in terms of the
Speaker 3: evolution of applying data and AI to sports? Because it
Speaker 3: just the statistics. I've been following sports my entire life,
Speaker 3: and I'm listening to a broadcast and they're saying stuff.
Speaker 3: I have no idea what they're talking about, Like now
Speaker 3: batting average is an important anymore to baseball and now
Speaker 3: it's on bass plus slugging. I don't know. I mean,
Speaker 3: it seems like we need a tutorial a lot of
Speaker 3: these broadcasts. Where can this go? Do you think?
Speaker 1: Yeah? I wouldn't know about baseball because I don't really
Speaker 1: understand the rules coming from Croatia. But in basketball, we
Speaker 1: you know, from now we have a player location data,
Speaker 1: but it's also growing towards player kinematics data, which NBA
Speaker 1: has available for Saturday's season Kinematics kinematics, so the locations
Speaker 1: of players waist, elbow, shoulder, all of the joints, so
Speaker 1: more detailed data of like player movements and yeah, so
Speaker 1: how how players are shooting? And you can extract all
Speaker 1: this more detailed information.
Speaker 4: Are thanks now to Havana Serk, senior product scientists at
Speaker 4: Zalis Analytics.
Speaker 3: Let's stick with our conversations on artificial intelligence. At the
Speaker 3: New Jersey Institute of Technology, we looked at the company Avonaut,
Speaker 3: a leading provider of cloud and advisory services. Avonaut was
Speaker 3: founded as a joint venture between Microsoft and Accenture.
Speaker 4: We were joined by Anita Giovanni, global head of Innovation
Speaker 4: at Avonat, and we asked her how the company approaches
Speaker 4: AI and how AI will impact organizations going forward.
Speaker 9: Yeah, so, we are a global consultancy, as you mentioned
Speaker 9: MICROSOFTIC Center, joint venture, sixty thousand employees around the world,
Speaker 9: and what we do is think about AI from a
Speaker 9: client perspective. How is it that we can support organizations
Speaker 9: across sectors be AI first and at the same time,
Speaker 9: we're all going through this journey together. So thinking about
Speaker 9: ourselves as an organization, how can we be AI first
Speaker 9: in our own business processes and for our own people
Speaker 9: so I'm a company and I come to you, what
Speaker 9: do you do for me? We think about a lot
Speaker 9: of things. Are you guys prepared from a people perspective,
Speaker 9: an organizational perspective, and a process perspective. For example, a
Speaker 9: lot of people that we interviewed in an AI readiness
Speaker 9: report said they were enthusiastic and optimistic about AI. That's great. However,
Speaker 9: half of the leaders said they weren't ready, and only
Speaker 9: a third of CEOs believe that their top leadership is
Speaker 9: AI fluent. So there is a dissonance between the excitement
Speaker 9: and enthusiasm and the reality of the preparedness of organizations.
Speaker 9: And what we do is make sure that organizations have
Speaker 9: the coaching and support they need to get there.
Speaker 3: I would think one of the challenges, just speaking for
Speaker 3: myself is I learned a whole lot speaking to again
Speaker 3: and the smart people from NJIT what AI is. I'm
Speaker 3: one of those people that says, if you can't explain
Speaker 3: it in one sense, you don't understand it. And I
Speaker 3: don't think I understand it. What's the basic framework that
Speaker 3: you try to get across your clients about what AI
Speaker 3: is and what it can mean for them?
Speaker 9: Yeah, think about AI and one of the biggest generative
Speaker 9: AI tools right now through Microsoft is copilots. Think of
Speaker 9: it as a co pilot, not necessarily a replacement pilot that.
Speaker 4: Can allow you to articulating.
Speaker 9: Yeah, allow you to do your job more effectively and
Speaker 9: more efficiently. And so instead of thinking about AI as
Speaker 9: a job replacement, think about it as a way to
Speaker 9: replace key tasks and allow you to spend your days
Speaker 9: in ways that you want to, talking to people, being
Speaker 9: more relationship focused rather than necessarily summarizing emails or going
Speaker 9: through data sets, et cetera.
Speaker 3: So it's a partner.
Speaker 4: So basically I could have some AI. Think go throw
Speaker 4: my email and like correlate the important parts and give
Speaker 4: it out, for example, and take it and give it
Speaker 4: to me, so I don't have to spend my home
Speaker 4: morning going through and reading reports.
Speaker 3: Yeah exactly.
Speaker 4: That's really cool. Yeah, and that would make me so
Speaker 4: much time to go do other stuff.
Speaker 3: Yeah.
Speaker 9: I mean, think about when you come back from vacation.
Speaker 9: You probably check your email when you're on vacation. I don't,
Speaker 9: but for an exact.
Speaker 4: Reason, because if I come back, I have like two
Speaker 4: thousand emails being gone for like a week, and I can't.
Speaker 9: Keep that I can't do it if you had the
Speaker 9: AA tool, what you could do after being away for
Speaker 9: two weeks. I don't check my email and probably get
Speaker 9: in trouble for that.
Speaker 5: But I don't.
Speaker 9: I can come back and say, what did I miss
Speaker 9: over the last two weeks, go through all my pings
Speaker 9: on teams, go through all my outlook, and can you
Speaker 9: prepare for me a summary so that now that I
Speaker 9: come back, I can actually be ready and can prioritize.
Speaker 9: That's where it really comes into.
Speaker 4: Wow, that's really cool.
Speaker 3: Yeah, So what when you sit down with your clients,
Speaker 3: I mean, what's some of the common requests you get
Speaker 3: from them or what do they ask for most of
Speaker 3: the help with I guess.
Speaker 8: Yeah.
Speaker 9: One of the things that's really top of mind for
Speaker 9: people is about skill set and training and capability building.
Speaker 9: So in our survey, we found that eight out of
Speaker 9: ten people said that twenty hours of their work week,
Speaker 9: almost fifty percent of their work week can be replaced
Speaker 9: with AI tools. The challenges they don't know how to
Speaker 9: use the tools in the most effective and efficient way,
Speaker 9: so the training around that is critical in the process.
Speaker 9: The other is a responsible AI a governance set. Right, Yeah,
Speaker 9: what are the guard rails that we have to put
Speaker 9: into place so that people can play creatively in the space.
Speaker 4: Do you feel like people and CEOs or board levels
Speaker 4: are do they now know what they don't know, they
Speaker 4: are beginning to figure it out, or we're still in
Speaker 4: the beginning part of that.
Speaker 9: I believe we're in the infancy of it. I think
Speaker 9: there is an infancy of the learning curve, but also
Speaker 9: an infancy of having the right people in the room,
Speaker 9: having diverse perspectives. As we think about responsible AI.
Speaker 3: And we're hearing you mentioned the I guess the ethical
Speaker 3: use of AI. I don't know how that's going to evolve.
Speaker 3: Is that going to be some partnership between public, private,
Speaker 3: the individual.
Speaker 4: I'm not sure I actually know what that means. Well,
Speaker 4: it just seems like ethical use of AI.
Speaker 3: Yeah, it just seems like the technology could get out
Speaker 3: of control.
Speaker 9: Look, as AI and generative AI becomes more ubiquitous, with
Speaker 9: increased scale comes increased risk. That's just the reality of things.
Speaker 9: So how do you mitigate those risks? I think one
Speaker 9: of the most important ways to do that is to
Speaker 9: have the right people in the room. So, whether that's
Speaker 9: from a diversity perspective of gender, whether that's having people
Speaker 9: of color in the room, people from diverse backgrounds. It's
Speaker 9: one of the reasons that we do the scholarship program
Speaker 9: for women in STEM at this very institute, because we
Speaker 9: want to make sure that they're not brought in as
Speaker 9: a second thought, but rather at the very beginning of
Speaker 9: the conversation.
Speaker 4: So, what's like an unethical use of AI? Like, where
Speaker 4: does AI get bad?
Speaker 5: Yeah?
Speaker 9: Well, I mean, look, you can use you can use
Speaker 9: AI to create images that don't actually exist. You can
Speaker 9: put voices on people to say things through their own
Speaker 9: voice when they may maybe have not said that video.
Speaker 9: You can think about putting in questions into generative AI
Speaker 9: that perhaps share data with the broader public that you
Speaker 9: didn't want to share that's company specific data. So there's
Speaker 9: a security component, there's a falsification component, There's lots of
Speaker 9: different ways you kind of have to be proactive about.
Speaker 3: And on this front, once again, maybe at no fault
Speaker 3: of their own, the government is generations behind where the
Speaker 3: technology is. I don't know how this plays out, I
Speaker 3: really don't. I mean, is there a feeling that the
Speaker 3: industry for a while is going to have to police
Speaker 3: itself or is there going to be some again public
Speaker 3: private partnership in terms of regulating this, because this is
Speaker 3: not the FCC regulating the airwaves. This is really really difficult.
Speaker 9: Yeah, it gets complicated. Look, I think there's an individual
Speaker 9: level to it, an individual level of responsibility, But at
Speaker 9: the end of the day, it's going to fall on
Speaker 9: the leaders, the leaders of organizations across the board. If
Speaker 9: the senior leaders are not thinking about responsible AI, they're
Speaker 9: not thinking about the AI fluency, no one else is
Speaker 9: going to think about that. So the responsibility on the
Speaker 9: leaders is very high.
Speaker 3: Our thanks to Anita Givanni, Global head of Innovation at ABANAT.
Speaker 4: Coming up on the program, our conversation on AI continues,
Speaker 4: we speak with Michael Johnson, President of the New Jersey
Speaker 4: Innovation Institute.
Speaker 3: You're listening to Bloomberg Intelligence on Bloomberg Radio, providing in
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Speaker 4: Earlier in the week, Bloomberg Intelligence broadcasted live from the
Speaker 4: campus of the New Jersey Institute of Technology, and the
Speaker 4: main topic of conversation was AI.
Speaker 3: We spoke with Michael Johnson, president of the New Jersey
Speaker 3: Innovation Institute or NJII. It's a standalone corporation owned by NJIT.
Speaker 3: We first asked Michael what NJII does.
Speaker 10: In the US. We have lots of research universities and
Speaker 10: there's lots of smart people, lots of great resources, but
Speaker 10: there's this fundamental problem in academia, which is it's tough
Speaker 10: for the outside world actually leverage those resources. So for
Speaker 10: governmental organizations for industry, they want access to the cutting
Speaker 10: edge of AI, for example, but it's tough for them
Speaker 10: to actually make those connections and interact with faculty. So
Speaker 10: NGI is an organization. It's a five oh one C
Speaker 10: three wholly owned by NGT, and the idea is that
Speaker 10: we are a standalone corporation that's a conduit between the
Speaker 10: outside world and NGT, So we make those facilitations, we
Speaker 10: create unique business models to work with faculty, and we're
Speaker 10: a quick moving organization, unlike academia, which is you know,
Speaker 10: tends to be slower and more difficult to work with.
Speaker 10: So we're that conduit between them and the outside world
Speaker 10: and roughly have about one hundred and twenty folks out
Speaker 10: of organization we're focused on that can.
Speaker 4: Just say it's really cool his three year old son
Speaker 4: is here. I mean, what three year old is going
Speaker 4: to come and talk about AI. I feel like that
Speaker 4: just says it all at the end of the day, right,
Speaker 4: that is the future? So am I a company that
Speaker 4: goes to you and then you pair me up with
Speaker 4: something or is it sort of the technology that you're evolving,
Speaker 4: and then you go pitch it to companies.
Speaker 5: How does that work?
Speaker 10: It's a bit of inside out and outside in. So
Speaker 10: we can go to corporations and try and find out
Speaker 10: what their problems are, what their pain points are, and
Speaker 10: then go and find faculty you can help out. Or
Speaker 10: we might have a few faculty that have a very
Speaker 10: specific problem. They need access to software, they need to
Speaker 10: access the resources, and we go externally to find a
Speaker 10: way to work with corporations on that, but it's pairing
Speaker 10: the two with each other. And faculty are really smart,
Speaker 10: they're really focused on their research, but they don't always
Speaker 10: have the mind to go out and actually execute on
Speaker 10: consultant type projects for industry. So we help form that
Speaker 10: framework and along the way we're trying to help with
Speaker 10: tech transfers, so getting technology out of the university into
Speaker 10: products and services is always a pain point, and also
Speaker 10: just generally accelerating innovation and also helping upskille workers.
Speaker 3: You know, over the last several quarters, Bloomberg does this analysis.
Speaker 3: It shows what are companies talking about on their quarterly
Speaker 3: conference calls, And for the last several quarters, every single
Speaker 3: company in Y S and P five hundred has talked
Speaker 3: about AI, with the exception of Apple. Last quarter have
Speaker 3: I mentioned AI? Which is interesting? What are companies most
Speaker 3: commonly asking you for help with?
Speaker 4: Oh?
Speaker 2: Man?
Speaker 10: That goes all over the place. It depends in the companies.
Speaker 10: We have some small mom and pop businesses that just
Speaker 10: want help, but trying to move towards technology, towards computers.
Speaker 10: We have other companies, for example, that want to be
Speaker 10: the bleeding edge of some sort and field. So for example,
Speaker 10: it might be life sciences, it might be AI for example,
Speaker 10: and they're asking us to help improve something that they're
Speaker 10: already doing, or it's a very specific project they're pushing
Speaker 10: us to find faculty to help out with. So it
Speaker 10: kind of depends. We have other folks. For example, Picatinny
Speaker 10: Arsenal and Department of Defense are looking for just workers,
Speaker 10: so helping us upscale workers for advanced manufacturing and all
Speaker 10: sorts of different programs they need help finding talent for
Speaker 10: so we're trying to help that with that as well.
Speaker 4: So JPM we're going to interfew saw this. They had
Speaker 4: a great piece out that said that some of its
Speaker 4: corporate customers are slashing manual work by almost ninety percent
Speaker 4: with its cash flow management tool that runs on AI.
Speaker 4: And that's the fear, right that we're going to use
Speaker 4: AI and replace all the workers and those workers don't
Speaker 4: have any jobs. Is there any truth to that?
Speaker 10: It's a great question. So whenever you have technologies they
Speaker 10: are disruptive, there are going to be jobs certainly that
Speaker 10: are going to go away. But if you look back
Speaker 10: to when accel first came out, or when computers first
Speaker 10: came out, you look at accounting as a great use case.
Speaker 10: Accountants didn't go away because we were going from a
Speaker 10: ledger that was literally on paper to a computer based system.
Speaker 10: We found new questions to answer, new ways that we
Speaker 10: could look at our accounting and finances. So I think
Speaker 10: the jobs are going to change, But the overall number
Speaker 10: of jobs in that net, I don't know if it
Speaker 10: will actually reduce. It might increase in some cases. But
Speaker 10: we're going to answer different questions. We're going to do
Speaker 10: things much more quickly than we did in the past,
Speaker 10: for sure.
Speaker 3: I guess my lack of knowledge of full appreciation of
Speaker 3: AIS is I'm just not sure if it's something completely
Speaker 3: new or is it just the next iteration of what
Speaker 3: the smart people at NJIT typically do. Is it I'm
Speaker 3: just not sure what's new about it other than Man,
Speaker 3: everybody's talking about it, and it was a theme. One
Speaker 3: of the themes that drove the stock market in twenty
Speaker 3: twenty three was a concept of AI and the average
Speaker 3: trader has no idea what AI is, but he's buying
Speaker 3: stocks because he thinks they're an AI play.
Speaker 10: It's been around for decades, right, but we have a
Speaker 10: couple of technologies that came out in the last two
Speaker 10: years that have really transformed the way we see AI
Speaker 10: and while we're talking about it, and the reason is
Speaker 10: because now it's accessible. So for example, to years ago,
Speaker 10: if I go into Google and I tell you how
Speaker 10: do I make chicken palm? I got all these ads,
Speaker 10: I get all these things that tell me about chicken parm.
Speaker 10: I go in a chat GPT and I type that
Speaker 10: for example, and I get a perfect recipe on how
Speaker 10: to actually make that, So it becomes very accessible to anyone.
Speaker 10: And I think that go to market strategy. The open
Speaker 10: I had of making accessible is what really changed the game.
Speaker 10: And also the same time computing power is exponentially increasing,
Speaker 10: it's more accessible. We're now able to use it everywhere
Speaker 10: from making chicken palm to try and do research.
Speaker 4: So what kind of cool stuff are you guys working
Speaker 4: on right now? Like what were you most excited about?
Speaker 10: For us as NGI, what we're very focused on is
Speaker 10: trying to get things out at the university into the
Speaker 10: real world. And one specific project that we're working on
Speaker 10: is actually on law enforcement and body cams. So bodycams
Speaker 10: is there a sensor that generates a huge amount of
Speaker 10: data and from those data sets, we're usually looking at
Speaker 10: them after the fact, so after something bad happens, we're
Speaker 10: trying to review that situation. What we're trying to do
Speaker 10: is can we look at that data and predict something
Speaker 10: bad is going to happen before it happens. So if
Speaker 10: we see a pattern between some behaviors, running back time for.
Speaker 4: A second, so you have a BTE so you're tracking
Speaker 4: the behavior to then model behavior later.
Speaker 10: Yes. So for example, let's say we see an officer
Speaker 10: is running more frequently, they're yelling more frequently. That has
Speaker 10: probably correlated to some behavior outcome, such as excessive use
Speaker 10: of force. So for example, we might identify this officer
Speaker 10: as at a much higher likelihood of excessive use in
Speaker 10: force in the future. Let's intervene and get them training
Speaker 10: before something bad happens. So we're trying to build that
Speaker 10: a software we can actually put onto the hardware and
Speaker 10: help the law enforcement and help with de escalating situations.
Speaker 4: Wow, that's really cool.
Speaker 3: What other stuff like?
Speaker 4: What are the thing are you excited about?
Speaker 10: Oh man, there's so many Take your second best. My
Speaker 10: second best would definitely be in the drone space. So
Speaker 10: drones are another sensor. We're collecting huge amounts of imagery data,
Speaker 10: and today a lot of that work is actually a
Speaker 10: person looking at videos, scrolling through video like you would
Speaker 10: from a VHS tape, and we're using computer vision and
Speaker 10: AI to actually analyze that data and try to predict
Speaker 10: what's happening and try to classify certain imagery and answer
Speaker 10: very specific questions like is a power line going to
Speaker 10: fail based upon a single picture from a simple drone?
Speaker 4: Oh, now that could be really helpful, dependually all the
Speaker 4: wildfires and stuff that we've had. And then as all
Speaker 4: the utilities are kind of grappling with like old infrastructure
Speaker 4: that is not easy to replace, kind of how you
Speaker 4: manage that? Is it expensive for these companies to use this?
Speaker 10: Usually the bottleneck today is data generation and data annotation
Speaker 10: because there's lots of data, but we have to annotate
Speaker 10: the data to be actually able to use it. So,
Speaker 10: for example, if the body cams, we have to know
Speaker 10: what those events are that we're trying to predict and
Speaker 10: how she classifying them ahead of time. So that's the
Speaker 10: real the bottleneck for it in a lot of cases.
Speaker 4: All right, thanks to Michael Johnson, president of the New
Speaker 4: Jersey Innovation.
Speaker 3: Institute, let's stick with our conversations on artificial intelligence at
Speaker 3: the New Jersey Institute of Technology. New Jersey Governor Phil
Speaker 3: Murphy recently laid out further details of a so called
Speaker 3: AI moonshot plan. The proposed plan would include seven million
Speaker 3: dollars to advance AI utilization and opportunities in the state.
Speaker 4: We were joined by AI expert Beth Simon Novic, who
Speaker 4: was recently appointed as New Jersey's first ever Chief AI Strategist,
Speaker 4: and we asked Beth how she helps implement Governor Phil
Speaker 4: Murphy's vision of having New Jersey lead the nation in
Speaker 4: the advancement of AI.
Speaker 7: Governor Murphy has said very loud and clear, we have
Speaker 7: to do better when it comes to technology in terms
Speaker 7: of embracing the use of technology to grow the economy,
Speaker 7: to grow jobs in the state, but also to improve
Speaker 7: how government works. So my job is to work on
Speaker 7: all of the above and to see what we can
Speaker 7: do as government to make that easier, to make that better,
Speaker 7: and to embrace the responsible and ethical use of AI
Speaker 7: to ensure that we're doing right by our residents.
Speaker 3: So what are some of the applications that the governor
Speaker 3: and the Governor's office thinks AI can do Over the
Speaker 3: next several years, Where will the residents of New Jersey
Speaker 3: see it? Do you think?
Speaker 7: So this is not a several years from now. The
Speaker 7: future is already here. And we've been using AI for
Speaker 7: quite some time, and generative AI since the very beginning,
Speaker 7: so in many ways that you don't even see or
Speaker 7: know about. So, for example, if you're getting a letter
Speaker 7: from the State of New Jersey about let's say your
Speaker 7: unemployment benefits, you're getting a letter that has been simplified,
Speaker 7: that has been written in plain English, that's been written,
Speaker 7: we hope, more clearly than it would have been before
Speaker 7: because generative AI can help us to do a first draft.
Speaker 7: If you're calling up about your anchor tax relief that
Speaker 7: the State of New Jerse is giving out to residents,
Speaker 7: you are hopefully getting your call resolved faster because you
Speaker 7: get a menu option that's we've written with the help
Speaker 7: of AI. Because voice to text our call center operators
Speaker 7: know people are calling in asking the following kinds of questions,
Speaker 7: we should write these menu options and these instructions and
Speaker 7: answers so people can get that information faster. When you're
Speaker 7: going out, for example, and typing in on a website
Speaker 7: and telling us comments of how we can do something
Speaker 7: better on a website like business dot J dot gov,
Speaker 7: where you can go to start and run and grow
Speaker 7: your business everything you need from one place. We're taking
Speaker 7: the comments we're getting from citizens about what they need
Speaker 7: about what they want, using AI to help us summarize
Speaker 7: those comments, synthesize them, and turn that into the information
Speaker 7: that people want and need front and center. So the
Speaker 7: goal is government that's more responsive, more informative, and providing
Speaker 7: services twenty four to seven that are responsive to what
Speaker 7: people actually want and need.
Speaker 4: That's a pretty good pitch. You were also the chief
Speaker 4: of innovation, right, h Jersey.
Speaker 7: I was for many years the chief Innovation Office.
Speaker 4: So did the Chief Innovation Officer become the AI strategist
Speaker 4: or is there also an innovation officer? And I guess
Speaker 4: I'm trying to understand, like is the innovation thing now
Speaker 4: AI or can there be other stuff?
Speaker 7: There is still other stuff. We have a wonderful new
Speaker 7: Chief Innovation Officer, Dave Cole, has taken over that title
Speaker 7: and is leading our efforts to use technology to improve
Speaker 7: how we bring services to residents. So projects like business
Speaker 7: dot J dot gov to take the business one, for example,
Speaker 7: or other digitization of residence services, so that instead of
Speaker 7: having to go to a government office, you know, between
Speaker 7: nine and five, you can come to a website, you
Speaker 7: can use your mobile phone.
Speaker 4: Oh my gosh, that'd be.
Speaker 7: Amazing transact with government twenty four to seven. That's work
Speaker 7: that's been underway for a long time, and that doesn't
Speaker 7: just depend on AI. That is about again, clearer instructions,
Speaker 7: planer English, things available online, giving you the information front
Speaker 7: and center that you want and need in the way
Speaker 7: that people have become accustomed to from the best businesses.
Speaker 7: We think that government should serve citizens in much the
Speaker 7: same way, except in the public interest.
Speaker 3: Well, New Jersey's had a long history of technological innovation.
Speaker 3: I think of telecommunications with Bellcore and Bell Labs supporting
Speaker 3: eighteen teen Verizon. I think about some of the biotech
Speaker 3: and pharmaceutical companies like Johnson and Johnson based here in
Speaker 3: New Jersey. I'm wondering, is there support for the young
Speaker 3: NJ grads that are in a garage somewhere in Jersey
Speaker 3: City coming up with the next AI type thing. How
Speaker 3: do we support those people?
Speaker 7: Absolutely so, there are a whole number and range of
Speaker 7: investments that are out there to support people starting new businesses.
Speaker 7: That's what my colleagues at EDA work on in particular,
Speaker 7: is ensuring that we're providing those kinds of incentives for
Speaker 7: people who want to start their business in New Jersey
Speaker 7: and grow their business in New Jersey. That's particularly why
Speaker 7: the government is here to help support those businesses going
Speaker 7: out and in particular now to look at how we
Speaker 7: can support new AI businesses or existing businesses who are
Speaker 7: asking how we can turn around and use AI to
Speaker 7: improve what we do. It's a question we've been answering
Speaker 7: for a long time. Before we called it AI. We
Speaker 7: called it big data.
Speaker 3: Yep, right.
Speaker 7: So the more the people we're using a lot of
Speaker 7: businesses have asked themselves, how could I go out and
Speaker 7: start using data to measure what's working, to measure what
Speaker 7: customers want, and again to deliver new kinds of services
Speaker 7: across a range of industries. It's why we've been starting
Speaker 7: new partnerships, such as with Princeton, around this new AI
Speaker 7: hub that's been set up so that we can connect
Speaker 7: some of that tremendous innovation that's coming out of universities
Speaker 7: like NJIT, like Rutgers, like Princeton. We're of course, known
Speaker 7: in this state for having the best universities and the
Speaker 7: best education system in the country, and we want to
Speaker 7: connect that back to how we're growing the economy and
Speaker 7: growing jobs. Hearing the state all right?
Speaker 4: Thanks to Bethsimono Noovic, Chief AI Strategist of the State
Speaker 4: of New Jersey.
Speaker 2: This is the Bloomberg Intelligence Podcast, available on Apples, Spotify,
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