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Looking about Apple here, stocks down two point seven percent. The European Union, who has always been tough on US technology I think twenty twenty five years ago with Microsoft in this scene called Windows, and they're still beating up on US tech companies. So another fine come along. Let's check in with anarag Rana. He covers all things technology for Bloomberg Intelligence. So put into context, what's what happened to Apple here from a regulatory standpoint and what it means for them.
Just explain kind of what the fine is for.
Yeah, this has been, you know, going on for a while, and tbxtions were that they were going to be fined about five hundred million euros. Now the more important thing is on March seven, the Digital Market Act goes live, and Apple's already made concessions in terms of all the things the European Union wants to do. I think the surprise to our analyst Hamblin, who is based in Europe, was the size of it. It's not you know, when we rumored was five hundred when it came to around
one point eight billion. One thing is for clear at this point that Apple is not going to just you know, pay this fine and walk away with the DMA or the Digital Markets Act. It's possible that the app store, you know, policies are going to be under more scrutiny, and I think that's what's driving the stock down. I mean, two billion dollars is not that big of a deal for Apple, but I think the twenty one billion dollars of revenue that the app store generates, I think that's that's a bigger issue.
So here's my thing, though, is that the stock is down over ten percent since it's January high for this year. So clearly something else was going on, just not this fine, and that's just adding fuel to the fire here. What is happening to Apple?
Yeah, I mean if you think about it, all the bad things that can happen to Apple are happening all at once. I mean, frankly speaking, it right now when you look at their iPhone sales that are slowing down, China competition, a lot of supply chain dependency on China. On top of that app store stuff. They are not a player in Jenei right now. So a lot of good things happening for Apple, and it's going to be a slow year for them. It's probably going to be
another slow year next year. So Apple has to come out but in June when they do their developer conference and put some fresh I would say air or life into the company by saying that, Okay, we do have a generative AI strategy and this is how we are thinking of achieving it. I think other than that, it's going to be a be a difficult year for them.
I think this June conference that you reference on Oki it's usually the conference maybe where they introduce a new cool product or something like that. But I feels like the pressure on the company this year is as great as I can ever remember it because they're either going to come out with something really cool as it relates to AI, or they're just going to come out and say no, we're not rushing into it, in which case the stock is going to presumably, you know, be challenging.
What do you think is going to happen?
Yeah, the June conference is going to be a lot of the software updates the Worldwide Developer Conference, and you do give you know, they are bound to give a lot more detail about what are the five, six, seven things that they're going to be updating on their software that has more Generator VII capabilities. I think it's not going to be that big just because these things take time. We just heard from Mark them and you know, not that long ago that they're shutting down the car and
allocating that headcount to generative AI. But you know, it's what are you going to do in three months? I think it's going to be a little longer than that. They're going to make some promises, but frankly speaking, I mean, they do have a distribution network, so you know, maybe maybe we should give them some some points at this
point to see if they can pull this off. It's going to lead to an iPhone refash cycle that we haven't seen before, but I think, but you know, I'm not betting on anything big at this point.
So go to the AI strategy. If you had to articulate what Apple's AI strategy is, what would you say.
Yeah, so let's think about all the different things that we do on our phone. So for example, City by itself, you know, could be far more sophisticated than what it is today. Imagine what all different things you can do with open AI or check GPT. Imagine if you could do that just on the phone itself without having to
go to a third party and do it now. Apple has the whereworth in terms of dollars to do it, whether they actually have the capacity from a technology point of view, If they can embed a lot of those features like you asking a question to your phone and you getting the answer right there, they have the distribution network of over one billion connected devices, then what happens is you don't really need to go into an app
to do a lot of that stuff. We also heard that they're going to develop a software that can write itself a little quicker. That's not going to help a consumer as much that they're going to help more developers. But you know, the thing that we want to see is what can be done on the phone itself that would force me not to tap into an app and I can get those answers immediately, And.
That to me seems like something that Apple can absolutely do. If I were a long term investor, should I be buying the stock here. I mean, Ai, I'm going to get a monster bumped.
In the multiple.
I am absolutely on the same camp with you, you know at this point, Paul. But frankly, they have to prove it. Right now, things haven't worked for them in terms of, you know, the being on the edge of any technology at this point, so I think they have to prove it in order to get it. Remember, they have over eight hundred million phones that people have in their hand in terms of the cellular connection, so at any given year they sell roughly about two hundred and
twenty million phones. If this thing really takes off, there are over forty percent of phones that are iPhone twelve and below or that is very low processing power, low memory, a lot that gets upgraded and that leads to a next big you know, cycle and iPhone. I think that
can be done, but I think they'll have to prove it. Remember, for a company that grows that two to five percent, they're still trading at like twenty five times earning, So it's not it's not cheap from even you know, that point of view.
But Anuraga, I thought that Apple wanted to eventually become primarily services revenue, Like, they didn't want to be dependent on hardware. They wanted to have people pay them stuff on like a monthly or yearly basis. How would that AI integration do that?
So the services revenue is an important piece, but it's nothing without the hardware. You have to have the hardware to get there.
Right, But don't they want it to be Don't they want it to be about that and not the hardware.
Yeah? Yeah, But at the same time, you know, if you are able to drive these higher value services, your ecosystem becomes stronger. People who have these older iPhones, let's say four years old, five years old, six years old, you're not going to be able to run those operations on it because it's going to be either too slow or your battery is going to die around very quickly. So you need to upgrade the hardware. Now I just talked about iPhones, but you can extend that to iPads,
to watches, to any other product that they have. It is the critical portion of it. Anybody who controls a large portion of these large language models will have an edge down the road. So they really want to be a player in that market. You don't want to be left behind.
So let's just go back to where we started here, which is some of the regulatory issues. Is this like twenty five years ago when the EU came after Microsoft for Windows and bundling all that stuff and they just kind of write some checks and you go away. Or is this something more of a challenge, more of a headwind for Apple do you think?
I think it's more of a headline risk for the next several years. A lot of these things is not going to be just you know, they can't go out and tell them to reduce these fees. But having said that, there is going to be an overhang of the stock. But we think that they can do so much. They can really boost the advertising revenue that they really haven't played that lever. They can take iCloud pricing up, they
can do Apple Care. I mean, Apple has a lot of levers to pull, and it's going to be interesting to see how different governments around the world approach this issue because Apple, I mean, they wrote a phenomenal piece
today about fighting this particular you know, they're fine. I think if you read that the entire piece as it relates to Spotify, I think they make a very good case of why their ecosystem is important for developers and why they should have you know, at least some you know, you know, skin in the game in terms of what they bring to the party.
All Right, Honor Rock, thanks so much. We super appreciate it. The best person to go to when it comes to Apple. I should I have an iPhone fourteen?
I forgot?
Really?
Yeah? Yeah, yeah, I eleven switched my switch from Verizon to T Mobile. I got a free phone.
And how's upen, Oh, it's okay.
The Wi Fi is a lot better, really, yes, but sometimes about the Wi Fi, it's a little Spottierka, It's interesting. It's interesting little trade off there. On Magrana joining us Bloomberg Intelligence a senior technology analyst.
You're listening to the Bloomberg Intelligence Podcast. Catch us live weekdays at ten am Eastern on applecar Play and Android Auto with the Bloomberg Business app. You can also listen live on Amazon Alexa from our flagship New York station Just say Alexa playing Bloomberg eleven thirty.
It's Alex Steels pulsewhen you We're live here at the New Jersey Institute of Technology here in Newark, New Jersey, and we're also on that YouTube things ahead over to YouTube dot com search a Bloomberg I think Yank Bloomberg Radio, Bloomberg Podcast of all things.
I'll tell you know you've made it.
When Donna Russo was in the house bringing it here, she's kind of running everything over here. So we appreciate don having us over here. Let's talk AI. Michael Johnson joint Is. He's the president of New Jersey Innovation Institute. Michael, thanks so much for joining us here. What is the New Jersey Innovation Institute.
It's a great question. So in the US, we have lots of research universities and there's lots of smart people, lots of great resources, but there's this fundamental problem in academia, which is it's tough for the outside world actually leverage those resources. So for governmental organizations, for industry, they want access to the cutting edge of AI, for example, but it's tough for them to actually make those connections and
interact with faculty. So NJI is an organization. It's a five oh one C three wholly owned by NNGT, and the idea is that we are a standalone corporation that's a conduit between the outside world and NGT. So we make those facilitations, we create unique business models to work with faculty, and we're a quick moving organization, unlike academia, which is you know, tends to be slower and more
difficult to work with. So we're that conduit between them the outside world and roughly have about one hundred and twenty folks out of organization and we're focused on that can.
Just say it's really cool his three year old son, is he? I mean, what three year old is going to come and talk about AI? I feel like that just says it all at the end of the day, right, that is the future. So am I a company that goes to you and then you pair me up with something or is it sort of the technology that you're evolving, and then you go pitch it to companies. How does that work?
It's a bit of inside out and outside in. So we can go to corporations and try and find out what their problems are, what their pain points are, and then go and find faculty you can help out. Or we might have a few faculty that have a very specific problem. They need access to software, they need to access the resources, and we go externally and find a way to work with corporations on that, but it's pairing
the two with each other. And faculty are really smart, they're really focused on their research, but they don't always have the mind to go out and actually execute on consultant type projects for industry. So we help form that framework and along the way, we're trying to help with tech transfers. So getting technology out of the university into products and services was always a pain point, and also just generally accelerating innovation and also helping upskilled workers.
You know, over the last several quarters, Bloomberg does this analysis. It shows you know, what are companies talking about on their totally conference calls, And for the last several quarters, every single company in Y S and P five hundred has talked about AI, with the exception of Apple last quarter and I mentioned AI, which is interesting.
What a company that's not doing? Now?
Yeah, what are companies most commonly asking you for help with?
Oh?
Man, that goes all over the place. It depends in the companies. We have some small mom and pop businesses that just want help with trying to move towards technology.
Towards computers.
We have other companies, for example, that want to be the bleeding edge of some sword and fields. So for example, it might be life sciences, it might be AI for example, and they're asking us to help improve something that they're already doing, or it's a very specific project they're pushing us to find faculty to help out with. So it
kind of depends. We have other folks. For example, Picatinny Arsenal and Department of Defense are looking for just workers, so helping us upscale workers for advanced manufacturing and all sorts of different programs they need help finding talent for so we're trying to help that with that as well.
So JPM, we're going to know if you saw this, they had a great piece out that said that some of its corporate customers are slashing manual work by almost ninety percent with its cash flow management tool that runs on AI. And that's the fear, right that we're going to use AI and replace all the workers and those workers don't have any jobs. Is there any truth to that?
It's a great question. So whenever you have technologies, they are disruptive, there are going to be jobs certainly that are going to go away. But if you look back to when Excel first came out, or when computers first came out. You look at accounting as a great use case. Accountants didn't go away because we were going from a ledger that was literally on paper to a computer based system. We found new questions to answer, new ways that we could look at our accounting and finances.
So I think the.
Jobs are going to change, But the overall number of jobs in that net, I don't know if it will actually reduce. It might increase in some cases. But we're going to answer different questions. We're going to do things much more quickly than we did in the past, for sure.
You know, I guess my I guess my lack of knowledge of full appreciation of AIS is. I'm just not sure if it's something completely new or is it just the next next iteration of what the smart people NJIT typically do. Is I'm just not sure what's new about
it other than man, everybody's talking about it. And it was a theme for Why the Stock One of the themes that drove the stock market in twenty twenty three was a concept of AI and the average trader across the river in New York has no idea what AI is, but he's buying stocks because he thinks they're an AI play.
It's been around for decades, right, but we have a couple of technology that came out in the last two years that have really transformed the way we see AI. And while we're talking about we were talking about it last night at my family's Sunday dinner, and the reason is because now it's accessible. So, for example, two years ago, if I go into Google and I type how do I make chicken Palm? I got all these ads, I get all these things that tell me about chicken parm.
I go in to chat ept and I typed that for example, and I got a perfect recipe on how to actually make that, so it becomes very accessible to anyone. And I think that go to market strategy. The open I had of making accessible is what really changed the game. And also the same time computing power is exponentially increasing, it's more accessible. We're now able to use it everywhere from making chicken palm to try and do research.
So what kind of cool stuff are you guys working on right now? Like, what were you most excited about?
For us?
As ANGI, what we're very focused on is trying to get things out of the university into the real world. And one specific project that we're working on is actually on law enforcement and body cams. So bodycams is there a sensor that generates a huge amount of data, and from those those data sets, we're usually looking at them after the fact, so after something bad happens, we're trying to review that situation. What we're trying to do is can we look at that data and predict something bad
is going to happen before it happens. So if we see a pattern between some behaviors, running back time for a.
Second, so you have a buye So you're tracking behavior to then model behavior later.
Yes, So for example, let's say we see an officer is running more frequently, they're yelling more frequently. That is probably correlated to some behavior outcomes such as excessive use of force. So for example, we might identify this officer as at a much higher likelihood of excessive use of force in the future. Let's intervene and get them training
before something bad happens. So we're trying to build that a software we can actually put onto the hardware and help with law enforcement and help with de escalating situations.
Wow, that's really cool. What other stuff like, what are the thing you excited about Oh man, there's so many we'll think your second best.
My second best would definitely be in the drone space.
So drones are another sensor. We're collecting huge amounts of imagery data, and today a lot of that work is actually a person looking at videos, scrolling through video like you would from a VHS tape, and we're using computer vision and AI to actually analyze that data and try to predict what's happening, try to classify certain imagery and answer very specific questions like is a power line going to fail based upon a single picture from a simple drone?
Oh, now that could be really helpful depually all the wildfires and stuff that we've had. And then as all the utilities are kind of grappling with like old infrastructure that is not easy to replace, kind of how you manage that? Is it expensive for these companies to use this?
Usually the bottleneck today is data generation and data annotation because there's lots of data, but we have to annotate the data to be actually able to use it. So, for example, with the body cams, we have to know what those events are that we're trying to predict and actually classifying them ahead of time. So that's the real the bottleneck for it in a lot of cases.
All right, Michael, thanks so much. It was really great. This is really fun. Get your perspective. Is your son gonna stay.
Or is he gonna he's don't listen all day?
Well, awesome, we like that future generation. Michael Johnson, president of New Jersey Innovation Institute, and Ji, I thanks very much. It was really great to get that perspective. That's really interesting. I think the bodycam situation too, like it's not a profiling and profiling thing. It's like you're gonna get the help that you need down the road, which I think
is really cool. And it's good to hear these actual use cases because it's easy to just say AI is cool, is going to do stuff, But to get an actual use case that you can do is quite interesting.
Yeah. Absolutely.
You're listening to the Bloomberg Intelligence Podcast. Catch us live weekdays at ten am Eastern on Apple card Playing and broid Otto with the Bloomberg Business app. Listen on demand wherever you get your podcasts, or watch us live on YouTube.
Paul and I are here broadcasting live from the campus of the New Jersey Institute of Technology n J. It where we're talking about all things AI and sort of how you create the thing and then move it outside and bring it to companies or businesses that need it and bridging that gap between those two and one person in part very much responsible for that here in New Jersey is Beth Simone Novak. She is Chief AI Strategist of the State of New Jersey. What a cool title, Beth, What does that mean?
First in the country?
What does it mean?
So?
I mean, are you like, hey, business, you should use that, or hey, government, let's use this?
All of the above?
Okay.
So Governor Murphy has said very loud and clear, we have to do better when it comes to technology in terms of embracing the use of technology to grow the economy, to grow jobs in the state, but also to improve how government works. So my job is to work on all of the above and to see what we can do as government to make that easier, to make that better, and to embrace the responsible and ethical use of AI to ensure that we're doing right by our residents.
So what are some of the applications that you know, the governor and the Governor's office thinks AI can do over the next several years.
Where will the residents of your New Jersey see it? Do you think?
So this is not a several years from now. The future is already here. And we've been using AI for quite some time, and Generative AI since the very beginning, so in many ways that you don't even see or
know about. So, for example, if you're getting a letter from the State of New Jersey about let's say your unemployment benefits, you're getting a letter that has been simplified, that has been written in plain English, that's been written, we hope, more clearly than it would have been before because Generative AI can help us to do a first draft.
If you're calling up about your anchor tax relief that the State of New Jersey is giving out to residents, you are hopefully getting your call resolved faster because you get a menu option that's we've written with the help of AI. Because voice to text, our call center operators know people are calling in asking the following kinds of questions, we should write these menu options and these instructions and
answers so people can get that information faster. When you're going out, for example, and typing in on a website and telling us comments of how we can do something better on a website like business dot NJ dot gov, where you can go to start and run grow your
business everything you need from one place. We're taking the comments we're getting from citizens about what they need, about what they want, using AI to help us summarize those those comments, synthesize them, and turn that into the information that people want and need front and center. So the goal is government that's more responsive, more informative, and providing services twenty four to seven that are responsive to what people actually want and need.
That's a pretty good pitch. You were also the chief of innovation, right, h Jersey.
I was for many years the chief innovation officer. Yes.
Did the chief innovation officer become the AI strategist or is there also an innovation officer? And I guess I'm trying to understand, like is the innovation thing now AI or can there be other stuff?
There is still other stuff. We have a wonderful new Chief Innovation Officer, Dave Cole, has taken over that title and is leading our efforts to use technology to improve how we bring services to residents. So projects like business dot J dot gov to take the business one for example, or other digitization of residence services so that instead of having to go to a government office, you know, between nine and five, you can come to a website, you can use your mobile phone.
Oh my gosh, that'd be amazing.
Forransact with government twenty four to seven. That's work that's been underway for a long time, and that doesn't just depend on AI. That is about again, clearer instructions, planer English things available online, giving you the information front and center that you want and need in the way that people have become accustomed to from the best businesses. We think that government should serve citizens in much the same way, except in the public interest.
Well, New Jersey's had a long history of technological innovation. I think of telecommunications with Bellcore and Bell Labs supporting eighteen teen Verizon.
I think about some of.
The biotech and you know, pharmaceutical companies like Johnson and Johnson based here in New Jersey. I'm wondering, is there support for the young NJ grads that are in a garage somewhere in Jersey City coming up with the next AI type thing.
How do we support those people?
Absolutely so, there are a whole number and rain of investments that are out there to support people starting new businesses. That's what my colleagues at EDA work on in particular, is ensuring that we're providing those kinds of incentives for people who want to start their business in New Jersey
and grow their business in New Jersey. That's particularly why the government is here to help support those businesses going out and in particular now to look at how we can support new AI businesses or existing businesses who are asking how we can turn around and use AI to improve what we do. It's a question we've been answering
for a long time. Before we called it AI, we called it big data, right, So the more the people we're using a lot of businesses have asked themselves, how can I go out and start using data to measure what's working, to measure what customers want, and again to deliver new kinds of services across a range of industries.
It's why we've been starting new partnerships, such as with Princeton around this new AI hub that's been set up so that we can connect some of that tremendous innovation that's coming out of universities like NGIT, like Rutgers, like Princeton. We're of course known in this state for having the best universities and the best education system in the country, and we want to connect that back to how we're growing the economy and growing jobs here in the state.
What's the hardest part of your job.
There's only twenty four hours in the day, and there's a very, very lot to do, both on the public sector side and on the private sector side.
Do you feel like it's awareness, is it implementation? Is it finding the cool technology? Is it having too many problems to solve?
Well, the cool technology is very much there, and I think what we're trying to do now is to ensure that, especially in government, we are building not just awareness but actually use of these tools to improve how we serve residents across a whole range of domains and across agencies.
So we know that Governor Murphy feels that AI is important and administration feels that AI is important, as the rest of the government within the state share that as well. Or is it require kind of a promotional pitch for the office.
Well, you know, the governor is the salesman in chief for the State of New Jersey, and of course, setting this message about the importance of AI, the ways we should be embracing these tools going out early. We're one of the first states to actually put out a policy that says we should responsibly and ethically use AI to better serve residents. And one of the things we're doing is promoting upskilling and learning across the whole of public sector.
It's not enough to have just the governor supporting AI, to have a chief AI strategist. We need every public servant out there to be asking themselves, how can I use these powerful new tools, again ethically and responsibly safeguarding privacy and security and people's data. But how can I go out and use these tools to write that better first draft of the email, to write that clearer website, to be able to write a better policy. This is
the next generation, if you will, of word processor. To put it very simply, but that we should be using to be able to serve residence better and we need everybody to know how to do that.
Bet, thanks so much. We really appreciate your time. We know you're quite busy. Beth Simona and Novak, chief AI strategist from the State of New Jersey. That was actually really helpful. Okay, so this is like the next version of the stuff that we do normally. Like that really helps me because I think for people like you and me, it's hard to understand the practical applications. It just becomes like AI. Yep, whatever that winds up meaning exactly.
You're listening to the Bloomberg Intelligence Podcast. Catch us live weekdays at ten am Eastern on applecar Play and Android Auto with the Bloomberg Business. You can also listen live on Amazon Alexa from our flagship New York station Just say Alexa play Bloomberg eleven thirty.
But I am learning a lot of cool stuff about AI, particularly the implementation. It's not just this thing that we talk about, like it can actually be used for certain areas and apparently it can also be used in sports. AI in the role of sports. So here to help us break that down on what that all means is Evana Scherich. She is Zealous Analytics senior product iientist also former basketball player. Right basketball player, You also know all
the things about technology. How do you use AI in sports?
Yeah, So this field had expanded in last maybe ten years of a lot in other sports. Even before that, it was in baseball that was one of the first sports. If you've seen Moneyball.
That's really yes, yeah, okay, I like me the moneyball, okay. And so it's basically like how to position, like what players to put where combinations? Is it that kind of stuff?
Correct? Correct? So so player evaluation in game decision strategy, that's sort of sort of things.
Yeah.
So again, played for your starter for NJIT's basketball. You also represented your native Croatia and youth basketball. So you're great at basketball, but you're also a math nerd to the nth degree. She got a BS and a pH degree and applied mathematics from nj T, focusing on computational fluid dynamics.
I don't know what that means.
I don't know what that means. That's but okay, I don't know.
So a great mathematician, great bad basketball player. Let's put it all together. What what are some of the leagues, What are some of the really good applications for some of that technology? Because we've seen you mentioned moneyball for you know that we've seen it in baseball. What other applications are out there that you think? It seems like we're in the very early innings of that.
Yeah. Yeah, So early on it started with just using basic, basic, data, so box scores, play by play, and then a lot of sports in recent years have what's called player tracking data, meaning we have locations of the players on the court or on a pitch, on a field, whichever sport we're
talking about, in at a high resolution. So so from that data we can extract not only things that are counted in a box score, but also other things that happened during the game that you wouldn't see u counted in like a basic box score for example.
What are some of the common questions that like coaches or owners come to you.
With the biggest question is how do we value players? How do we how do we find which which players, which teams should sign, which how how long of a contract, how how much money should be on a contract. So that's that's one side. So so that's the player evaluation side, and then the other side is coaching and in game decision making. So which situations are producing the most value for for the teams, Which situations are creating creating better opportunities to score.
I know, like in baseball, major league baseball and in minor league baseball.
Now it's coming into all the other parts of baseball.
The analytics people the data people versus maybe some of the more traditionalists and they're kind of they kind of butt heads on occasion.
And how much analytics do you use? Imagine knows what I'm talking about.
So how much analytics do you use versus just my gut I think this player will do well?
Or how do you kind of bridge that topic? Yeah?
Yeah, So that's a that's a big important thing because you can just have data without the domain expertise. And I think that's something that we a Zellas have a really good strength is that we have the experts in in data and statistics, in AI, in machine learning, but we also have a lot of people who worked in sports teams and have that sort of experience and know which questions the teams want to answer, what's useful for them and uh and how can we help them best?
So yeah, because when you were saying what AI could help you do, it feels like that's not what a coach is supposed to do. But you're saying that you need someone to interpret how to manage that and stuff.
Right, right, So you need like a bridge between the data and what's what's happening on the court.
All right, If I'm an agent representing a player. Now, this is I got to learn this stuff because the team's gonna come.
At me and say, this is what the program tells me that, yeah, your.
Client's worth blank because his or her ops is this and blah blah blah blah blah blah. And you got to come back and say, no, I think he's better than that.
And I think he's really more. So did they do you have?
Do you work with the agents and players and selves as well, because they better be smart.
On this stuff?
Yeah, yeah, that's it's a great area where whereas elles is growing as well in some of our sports. But but yeah, it's it's not you know, an agent cannot learn all of this on their own, so so having a company or a contractor who can.
So do you guys work with agents and players and directly.
In in certain sports?
Yes, yeah, but not all across the board. So you also, as Paul was mentioned earlier, you got your BS and your PhD in applied mathematics and nj I T because we're here and we're talking about nj I T kind of bridges the gap between learning stuff and then putting it out into the world. How did this help you evolve your career and leave you where you are today.
Yeah, even though I studied competitional fluidnamics, it's not exactly data science, but I've learned a lot of skills that.
Were by the way, so you can pretend it is.
There's a little skills that transfer from from one field to the other and coding, analyzing large data sets, of creating visualizations and communicating scientific results to to regular audience, to anybody else who can understand to understand it.
Are there some sports that are embracing AI or just technology analytics more than others?
I think that's that's historically in baseball, particularly because they had the more advanced data for the longest time. But other sports now also have the player tracking data and are starting to get more more on that side.
How did you wind up in this? Because if you played basketball, right, because you're originally from Croatia, right, So you played basketball and then you somehow wound up and deep into analytics. How did how did you do that?
Well?
I always loved math and I always loved basketball, and this was a perfect combination of the two.
So in I'm kind of wondering where are we do you think in terms of the evolution of applying data and AI to sports, because it just this satistics. I've been following sports my entire life, and I'm listening to a broadcast and they're saying stuff.
I have no idea what they're talking about, Like now batting.
Average is an important anymore to baseball, and now it's on bass plus slugging.
I don't know.
I mean, it seems like we need a tutorial on a lot a lot of these broadcasts.
I mean, how do you where? Where can this go? Do you think? Yeah?
I wouldn't know about baseball because I don't really understand the rules coming from Croatia. Uh but but in basketball, we you know, for now we have the player location data. But but it's also growing towards player kinematics data, which which NBA has available for this season. Kinematics and kinematics, So the locations of players waist, elbow, shoulder, all of the joints, the more detailed data of like player movements and and uh yeah, so so how how players are shooting?
And you can you can extract all this more more detailed information and that's the next up in basketball.
Wow, part of me thinks that's cool. And also creepy like all at the same time. Any sports where this like doesn't at all work for I mean this feels like this makes sense in like team sports. What about like more individual sports like gymnastic skiing, Like how does it work in those kind of things?
Yeah, so it's those sextual works in golf, which is obviously an individual sport, and there we work directly with the players.
And what kind of data do you look at there for the golfer? Mean to me, it's just can I keep it on the fairway?
Can you line it up and shoot it in?
Yeah?
What can you tell me about my non game golf?
I actually, you know, don't play golf and don't completely understand that fair.
But the same idea that they can storm, like how you stand like that kind of thing, Like what kind of tools are like where you hit it?
Where the ball I guess it's called falls and.
Clubhead speed, and I mean they're.
Breaking it head speed, you have stuff.
Yeah, they got it all now with the track man. Everybody's got a little computer sitting right.
Behind them on the driving range and it measures basically everything. So now it's all about spin, ray, club head speed. All this kind of stuff. But for those of us are just trying to hit it on the grass and not the water or like the desert, because it's.
Not very helpful.
Yeah, just like go that way, all right, Avanna thanks a lot of enersherk zealous analytics really appreciate it. That's like an amazing story. I've never gotten into golf though.
Why not?
It's boring?
Yeah, I mean is it?
Is it boring? You play it? It's boring to watch it?
No, it's people are passionate about it, and oh it's I had it.
Like my kids were young. You put golf on.
It's nice and serene, it's and it keeps them yet exactly keeps them the safe.
That was my strategy with the four when when they were young.
So brilliant. Yeah, why did not think of that?
Yeah? So anyway, you got some good golf start.
Yeah, Analytics in sports, Uh, it's everywhere. It's getting bigger and teams are investing more in it.
So it's just the future.
Listening to the Bloomberg Intelligence Podcast catch us live weekdays at ten am Eastern on applecar Play and Android Auto with the Bloomberg Business app. You can also listen live on Amazon Alexa from our flagship New York station Just say Alexa playing Bloomberg eleven thirty.
We're live here today from the New Jersey Institute of Technology NJ for the cool kids in Newark, New Jersey, talking about AI and boy, there's a lot of smart people. We came to the right place for that, including our next guest, Anita Givanni Global ahead of Honor of Innovation in Avanad. Avanad was founded by Microsoft and Xcenture. Anita, thanks so much for joining us here.
Could you talk to.
Us about how you guys at Avanon approach AI. Where do you try to help out in the equation?
Yeah, So we.
Are a global consultancy, as you mentioned, Microsoft Etcenter joint venture, sixty thousand employees around the world, and what we do is think about AI from a client perspective. How is it that we can support organizations across sectors be AI first and at the same time we're all going through this journey together. So thinking about ourselves as an organization, how can we be AI first in our own business processes and for our own people.
So I'm a company, Can I come to you? What do you do for me?
We think about a lot of things. Are you guys prepared from a people perspective, an organizational perspective, and a process perspective. For example, a lot of people that we interviewed in an AI readiness report said they were enthusiastic and optimistic about AI.
That's great.
However, half of the leaders said they weren't ready and only a third of CEOs believe that their top leadership is AI fluent. So there is a dissonance between the excitement and enthusiasm and the reality of the preparedness of organizations. And what we do is make sure that organizations have the coaching and support they need to get there.
I would think one of the challenges, just speaking for myself is I learned a whole lot today speaking to again and the smart people from NJIT kind what AI is. I'm one of those people that says if you can't explain it more and sends you don't understand it, And I don't think I understand it. How do you what's the basic framework that you try to get across your clients about what AI is and what it can mean for them.
Yeah, think about AI and one of the biggest, one of the biggest generative AI tools right now through Microsoft is copilots. Think of it as a co pilot, not necessarily a replacement. Pilot that can allow you to articulating, Yeah, allow you to do your job more effectively and more efficiently.
And so instead of thinking about AI as a job replacement, think about it as a way to replace key tasks and allow you to spend your days in ways that you want to, talking to people, being more relationship focused rather than necessarily summarizing emails or going through data sets, et cetera.
So's a partner. So basically I could have some AI, think go through my email and like correlate the important parts and give it out, for example, and take it and give it to me, so I don't have to spend my whole morning going through and reading reports. Yeah, exactly. That's really cool.
Yeah, and that.
Would how much time to go do other stuff?
Yeah?
I mean think about when you come back from vacation. You probably check your email when you're on vacation. I don't, but for that exact.
Reason, because if I come back, I have like two thousand emails being gone for like a week, and I can't keep that. I can't do it.
If you had the AI tool, what you could do after being away for two weeks. I don't check my email and probably get in trouble for that, but I don't.
I can come back and say, what did I miss.
Over the last two weeks, go through all my pings on teams, go through all my outlook, and can you prepare for me a summary so that now that I come back, I can actually be ready and can prioritize. That's where it really comes into.
Wow, that's a handly cool.
Yeah, So what when you sit down with your clients, I mean, what's some of the common requests you get from them? Or you know, what are some of the what do they ask for most of the help with I guess.
Yeah.
One of the things that's really top of mind for people is about skill set and training and capability building. So in our survey, we found that eight out of ten people said that twenty hours of their work week, almost fifty percent of their work week can be replaced with AI tools. The challenges they don't know how to use the tools in the most effective and efficient way, so the training around that is critical in the process.
The other is a responsible AI A governance set, right, Yeah, what are the guard rails that we have to put into place so that people can play creatively in the space.
Do you feel like people and CEOs or board levels, do they now know what they don't know? They are beginning to figure it out, or we're still in the beginning part of that.
I believe we're in the infancy of it. I think there's an infancy of the learning curve, but also an infancy of having the right people in the room, having diverse perspectives. As we think about responsible AI.
And we're hearing you mentioned the I guess the ethical use of AI.
I don't know how that's going to evolve.
Is that going to be some partnership between public, private, the individual.
I'm not sure I actually know what that means.
Boy, it just seems like ethical use of AI.
Yeah, it just seems like the technology could get out of control.
You will look as AI and generative AI becomes more are ubiquitous. With increased scale comes increased risk. That's just the reality of things. So how do you mitigate those risks? I think one of the most important ways to do that is to have the right people in the room. So, whether that's from a diversity perspective of gender whether that's having people of color in the room, people from diverse backgrounds.
It's one of the reasons that we do the scholarship program for women in STEM at this very institute, because we want to make sure that they're not brought in as a second thought, but rather at.
The very beginning of the conversation. So, what's like an unethical use of AI? Like, where does AI get bad?
Yeah?
Well, I mean, look, you can use you can use AI to create images that don't actually exist. You can put voices on people to say things through their own voice when they may maybe have not said that video. You can think about putting in questions into generative AI that perhaps share data with the broader public that you
didn't want to share that's company specific data. So there's a security component, there's a falsification component, There's lots of different ways you kind of have to be proact and.
On this front, once again, maybe at no fault of their own, the government is generations behind where the technology is. I don't know how this plays out, I really don't. I mean, is there a feeling that the industry for a while is going to have to police itself or is there going to be some again public private partnership in terms of regulating this, because this is not the FCC regulating the airwaves.
This is really really difficult.
Yeah, it gets complicated.
Look, I think there's an individual level to it, an individual level of responsibility, But at the end of the day, it's going to fall on the leaders, the leaders of organizations across the board. If the senior leaders are not thinking about responsible AI, they're not thinking about the AI fluency, no one else is going to think about that. So the responsibility on the leaders is very high.
How do they get fluent aside from talking to you?
Yeah, well, there's a defining AI understanding and feeling comfortable with the language of AI. And then there's some very tactical things like prompt engineering. When you put in a question into jen AI and get a response, there are ways you can position that question in a more intelligent way to get a response that more aligns with your need. So there's very tactical things you can do through some more AI fluent.
What's that? I wonder what the technology we do?
We know what the technology investments can be required to be proficient in AI, because I feel like there's gonna be a lot of companies, a lot of people left behind. It's not just having the ability to have a laptop on your desk. It feels like it's a.
Lot more than that.
Yeah, I mean, we talked about this very briefly.
But data is going to be critical.
Data and AI are interlinked. So without strong data sources, the AI won't be as powerful as it has the potential to be. And so a lot of the technology investment right now, besides the people investment in training, is going to be on cleaning up and making sure that we have good, strong data to work off of.
So interesting, Anita, thank you so much, really appreciate Anita Vann. Did I say that right? We'll get it eventually? Okay, all right, we're going to get it. That will be Paul, and our quest is to get that crap.
You know.
I have to say, I feel like I learned a lot. I have a little bit of an understanding as to like, okay, now this is how people like you and I can understand it a.
Little bit, which is very cool, right, But who gets a PhD in like applied mathematics, not.
Us or what was a fluid math of something like that?
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