Speaker 1: Hey everyone, it's Robert and Joe here. Today we've got
Speaker 1: something a little bit different to share with you. It
Speaker 1: is a new season of the Smart Talks with IBM
Speaker 1: podcast series.
Speaker 2: Today we are witnessed to one of those rare moments
Speaker 2: in history, the rise of an innovative technology with the
Speaker 2: potential to radically transform business and society forever. The technology,
Speaker 2: of course, is artificial intelligence, and it's the central focus
Speaker 2: for this new season of Smart Talks with IBM.
Speaker 1: Join hosts from your favorite Pushkin podcasts as they talk
Speaker 1: with industry experts and leaders to explore how businesses can
Speaker 1: integrate AI into their workflows and help drive real change
Speaker 1: in this new era of AI. And of course, host
Speaker 1: Malcolm Gladwell will be there to guide you through the
Speaker 1: season and throw in his two cents as well.
Speaker 2: Look out for new episodes of Smart Talks with IBM
Speaker 2: every other week on the iHeartRadio app, Apple Podcasts, or
Speaker 2: wherever you get your podcasts, and learn more at IBM
Speaker 2: dot com slash smart talks.
Speaker 3: Hello, Hello, Welcome to Smart Talks with IBM, a podcast
Speaker 3: from Pushkin Industries, iHeartRadio and IBM. I'm Malcolm Gladwell. This
Speaker 3: season we're diving back into the world of artificial intelligence,
Speaker 3: but with a focus on the powerful concept of open
Speaker 3: its possibilities, implications, and misconceptions. We'll look at openness from
Speaker 3: a variety of angles and explore how the concept is
Speaker 3: already reshaping industries, ways of doing business, and our very
Speaker 3: notion of what's possible. I'm particularly excited for today's guest,
Speaker 3: Brian Ryerson. He's Senior Director of Digital Strategy at the
Speaker 3: US Tennis Association, helping to oversee one of the most
Speaker 3: iconic events in the world of sports, the US Open.
Speaker 3: Brian sat down with Pushkin's own Jacob Goldstein, host of
Speaker 3: the podcast What's Your Problem. A veteran business journalist, Jacob
Speaker 3: has reported for The Wall Street Journal, the Miami Herald,
Speaker 3: and was a longtime host of the NPR program Planet Money.
Speaker 3: IBM has been the official technology partner of the US
Speaker 3: Tennis Association for more than thirty years, and the more
Speaker 3: recent evolution into generative AI has enhanced the world class
Speaker 3: digital experiences that help more than fifteen million fans from
Speaker 3: all over the world enjoy the US Open Tennis Championships.
Speaker 3: In this episode, we will explore how generative AI is
Speaker 3: being used to generate match insights, spoken commentary for match highlights,
Speaker 3: and postmatch summaries at scale for fans to enjoy through
Speaker 3: the US Open app and website. We'll explore how these
Speaker 3: AI solutions enable the editorial team to cover more of
Speaker 3: the tournament than ever before, bringing fans even closer to
Speaker 3: the game they love, and will learn more about one
Speaker 3: of the engines behind this AI powered content creation, a
Speaker 3: large language model from the ib M Granite family, which
Speaker 3: is trained and maintained using the watsonex AI and data platform. Okay,
Speaker 3: let's dive in.
Speaker 4: Brian, Welcome to the show.
Speaker 5: Thanks for having me. I'm excited to be here.
Speaker 4: Can you say your name and your job?
Speaker 5: Yeah, I'm Brian Ryerson. I'm Senior director of Digital Strategy
Speaker 5: at the USTA.
Speaker 4: Some question, what's the USTA.
Speaker 5: The US Tennis Association.
Speaker 4: And tell me about the USTA, Like, what is it?
Speaker 5: Yeah? So the USTA is the governing body of tennis
Speaker 5: in the US. Or mission is to grow the sport
Speaker 5: of tennis across the US at all levels. Really, I
Speaker 5: would say we're more like a health and wellness company
Speaker 5: where tennis is the means to health and wellness. And
Speaker 5: then the US Open is kind of our tenth pole
Speaker 5: event that happens everyear and Flushing Meadows and is really
Speaker 5: our chance to showcase the support of tennis at its
Speaker 5: highest level to fans all around the world.
Speaker 4: Yeah, I mean the US Open. I assume most people
Speaker 4: know this, but it's Grand Slam. It's one of the
Speaker 4: what four biggest tennis tournaments in the world.
Speaker 5: Yes, yeah, every year, we especially the past couple of years,
Speaker 5: we've seen immense growth and you know, we are very
Speaker 5: hopeful this year and our big goals that have over
Speaker 5: a million fires on site during the three week window
Speaker 5: this year, So it's an amazing event. I always say
Speaker 5: it's a food and wine festival where tennis is the
Speaker 5: main attraction and it's a really fun, unique atmosphere.
Speaker 4: How did you get into the tennis business.
Speaker 5: It's a great question. It's not where I thought i'd
Speaker 5: end up for especially being there for fourteen years. So
Speaker 5: I was a marketing and technology major in school, and
Speaker 5: I also played college lacrosse and sports was always a
Speaker 5: big part of my life and always wanted to be
Speaker 5: in the sports and entertainment world. I'm here from the
Speaker 5: New York area. This is where I grew up so
Speaker 5: I moved back home and had a few friends who
Speaker 5: worked there, and I started out more on the number
Speaker 5: side of things and really digital analytics. It was really
Speaker 5: the start of when Facebook and Twitter is just starting
Speaker 5: and digital marketing and all of that. And you know,
Speaker 5: I went to my first year so Open not really
Speaker 5: knowing what to expect, and again, I think the atmosphere
Speaker 5: kind of captivated me and hooked me in. And I've
Speaker 5: been there now fourteen years.
Speaker 4: And so your title is Digital Director. What does that mean?
Speaker 4: What's your job?
Speaker 5: Yeah, so it's interesting one because it's tough to explain
Speaker 5: to folks who are not in the weeds on all
Speaker 5: things US open or even in the sports world. But
Speaker 5: really I oversee all of our consumer facing digital property.
Speaker 5: So that's the us open dot org, our website built
Speaker 5: by IBM, as well as our mobile app. I oversee
Speaker 5: our content strategy, our sponsorship integrations. So really anything consumer
Speaker 5: facing that happens on the web is under my purview,
Speaker 5: even some of our new platform extensions and gaming and
Speaker 5: things like that. Anything that you can physically interact with
Speaker 5: is kind of under my purview.
Speaker 4: And so you've been there now for fourteen ISSU years,
Speaker 4: which in the digital world is a long time. How
Speaker 4: has that sort of digital experience of sports changed over
Speaker 4: that time.
Speaker 5: Yeah, it's obviously grown digital now, is what we say
Speaker 5: and what my team says. It's the number one way
Speaker 5: to engage with fans that can't make it to the event,
Speaker 5: as well as those fans who are at the event,
Speaker 5: and how to enrich their stay. So it's really kind
Speaker 5: of you're tackling multiple personas. It's the international fan who's
Speaker 5: staying up late to watch in other countries, to the
Speaker 5: fan here who's maybe watching on broadcasts, and we go
Speaker 5: in a company and enrich that broadcast with new stats
Speaker 5: and insights. To the on site fan who bought a
Speaker 5: ticket and maybe doesn't know what match is happening on
Speaker 5: what court. We do have twenty plus courts happening at
Speaker 5: a time, with all different matches, So we really try
Speaker 5: to help all fans navigate the US Open the best
Speaker 5: way possible.
Speaker 4: And so, like, what are some of the sort of
Speaker 4: problems you're trying to solve. What are some of the
Speaker 4: hard things about your job?
Speaker 5: Yeah, obviously technology changes at a rapid pace, right, So
Speaker 5: I think part of it is how do we stay
Speaker 5: on the forefront of that, and how do we do
Speaker 5: that in the best way and make the best fan
Speaker 5: experiences possible and the best user experiences possible. That's always
Speaker 5: kind of driving factor number one. Then number two, it's
Speaker 5: understanding and listening to our fans and what kind of
Speaker 5: content they want. You hear me talk a lot about storytelling.
Speaker 5: I feel like there's a lot of storytelling that happens
Speaker 5: around the US open that we really want to bring
Speaker 5: to fans. And that can be as simple as storytelling
Speaker 5: of what's happening today and what you should be watching too.
Speaker 5: Maybe it's your favorite players and what's going on behind
Speaker 5: the scenes with them, to even introducing I want to say,
Speaker 5: the casual fans to who they should be watching, why
Speaker 5: they should follow certain players, and more bringing that player's
Speaker 5: story to life.
Speaker 2: Yeah.
Speaker 4: I mean, I feel like almost the whole point of
Speaker 4: sports is to like create stories for us to follow, right,
Speaker 4: Like they're engineered to be stories. It's exactly, this thing
Speaker 4: is happening in front of you and there are two
Speaker 4: antagonists and the stakes are high, and you don't know
Speaker 4: how it's gonna end, Like it's built to be a story.
Speaker 5: Yeah, And that's the main challenge of the job is
Speaker 5: you can plan, plan, plan, but once you get on
Speaker 5: two players on court and you don't know what that
Speaker 5: outcome is going to be, it's now sitting and waiting
Speaker 5: and watching and you become a fan yourself. And then
Speaker 5: it's how do you really captivate that story and how
Speaker 5: do you narrate it and how do you like translate
Speaker 5: up to fans.
Speaker 4: And it's like you kind of have to do it
Speaker 4: in real time, right, Like the whole point of sports
Speaker 4: is you don't know what's gonna.
Speaker 5: Happen exactly, and that's the excitement. And it's also there's
Speaker 5: so many different types of fans. You know, there's the
Speaker 5: fans who want a lot of enriched data and their
Speaker 5: tennis nerds for lack of better of saying it, and
Speaker 5: that they really want to dive deep into the intricacies
Speaker 5: of the game, versus the casual fan who maybe just
Speaker 5: wants more of this high level storyline of what does
Speaker 5: this mean? Why is it important? So it's really trying
Speaker 5: to figure out how to deliver that at scale and
Speaker 5: really help fans get what they're looking for and the
Speaker 5: type of content they're looking for.
Speaker 4: So are there specific examples of you know how fan
Speaker 4: feedback has led to specific features digital features you build.
Speaker 4: Are there, like particularly popular features you've come up with, Like,
Speaker 4: what are some specifics.
Speaker 5: Yeah, some low hanging fruit type things that came from
Speaker 5: fan feedback. Is simple things sometimes like managing time zones
Speaker 5: and when matches start.
Speaker 4: A persistent problem where those of us can work across
Speaker 4: times exactly.
Speaker 5: And we do have, like I've mentioned, twenty plus courts
Speaker 5: happening at a time, So it's a lot to follow,
Speaker 5: and how do you translate that to a fan, whether
Speaker 5: it's to their native language or to their time zone
Speaker 5: or things like that. So that's one thing that came
Speaker 5: through fan feedback, and another one a three to five
Speaker 5: hour match, especially when you're having twenty plus of them
Speaker 5: happening at a time, is there's too much for one
Speaker 5: person to follow. So how do you start from an
Speaker 5: editorial perspective really helping with that storytelling and guiding a
Speaker 5: fan to like, all right, whether there's an upset about
Speaker 5: to happen, or here's your matches to watch, or even
Speaker 5: some of the predictions we're starting to put in, is
Speaker 5: we really want to guide the fan before a match,
Speaker 5: here's where you should tune in to even after a
Speaker 5: match of here's what's happened, Here's what's important, and we're
Speaker 5: really excited with some of the features we've built in
Speaker 5: the last few years that I would say really helps
Speaker 5: us do that at more scale than what we were
Speaker 5: able to do with just writers following a match and
Speaker 5: covering every single match.
Speaker 4: Huh. So I want to talk a little bit about
Speaker 4: the partnership between IBM and the USTA, Like, just tell
Speaker 4: me about the work you do together.
Speaker 5: So IBM is our official digital and technology partner and
Speaker 5: innovation the US Open they predate me. It's a thirty
Speaker 5: year partnership and it truly as a partnership. So I
Speaker 5: view the IBM consulting team as an extension of my
Speaker 5: USTA team, So we work with them year round. They design,
Speaker 5: develop and deliver the digital properties. They help us provide
Speaker 5: the tools to create content to do things at scale,
Speaker 5: They help us from stats and information and really help
Speaker 5: us push from an innovation standpoint to make sure that
Speaker 5: we are staying on that cutting edge of technology. So
Speaker 5: I would truly say it's much more than a sponsorship,
Speaker 5: where it's truly a partnership to deliver that fan experience.
Speaker 4: And so What are some of the specific things that
Speaker 4: you have done with IBM.
Speaker 5: Yeah, so, I mean there's countless ones to talk through. Obviously,
Speaker 5: they thirty years ago. They helped us build our first
Speaker 5: website and it's kind of grown from there over the
Speaker 5: past few years. I would say, I think it was
Speaker 5: twenty eighteen as we started AI Highlights, So that was
Speaker 5: really when we were able to have all twenty matches
Speaker 5: going at a single time. We were able to quickly
Speaker 5: deliver succinct highlights to fans to our digital platform so
Speaker 5: they could see highlights for every single core.
Speaker 4: Is that video highlights? Is that tech summaries? What does
Speaker 4: that mean?
Speaker 5: At the time, it was video highlights, Okay, So it
Speaker 5: was really taking that three to five hour match, let's say,
Speaker 5: and cut it down to a three minute highlight that
Speaker 5: could show up within moments after a match, ending to
Speaker 5: our website and our mobile app, so fans could see
Speaker 5: that all around the world and really kind of get
Speaker 5: that three minute overview what happened in a match, and.
Speaker 4: Was that AI enabled? Was AI a piece of how
Speaker 4: to do that?
Speaker 5: It was? It was probably our first foray into AI.
Speaker 4: Back twenty eighteen is relatively early, Yeah, exactly, for tennis exactly.
Speaker 5: Yeah. It really, I want to say, opened up our
Speaker 5: ability to one again storytell but attract new fans too.
Speaker 5: Is video has actually been our number one growth area
Speaker 5: since twenty eighteen, and I think a lot of that
Speaker 5: has to do with the scale of how we deliver
Speaker 5: that content.
Speaker 4: Using AI and being able to deliver this sort of
Speaker 4: video highlight reels at scale.
Speaker 5: Yeah, and do it quickly. Right. We've always had highlights,
Speaker 5: but it was a manual process where you had a
Speaker 5: video that or cutting through you know, a three hour match,
Speaker 5: selecting the right scene, stitching together, it would have to
Speaker 5: get voiced over, et cetera. We really have used AI
Speaker 5: to make it, i want to say, much more efficient
Speaker 5: and speed up that process and deliver it more quickly
Speaker 5: to our fans.
Speaker 4: I mean, it would be a bummer to get scooped
Speaker 4: by whatever NBC News or Yes Pen or whatever. I'm
Speaker 4: sure there are all your partners and you love that most.
Speaker 4: Obviously you want to have the video first, right, it's
Speaker 4: your match.
Speaker 5: Yeah, And I think it's also important to us as
Speaker 5: being the USTA is ensuring that it's not just you know,
Speaker 5: the main marquee players, that every player and all those
Speaker 5: storylines and that whether it's you know, the main singles
Speaker 5: draw to our mixed doubles, et cetera. They all need
Speaker 5: highlights and they all have their own stories to tell,
Speaker 5: and how do we do that at scale? It was
Speaker 5: something that before we had that product was not something
Speaker 5: you were able to do.
Speaker 4: Great, So let's let's talk in some more detail about
Speaker 4: what you're working on. Let's start with the app. Tell
Speaker 4: me about the us Open app and the Companion website.
Speaker 5: Yeah, so I'll start with the app, and I feel
Speaker 5: like they serve similar needs, but they're a little different
Speaker 5: in their own respective manners. Is the app. Everybody has
Speaker 5: a phone in their hands at this point. The app
Speaker 5: is kind of their guide to when I say a
Speaker 5: million fans on site, we view the app as we
Speaker 5: want that to be their on site guide, and Companion
Speaker 5: a million.
Speaker 4: Let's just pause on a million fans on site, right,
Speaker 4: because like a big professional whatever, an NFL game or
Speaker 4: something that's like one hundred thousand, this is ten x that.
Speaker 5: Yeah, and a three week window and a very succinct,
Speaker 5: tight action packed window. There's a lot of action logistics.
Speaker 4: Okay, so keep going.
Speaker 5: So the app, you know, whether it's finding the schedules,
Speaker 5: the live scores, what's happening on court. That's really the
Speaker 5: focus point of the app, and what we're really focused
Speaker 5: on this year is how do we build in some
Speaker 5: of those map summaries into the app, into our slam
Speaker 5: Tracker experience. So again, before match, that kind of match
Speaker 5: preview of here's maybe if you have a ticket, here's
Speaker 5: what to expect, here's you know are likely to win,
Speaker 5: who we are predicting, so you can kind of get
Speaker 5: some information heading in, and then after the match it's
Speaker 5: more of what just happened, what it means for the
Speaker 5: rest of the draw, who they're playing next, is this
Speaker 5: the first time this has happened, et cetera, and really
Speaker 5: enriching that experience as well. So the app is one
Speaker 5: your guide to what you should be watching, but also
Speaker 5: then giving you that insights and context of what's happening
Speaker 5: on that court as you're.
Speaker 4: Watching, like the commentator in your pocket exactly. So you
Speaker 4: used a phrase in there as if I already knew it,
Speaker 4: and I love the phrase, but I want you to
Speaker 4: talk more about it. That phrase is slam Tracker.
Speaker 5: Yes, So slam Tracker is our long standing live scores
Speaker 5: I want to say Match Center. It is, okay, where
Speaker 5: every single data point for every single match lives, and
Speaker 5: it really it helps showcase what's happening to match. I say,
Speaker 5: it's our brock Cast companions. If you're watching live, it's
Speaker 5: our in stadium companion. And it's also the best thing
Speaker 5: to have if you aren't able to watch.
Speaker 4: And so, like, I'm on the app and there's a
Speaker 4: thing called slam Tracker, and it like taps slam Tracker.
Speaker 4: What do I see on my phone when I tap
Speaker 4: slam Tracker? You know, midday when the tournament's happening.
Speaker 5: So before match, that's where you get a lot of
Speaker 5: pre match content. That's where those live kind of our
Speaker 5: predictions are likelihood to win lives within that So likelihood
Speaker 5: to win essentially pulls in a bunch of data points.
Speaker 5: So pass matches, how many times these players have played
Speaker 5: each other against each other, even some punditry and other
Speaker 5: written articles that maybe our editorial team put out and
Speaker 5: really kind of puts a prediction out there.
Speaker 4: And so it's just a percentage chance.
Speaker 5: Yes exactly, but it uses millions of data points to
Speaker 5: come up with that. Yes, So it really helps you
Speaker 5: kind of understand what you're getting into for that match.
Speaker 5: During a live match, it is every single point, so
Speaker 5: point by point scoring as well as in depth analysis
Speaker 5: in point commentary where also this year have a live
Speaker 5: visualization that accompanies that will really help bring the match together.
Speaker 5: And what I mean by that is it uses our
Speaker 5: ball tracking technology to really showcase the match in near
Speaker 5: real time, so within seconds delay of where the ball's
Speaker 5: being hit, where the players are, and really bring a
Speaker 5: visualization to life and layered stats and data on top
Speaker 5: of it.
Speaker 2: Huh.
Speaker 4: Is that sort of like when I'm watching a match
Speaker 4: on TV and there's like a close call as the
Speaker 4: ball in or out and they do that thing where
Speaker 4: they kind of show a sort of video game version
Speaker 4: of where the ball landed. Does it look like that?
Speaker 5: It's like that before every single shot, So it's not
Speaker 5: just those close ones. It's our first foray to bring
Speaker 5: that match to life.
Speaker 4: Huh. And so what do I see on that kind
Speaker 4: of view that I don't see from whatever watching the video?
Speaker 5: Yeah, So one you'll be able just to see more
Speaker 5: of the ball trajectory and where the ball is being hit,
Speaker 5: but then you can also start layering things in stats
Speaker 5: and insights on top of that, so how many times
Speaker 5: has player A hit the ball on a certain baseline,
Speaker 5: how fast are they hitting it, maybe their serve percentage
Speaker 5: and a certain side of the court, et cetera. So
Speaker 5: you can really start layering in for the ones that
Speaker 5: really want to. I've deep into the for the nerds.
Speaker 4: It's for the information rich exactly.
Speaker 5: It's the strategy of tennis. It really should be an
Speaker 5: interesting way to slice and dice a match.
Speaker 4: Huh.
Speaker 3: It's remarkable how the USTA is leveraging AI to enhance
Speaker 3: fan engagement and deliver immersive experiences both on site and online.
Speaker 3: Brian's emphasis on storytelling really underscores the evolution of sports marketing.
Speaker 3: The slam Chakra feature particularly caught my attention. It's essentially
Speaker 3: bringing the excitement of a tennis match to life in
Speaker 3: your palm, moment by moment. As someone who appreciates the
Speaker 3: narrative intricacies of sports, I find it compelling how AI
Speaker 3: helps predict and analyze matches in real time.
Speaker 4: Tell me about the AI commentary feature.
Speaker 5: Yeah, I know. I mentioned AI highlights back in twenty eighteen.
Speaker 5: It's now progressed for us. And again, if we go
Speaker 5: back to before we had a highlights to have a
Speaker 5: highlight ready for this was a video editor cutting the
Speaker 5: highlight and getting voiced over and then being published aside,
Speaker 5: and it took probably an hour plus for that highlight
Speaker 5: to really be created. Now with AI commentary, not only
Speaker 5: are we creating and cutting the highlights using our AI technology,
Speaker 5: but it's now using all the data points that we
Speaker 5: have around the match, whether it's our live scoring data,
Speaker 5: our ball tra directory data, etc. And it's really creating
Speaker 5: a script that helped storytell around that match. That's all
Speaker 5: using Watson X technology and then using text to speech
Speaker 5: we're able to actually then create the commentary on top
Speaker 5: of that, which all happens now within minutes. So our
Speaker 5: team's able to now create fully voiced highlights for every
Speaker 5: men's and women's singles match to our site within minutes.
Speaker 4: So I know there's a new feature you're working on
Speaker 4: for this year called match reports. What are match reports?
Speaker 5: It's our ability to succicktly tell the story of a match,
Speaker 5: so everything happens in five hours within that match down
Speaker 5: to a couple paragraphs that really helps a user understand
Speaker 5: or a fan understand what just happened. Again, some key
Speaker 5: stats what's upcoming really help us with that storytelling. In
Speaker 5: the past, when we have twenty two courts happening at
Speaker 5: a certain time, we would have to pick and choose
Speaker 5: which stories we think or which matches we think are
Speaker 5: going to have the best stories, and that's a really
Speaker 5: hard thing to predict from an editorial perspective. With our
Speaker 5: match reports now we'll be able to have full coverage
Speaker 5: of every single match during the main draw.
Speaker 4: So, of course I want to talk about jeneritive AI.
Speaker 4: How could we not talk about generative Of course, what
Speaker 4: are you working on with jenitive AI?
Speaker 5: So match reports is the prime example of it. So
Speaker 5: Match Reports will be completely using Watson next genera of
Speaker 5: AI technology, And really again to us, it's how can
Speaker 5: we do that storytelling at scale? Tennis is such a
Speaker 5: data rich sport. All sports have data, but tennis has
Speaker 5: a lot of shots and different shot types and ball
Speaker 5: trajectory and live scoring data and umpire chair data and
Speaker 5: and all that. Factoring in jeneral of AI really helps
Speaker 5: us take some of that structured and unstructured data really
Speaker 5: one organize it in a way, but then help us
Speaker 5: quickly tell that story at scale to all of our fans,
Speaker 5: and I think we're really just starting to scratch at
Speaker 5: some of the capabilities, and we're really excited about where
Speaker 5: we're being, but we also see the opportunity of even
Speaker 5: how we can grow to new fans and new fans
Speaker 5: around the world using jener of AI in the future.
Speaker 4: So I'm curious, and you alluded to this a moment ago,
Speaker 4: but I'd like to talk a little bit more about
Speaker 4: it because it seems interesting as a technical problem. Right,
Speaker 4: is the nature of turning tennis matches into stories, which
Speaker 4: is fundamentally what we're talking about here in different ways
Speaker 4: in different media, is about taking both structured data, right
Speaker 4: like the stats who you know, points stats matches, and
Speaker 4: also unstructured data, right like commentary and articles and the
Speaker 4: kind of fuzzier parts of storytelling. And so I'm curious
Speaker 4: how AI kind of helps you manage both the structured
Speaker 4: and the unstructured data.
Speaker 5: Yeah. So, I think the structured data is pretty self experimentatory,
Speaker 5: but when you get into the unstructured data and some
Speaker 5: of the punditry, that's where you get more of the
Speaker 5: opinion pieces into it. Like a specific player matchup, this
Speaker 5: player always plays well against so and so, or as
Speaker 5: they play always played well at night, or they're a
Speaker 5: fan favorite and the crowd, you know, adrenaline and the
Speaker 5: crowd being behind you can really motivate you to play
Speaker 5: a lot better. So it pulls in all those unstructured
Speaker 5: pieces and helps us really put some more rigor around
Speaker 5: it and help add and enrich our storytelling with it.
Speaker 4: And so I'm curious when you're starting to use generative AI,
Speaker 4: you know, over the past few years, like, what were
Speaker 4: your concerns going into that.
Speaker 5: I think our biggest concern is ensuring that one factually
Speaker 5: it is correct, because it's only as good as the
Speaker 5: data you feed in. And how do you really ensure
Speaker 5: that your model's working right and that the output and
Speaker 5: the data you're feeding it matches the output, and how
Speaker 5: do you do that at scale? So we do have
Speaker 5: a lot of human intervention. That's where the IBM consulting team,
Speaker 5: they're on site with us for those full three weeks
Speaker 5: really helping us review everything and we're constantly learning, especially
Speaker 5: early in the tournament. And I would say the other
Speaker 5: big concern, again it goes around to the data, is
Speaker 5: what data do we have available that is trustworthy? So
Speaker 5: you know, we are feel very confident with the data
Speaker 5: that comes off of court, but when we get into
Speaker 5: that unstructured piece, what are the right data sources? How
Speaker 5: do we validate those data sources and how do we
Speaker 5: ensure that they're accurate Because if the data that has
Speaker 5: to go in has to be accurate for the for
Speaker 5: the output.
Speaker 4: So how do you do that? That's the concern? How
Speaker 4: how do you address it?
Speaker 5: Yeah, so I think there's there's a number of tools
Speaker 5: that we use all within the Watson X umbrella. We
Speaker 5: do a lot of training with the IBM team, so
Speaker 5: we have to constantly train and retrain that model. I
Speaker 5: think the other piece that we're doing is again as
Speaker 5: we're creating that content and we have the IBM consulting
Speaker 5: team on site helping us with that, is as we
Speaker 5: see things and we see outputs, it's refeeding that back
Speaker 5: into the model to make it better for the next time.
Speaker 5: So it's a constantly learning process that we're undergoing.
Speaker 4: So I want to talk about scale. Yes, you have
Speaker 4: like what twenty two different courts with matches going all
Speaker 4: at the same time. You're trying to, you know, approximately
Speaker 4: instantly generate summaries of all these matches in something like
Speaker 4: real time, and I'm curious in particular how the IBM
Speaker 4: models you're using, the IBM Granite models are helping you scale.
Speaker 5: Yeah. So I think one of the big learnings we
Speaker 5: had with IBM granted models too is that we're able
Speaker 5: to run it, you know, against last year's tournaments and
Speaker 5: see what the expected outputs could be and really help
Speaker 5: train that model heading into the tournament. Because as we
Speaker 5: talked about in the beginning, is we can plan, plan,
Speaker 5: and plan, but once two players get on court, the
Speaker 5: outcome is unknown. So how do we really run it
Speaker 5: through its paces and really make sure that whatever that
Speaker 5: outcome could be and whatever that scenario is, whether it's
Speaker 5: a fifth set tie break that happens, or maybe there's
Speaker 5: a you know, a fault in the match or something
Speaker 5: that we're not anticipating, that we have that accounted for
Speaker 5: and that the a won't throw off that output. So
Speaker 5: we really try to think through every scenario, which is
Speaker 5: sometimes difficult, right because again live sports is the unknown
Speaker 5: is the unknown that's what makes it fun. We do
Speaker 5: spend a lot of time thinking through potential scenarios and
Speaker 5: ensuring that we have the right data sets and the
Speaker 5: model to predict that tell.
Speaker 4: Me about match reports and the generative AI model you're
Speaker 4: using for that.
Speaker 5: Yeah, so match reports will be new for us this year,
Speaker 5: So we're in testing right now, so we're really excited
Speaker 5: around it. But the model that we'll be able to
Speaker 5: use using Watson X will use a bunch of different
Speaker 5: parts of the suite of tools A meaning that again
Speaker 5: of taking some of that punditry and the unstructured data
Speaker 5: and the editorial spend, take our structured data as well.
Speaker 5: And really what we're working on right now is figuring
Speaker 5: out the right prompts for the AI to really ensure
Speaker 5: that it tells the right structured story, meaning what just happened. Right,
Speaker 5: So our recap is pretty standard. Here's what the data
Speaker 5: is telling us, who won, who lost, how many sets?
Speaker 4: Here's the score the structured data part, that's the easy part.
Speaker 5: Yeah, and then really where it gets exciting is then
Speaker 5: what does this mean? Meaning what's upcoming? So there's all
Speaker 5: these different scenarios when you get into you know, two
Speaker 5: hundred and fifty four players and a large draw. This
Speaker 5: allows us to distill that down and really tell kind
Speaker 5: of what could happen upcoming. The AI helps us do
Speaker 5: that at scale.
Speaker 4: So I want to sort of generalize for a moment
Speaker 4: to talk about kind of you know, broader challenges with
Speaker 4: AI and how you've solved them. You know a lot
Speaker 4: of generative AI pilots fail because the data quality isn't
Speaker 4: high enough, because the risk controls aren't there, and so
Speaker 4: I'm curious how you dealt with those problems and are
Speaker 4: dealing with them data quality.
Speaker 5: Again, we feel calm with the data that is supplied
Speaker 5: from the US open and from the USTA. Right, So
Speaker 5: we have again that's our structure, scoring data and all that.
Speaker 5: I think what we're constantly looking at is when we
Speaker 5: get outside of our known sources and out to third
Speaker 5: parties is that's where a lot of the testing and
Speaker 5: model work happens. So we pull in different data sources
Speaker 5: and really try to work through how it changes that output. Again,
Speaker 5: some of that comes down to where it's an open
Speaker 5: model and the transparency that we have and the learning
Speaker 5: that comes behind it. That's where a lot of that
Speaker 5: confidence can come from, and it comes from a lot
Speaker 5: of testing and feeding it more data. Your second question
Speaker 5: was a little bit more around the output I believe.
Speaker 4: Right, Yeah, and risks right, So risk, I think of
Speaker 4: risk more in terms of output, right, But the obvious
Speaker 4: sphere is like what if it says something wrong? Yeah,
Speaker 4: inflammatory or whatever like that seems scary?
Speaker 5: Yeah, it definitely is, and it's definitely one of our
Speaker 5: largest concerns when we first took this. FORAY, I would
Speaker 5: say a lot of that comes through our work with
Speaker 5: IBM and I consulting team and really ensuring that again
Speaker 5: they're an extension and the partnership there of our team.
Speaker 5: So whenever we are creating let's say it's the match Report,
Speaker 5: and we're going to be creating these excinct articles for
Speaker 5: every single men's and women's single match that happens, is
Speaker 5: all of those will have manual review and people looking
Speaker 5: through them for accuracy to ensure that the model then
Speaker 5: hallucinate or make up a factor or fill in the
Speaker 5: gaps from things like that. That's the first step. And
Speaker 5: then also when our editorial team goes to publish those
Speaker 5: of the website, they're going to be checking it as well.
Speaker 5: So there are manual interventions throughout that to really check
Speaker 5: that model. But we feel that the ability to do
Speaker 5: it at scale and with us more to check that
Speaker 5: is the efficiency problem that we've been looking to solve.
Speaker 4: So the USTA and IBM have been working together on
Speaker 4: digital innovation for like thirty years from you know, the
Speaker 4: first website, yes for the USTA until now. So that's
Speaker 4: the past thirty years. If you look ahead, what's the next.
Speaker 5: Thirty thirty years is a really long time?
Speaker 2: Agree?
Speaker 6: Yeah, I think you know where I get excited, and
Speaker 6: I think I alluded to it in the beginning about
Speaker 6: how I feel like we're just scratching at the surface,
Speaker 6: especially with Journati of Ai, and where I see it
Speaker 6: going is there's a lot of different fans out there,
Speaker 6: and we're also very kindness in the us OP and
Speaker 6: that we're a worldwide event, and that there's a lot
Speaker 6: of different fans that were not necessary creating content for
Speaker 6: bespoke meaning in their native language or maybe it's in
Speaker 6: that native players language and things like that.
Speaker 5: Is where I get excited is we've seen immense growth
Speaker 5: with a Highlights and the ability to now do highlights
Speaker 5: at scale. Is the ability for us to start creating
Speaker 5: content in different languages, maybe covering different parts of the match.
Speaker 5: So maybe you do have that stats junkie you really wants,
Speaker 5: just it's the fastest serve and here's the deep insights
Speaker 5: versus the casual fan who's looking for more of the
Speaker 5: storytelling around how a player trains and what leading up
Speaker 5: to it was like and what it means for them
Speaker 5: afterwards and things like that. A lot of that takes
Speaker 5: a lot of time. Now we're able to solve that
Speaker 5: efficiency problem and do it in multiple languages, we can
Speaker 5: really create I want to say, personalized content to a
Speaker 5: lot more fans all around the world, which again helps
Speaker 5: us grow the sport of tennis great.
Speaker 4: So I want to finish with a speed round. Okay,
Speaker 4: are you ready?
Speaker 5: I am ready?
Speaker 4: Okay, first thing that comes to mind, complete this sentence.
Speaker 4: In five years, AI will.
Speaker 5: Transform many parts of the business.
Speaker 4: What is the number one thing that people misunderstand about AI?
Speaker 5: That it's supplemental, not replacing, meaning that it helps it
Speaker 5: with efficiencies, but it doesn't necessarily replace the creativity.
Speaker 4: Right now, what advice would you give yourself ten years
Speaker 4: ago to better prepare you for today?
Speaker 5: I think it would have been, especially now that we're
Speaker 5: able to take so much of that unstructured data and
Speaker 5: pass content that we were created to help tell st
Speaker 5: was to I want to say archive more of that
Speaker 5: in a way that we could be using that to
Speaker 5: help pull from that now. So you know, we've seen
Speaker 5: kind of a change in the guard from some of
Speaker 5: our star players to now new and up and comers,
Speaker 5: and it would be really fascinating to me if there
Speaker 5: was a way to to cross sections some of that
Speaker 5: and saying like what tra directories are certain up and
Speaker 5: coming players maybe filing from others. So it's more I
Speaker 5: wish we kept more of the content.
Speaker 4: We created back fave the data exactly. Well are you
Speaker 4: saving it all now?
Speaker 5: Oh yeah, one hundred percent learned our lesson?
Speaker 2: Yes, yes.
Speaker 4: So on the business side of AI, what do you
Speaker 4: think is the next big thing?
Speaker 5: I alluded to it earlier. I think it's personalization and
Speaker 5: getting content that's catered to you at scale, whether you
Speaker 5: know that's across the sports sphere or or any type
Speaker 5: of written content or or news content. I feel like
Speaker 5: the ability to really get contentated to the type of
Speaker 5: fan you are and the insight you have is where
Speaker 5: we're all headed.
Speaker 4: And in terms of your non work life, how do
Speaker 4: you use AI day to day?
Speaker 5: It's funny, I was just having this conversation with a
Speaker 5: friend the other day, and we were talking about sometimes
Speaker 5: when you're starting something new, the hardest thing to do
Speaker 5: is you have a blank piece of paper or a thought,
Speaker 5: and how do you get started. Sometimes with these generative models,
Speaker 5: the easiest thing and the best thing you can do
Speaker 5: is it helps you get started. Meaning it may not
Speaker 5: be one hundred percent with that first prompt, but it's
Speaker 5: that efficiency of whether it's an outline for a new idea,
Speaker 5: or it's a marketing brief you have to write, or
Speaker 5: sometimes even if it's an email you have to write
Speaker 5: for a personal something and you're not sure how to
Speaker 5: word it the right way. It allows you to have
Speaker 5: a start and then you can edit from there. So
Speaker 5: again going back to my efficiency point, it helps you
Speaker 5: become more.
Speaker 4: Efficient, solves the blank page problem.
Speaker 5: It does.
Speaker 4: Brian, it was great to talk with you. Thank you
Speaker 4: so much for your time.
Speaker 5: Yeah, this was fun. Thanks for having me.
Speaker 3: Huge thanks to Jacob and Brian for the deep dive
Speaker 3: into the cutting edge innovations transforming the game of tennis.
Speaker 3: Brian shed light on how the US opens partnership with
Speaker 3: IBM is harnessing data driven insights to reshape storytelling in sports,
Speaker 3: from AI generated commentary to Match reports. As we look ahead,
Speaker 3: I'm excited about the possibilities for personalizing content and reaching
Speaker 3: fans in new ways. The future of AI promises more
Speaker 3: than just efficiency. It's about enhancing fan experiences worldwide. Smart
Speaker 3: Talks with IBM is produced by Matt Romano, Joey Fishground,
Speaker 3: and Jacob Goldstein. We're edited by Lydia jen Kott. Our
Speaker 3: engineers are Sarah Bruger and Ben Tolliday. Theme song by Gramascow.
Speaker 3: Special thanks to the eight Bar and IBM teams, as
Speaker 3: well as the Pushkin marketing team. Smart Talks with IBM
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Speaker 3: To find more Pushkin podcasts, listen on the iHeartRadio app,
Speaker 3: Apple Podcasts, or wherever you listen to podcasts. I'm Malcolm Gladwell.
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Speaker 3: this podcast don't necessarily represent IBM's positions, strategies, or opinions.