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