The Exchanges

Q guess like in the context of, um, Square and its foray into AI, there's a set of areas that traditionally have been areas where payments companies have sort of applied ML, you know, so that'd be things like fraud detection or other areas like that. Um, can you tell us a little bit about how that evolution occurred at Square and what areas you, you find most intriguing going forward?

A Well, as you state in financial services, um, application of machine learning has, um, you know, has been key for a long period of time, and particularly if you look at the, you know, a business like Square, where you've got millions of small customers, and it's, it's not a, what you're, you don't really have a one-to-one relationship with the vast majority of your customers, just because the scale and the size of them, um, you really have to bring technology to bear in terms of, Understanding like a whole range of things from, you know, who's a good actor and who's a bad actor, um, to, you know, who do you target for a specific product? Who, who's going to be most likely to find, you know, a marketing product useful or least likely to find it useful or that sort of thing. So there's lots of internal applications and have been for years, um, in terms of machine learning, manage risk, you know, manage fraud, um, As well as to cross sell and grow the business. And then more recently, even kind of prior to this kind of latest, um, big shift in the AI landscape, you know, we, we were using GPT two, um, as part of us, the square messages product, um, being, uh, you know, a virtual assistant to help, um, customers, you know, answer responses to customer inquiries and variety of things. But what, what's so exciting to me about, um, Kind of really how the landscape has changed and the …

AI assessment note: “we were using GPT two, um, as part of us, the square messages product”

Q GM for AWS storage. And, um, you know, just beyond storage to responsible for a huge number of innovations and computing that we all use now as three Glacier, Lambda, EBS, I'm missing some. Um, how do you think about like, there, there are a lot of, uh, there's a lot of discussion of AI changing the cloud services. Like, do you see this as a new wave of computing?

A I mean, certainly there's a bunch of new aspects to it. Um, you know, cloud computing historically, you know, very, very CPU intensive, some GPU as well too, um, various use cases, but obviously, you know, AI just seeing an explosion in GPU based compute. Obviously there's tons of demand right now just for compute capacity, um, for training. It's not replacing existing workloads. It's adding new workloads. Um, As people are figuring out how to then expand, you know, companies like square block, figuring out then how to, you know, how are we going to apply these technologies? And then where do we, where are we going to go do You know, go do our training and, and whatnot. So I, I think it's an exciting time. Um, you know, one of the fun parts about being in technology is like, you just, you get these big shifts that happen. Um, you know, so it's never a tall moment. And, uh, I, I think the race is definitely heating up and, you know, it's in many ways, I think it's a land grab and, you know, lots of different players are figuring out how they go grab land.

AI assessment note: “It's not replacing existing workloads. It's adding new workloads.”

Q like a single natural language call versus if you contrast that to, um, like what, you know, the joke is you can't even keep track of like the Amazon services released, right? Like, do you think we get a wealth of services over time the way many services have emerged in cloud or it's just you, you lob in, you know, more and more complicated prompts to a single model?

A Um, it's probably both. Um, the, you know, if you go back AWS at the beginning, right, um, you know, S three was sort of the, you know, the first S Q S was actually technically the first, but S three was really kind of the first service and incredible, simple, incredibly simple API. Right. Um, like, you know, for rest operators or something, what was compelling about it is it was so easy to use. Right. Um, And then, obviously, a whole bunch of stuff sprang up around it. You know, S-three became not just, you know, a first, well, it was a first-class service zone, right, with, you know, direct customer relationships, but it became foundational as well for many of the other services that were built on top of it, right? So you go, you go trace kind of the, you know, the call stack, if you will, within most AWS services, probably, I would argue probably all of them, you know, you can go find S-three somewhere as a component of it. Take OpenAI started, you know, relatively simple, but, and, you know, adding to stuff, in fact, making them, you know, ease of use actually, even though adding a new capabilities in some ways, adding functionality that makes call patterns even simpler, right? With threads and messages and some of these other things. And so I suspect we'll see, continue to see an evolution where we're going to get some more capabilities that extend some of the core foundat…

AI assessment note: “Um, it's probably both.”

Q Right. And I think it's, I think, first of all, that was like the, one of the most terrifying business conversations I've ever had. You were perfectly nice about it, but I was just like, oh my What am I doing doing these open source companies? She's right. This is terrible. Um, what do you, what do you think, um, happens in that landscape of like the open source models?

A Um, well, there's certainly demand, like there's strong customer demand for open source models, right? Um, for enterprise demand for it, right? Cause it's, uh, it's not quote black box. Um, you theoretically could, In-house at all if you wanted. Um, so I think, you know, anytime there's, there's demand, you know, the products will find a way into the marketplace and any time there's a passionate developer community who, you know, is interested both in sort of giving to the community, but also it's a way to make your name as a, you know, as an engineer too, by participating in these projects and, you know, being a core commit or whatnot. You know, I think open source is going to Continue to evolve. The question is, is, yeah, where, where and how do you make money off of it? Obviously, you know, there, there are some companies that, you know, have done well, taking open source or some of the founders or, you know, the, the project or whatever, and then, you know, launching companies around it. I put, Confluent, um, with Kafka in, in that bucket. Um, but yeah, there've been some others that have struggled, you know, who dupe was there for a while, but kind of never, never quite got the commercial piece working well. Um, and I think just time, not, not enough than differentiation, um, relative to what the cloud providers could do. Um, pick up and, and go out. And, you know, I think…

AI assessment note: “there's strong customer demand for open source models”

Q just kidding. Um, you know, you've had, I think one of the most impressive careers in technology and all sorts of different ways. You've been involved with some of the most important companies in the world and literally every decade that you've operated, you've been at the most or one of the most important companies. What's next? Like, how do you think about the next couple years, the next decade?

A Um, I don't know. Uh, it's a good question. It's one I'm working on figuring out. Um, My husband retired from work two years ago. I've lost two years, and he'd be like, Alyssa, come out and play with me. Come play with me. I'm like, ah, I'm working. I like it. We're working 78 hours a week, right? It's like, what are you doing, girl? You know, so, um, and I'm like, well, um, so, you know, I think, obviously, I like, I love technology. I love deep technology. Square was super interesting. It was the highest up the stack I'd ever really worked. It was first time ever working on, you know, financial stuff. Intel and Confluent and whatnot, kind of helped scratch the itch of, I still, like, fundamental technology, like, it's fundamental, right? I mean, there's something, there's something to it. And so, still reading stuff, still like, you know, watch the, you know, watch the Open AI Dev Day, right? You know, tinkering around, but he's, my husband's trying to keep me as busy as possible. And running around with him. So we'll see. I don't know. Um, I don't know if it's going to be a permanent retirement or, uh, you know, or a sabbatical, you know, a sabbatical kind of thing. Don't know. We'll see. I'd love to hear, like, what are you guys most excited about in this space? If you could pick kind of one thing, what are you, you know, for the next year ahead, what do you, what do you ho…

AI assessment note: “I don't know if it's going to be a permanent retirement or, uh, you know, or a sabbatical”

Q use this technology Before most people were aware that this was a big deal. And then to your point, there's some really interesting things that you've been doing in terms of merchant coaching and other areas that, you know, I think are really fascinating. Are, are there big areas of e-commerce that you just think are going to be swept up in this technology that people aren't talking about enough?

A Well, I think almost every aspect of kind of a small business, you can find applications and, you know, some of the technology is not quite there yet, um, but is rapidly getting there in terms of some of the Finance and numbers and quant pieces. Um, you know, some of the, the quantitative hallucinations have been a little bit more than, um, than the others, but, but it's all rapidly going. And I think it's, you know, if you look at the largest e-commerce players, you know, the Amazons and the Walmarts, right? Like they've been investing heavily in this area. So, you know, the, the larger e-commerce companies, Um, have definitely embraced, and frankly, in e-commerce in general, it's been for these retailers or for e-commerce retail platforms, because one of the things is, um, if you're in e-commerce, basically everything's already digitized. So, um, one of the differences between, um, in-store commerce and particularly local commerce and, um, and e-commerce is the fact that, you know, just to basically to operate in e-commerce, you have to, you have to digitize You know, you have to have images to, you know, show what your product is. You have to show, you, you have to have, you know, compelling description of it. You have to track inventory, you know. So there's a bunch of stuff you have to have, which many, this is, again, some of the white space for small businesses, local bu…

AI assessment note: “I think almost every aspect of kind of a small business, you can find applications”