Data At Scale For AI At Scale: How To Think About Data Readiness

[Dominic]

Ever wondered how to bridge the gap between AI's potential and practical implementation? At SnapLogic's Integreat 2024 in London, Dominic had the pleasure of recording live with Maks Shah from Syngenta, who enlightened us with her perspective on the "agent-creator" concept. Maks shares how this intriguing idea, highlighted in presentations at Integreat from industry leaders including LEGO and Spotify, sparked her curiosity. Immersive experiences, like the GenAI Escape Room lab at Integreat, facilitate understanding by connecting theoretical concepts with hands-on application, resonating with a diverse audience eager to harness technology.

Join us as we explore the relationship between innovative AI technologies and the foundational data readiness crucial to their success. Maks emphasizes the importance of having data that is primed for AI applications and how this groundwork can set the stage for future breakthroughs. While the allure of AI's promise captivates many, the real challenge lies in ensuring data is fit for purpose—an area where Maks and her team are laser-focused.

Listen in to discover how these themes shaped conversations at the Integreat event and what they mean for your own AI and data integration journey.

Find more from Maks Shah here: https://www.linkedin.com/in/kiamosshah/

The event page for Integreat 2024 is here: https://www.snaplogic.com/integreat-tour/london Register to be notified when recordings will be available!

Transcript

Dominic Wellington: 0:00

Welcome to a special live recording of the Enterprise Alchemists. This is a podcast by SnapLogic for enterprise architects, and we are here at SnapLogic's Integreate 2024 in London, together with Max Scharf, syngenta. Welcome, max. Welcome to the live recording of the show.

Maks Shah: 0:17

Well, thank you very much for inviting me. It's a pleasure to be here.

Dominic Wellington: 0:20

Great. T those of us who are here at the show very much enjoyed your presentation, and so what I wanted to talk about, thank you for giving us a couple of minutes, and this is during the cocktail hour for the listeners, so we, at the very end of the day, we've been able to sit through a whole lot of very interesting presentations, and so, first of all, I just wanted to get your reaction. What was your main takeaway from today? What was the thing that turned on a light bulb above your head?

Maks Shah: 0:52

Well, the thing that got me very interested and very curious was the idea of agent-creator. It was a very strange moment for me because, on one hand, I was very, very excited and then, on the other hand, I was very, very humbled, because this is an area I really don't feel I understand and I want to learn more about now after seeing the various presentations and talks, especially what was coming out of LEGO and also a couple of the others.

Dominic Wellington: 1:27

So that is a very common reaction. I've heard that a lot. So one thing is so this morning I was running a Gen AI escape room, and that's a hands-on lab where you get to use the technology to go through a number of challenges, one after the other, and it works like an escape room. You get to the end, you get out of the room and you have achieved three or four different hands-on tasks with the tech. And so what was interesting to see was that, as Jeremiah was going through his demo on stage of the agent creator, the people who had been in the morning session, all of these light bulbs were going on, because these were the same components they'd been using in the morning the snaps and the pipelines and the things, and so when Jeremiah was showing them, they were like, oh, I recognize that.

Dominic Wellington: 2:14

And so that's something that I would advise you and I would advise the listeners. It's something that we also do outside of these events. If you want, we can come out to your offices, to your site, and we can do something with your teams to give them that light bulb moment, because, yes, there is that moment of "this stuff is all so cool, but what does it take to get that? But that's what I took away from your presentation, because you had that moment. What was it? Data at scale enables ai at scale. That was the big takeaway for me from your presentation.

Maks Shah: 2:46

Yeah, I think everyone is excited about the promise of what AI will bring and everyone is excited about experimenting, but I think, there was also a common theme throughout all the presentations this afternoon, and that was that your data has to be fit for it, and I think a lot of us, what we're struggling with right now is there are things we want to do, but our data is not fit for it, and we're busy actually trying to get that to happen. And, on the one hand, it's frustrating because you're doing this, because you want to get to the next thing you want to do.

Dominic Wellington: 3:21

To get to do the cool thing.

Maks Shah: 3:22

Yeah, exactly, but you've got to do all this foundational work still, and that's very much where me and my team come in. We're obsessed about the foundation, we're obsessed about data and we're obsessed about getting our data AI ready.

Dominic Wellington: 3:39

I mean, that is already setting you up for success, because we recorded the session with Jeremiah Stone earlier this week. Depending on which order you're listening to the podcast, this may be before or after the current episode, but we were talking about the failure modes. Because, depending on who you talk to, Gartner and Bain and Rand Corporation, interestingly there's like an 80 plus percent failure rate for these projects, for the ones who try to jump ahead too fast, too far and they don't do the boring work of getting the data ready, and so I think you're well set to maybe take a little bit more time to reflect, but have a higher rate of success, ideally, than 15%.

Maks Shah: 4:20

I'd love to be part of that 15%.

Dominic Wellington: 4:23

15% is good, but we'll try to make that 50%, why not? And it doesn't have to be 100% Again, Jeremiah said this, and Brian Dumman from AstraZeneca also said, you know, not every idea that sounds plausible is going to be fit for it, but the trick is figuring those out and filtering them and enabling the good ones.

Maks Shah: 4:43

Yeah, I mean I'm quite fortunate I'm in research and development, so this is the part of the company, obviously, that experiments and innovates a lot and that's core at who we are. And I think this is the other thing that's so very inspiring being here is that you hear about people who are actually just going out and trying, understanding and then adapting and going on to the next experiment .

Maks Shah: 5:15

Like I said, I'm humbled, but I'm excited, and I can't wait to learn more about this.

Dominic Wellington: 5:22

Yeah, that was the other big takeaway for me from your presentation that before digital technology in your world, in the agricultural world, your cycles were annual. Maybe you got a couple of cycles in tropical climates and whatnot, but that was the speed that you could iterate at. And with digital tech you can iterate hundreds of times in that same time span and try many more experiments, and sure, a bunch of them will fail. But the failures are also informative.

Maks Shah: 5:51

I think that's the thing. At the end of the day, digital science is another tool in a scientist's arsenal, just like the microscope was for biologists. We accumulate these various tools. Accumulate these various tools, and the power of digital science, I think, is the fact that you can conduct experiments virtually that you wouldn't even want to try in the real world Because, frankly, they're too risky or they're too wild. But here on your laptop, you have the ability to actually create a universe and run experiments that you couldn't do otherwise.

Dominic Wellington: 6:41

Explore the very edges of the envelope. Well, thank you very much. It's been a long day, so we won't keep you any longer, although I'm sure people will have all sorts of questions, but thank you for taking the time For the listeners, Maks Shah of Syngenta. I will put some links in the show notes so that you can find her online and you can follow up on what Syngenta is doing with SnapLogic. It's a great story and there's a lot of nuggets of information. But for now, thank you once again.

Maks Shah: 7:08

Well, it was a pleasure and thank you for having me.