 Hello everyone, we are wrapping up the Cube's live coverage of Teradata Possible here in Orlando, Florida. I'm your host, Rebecca Knight, along with my co-host, my erstwhile co-host, Rob Streche. So it is so clear, based on just the day that we've had, and frankly, other conferences we've done together, that we are really in the era of AI, that this is really the technology that is going to redefine work, our personal lives, really everything about the way we do everything in the years to come. It's such a powerful shift in the next level of AI innovation, what, what do, I mean, where do we go from here? I don't really know, I have a question. Well, I think what's been very interesting today is this company's been around for 40 years, and I think that when people look at Teradata, they're like, oh, they're the old company that retailers used, or healthcare, or something like that, and I think what they've proven in this series of events with Possible is they're embracing innovation. This team that's here with Hillary and the VP, or SVP of Engineering, being integrated with Microsoft, and them being up here, and AWS being up here, they're not just talking about it, they're out there doing AI. They're out there with ask.ai, that's paired up with Microsoft, and with OpenAI, and they're looking at a number of the others that are doing integration with Bedrock at AWS, where you've got Anthropic. I think what's really exciting is it's really a new chapter for Teradata, and the innovation is really the lead. That's a really great point, that this company that's been around for 40 years, and this is something that we heard over and over. This is not their first time at the Rodeo with AI. They've been working in this for quite some time now, and yes, it's now become part of the national dialogue with the introduction of Chachi BT and Bard and all the others, so we're just catching up to what they've been doing for quite some time now. Yeah, and I think that's really key. People who look at AI and say, oh, wow, it's really new and newfangled, don't understand, they may have used something like Dragon Naturally Speaking. Well, hey, that's NLP underneath the hood or natural language processing, which is, by the way, AI. It's a model that's been trained on that. You talk to your car, that's another NLP model that's been trained. So I think AI has been around us for a long time. I think where you look at these unsupervised models that really is these large language models that are really new, and I think what's cool about some of the discussions that we had, even with Hillary, and I kind of look at this, is all of a sudden, everybody was going to be a vector database, and there was like thousands of them coming out. When you talk about it, it's here's why you're doing it. It's you want to have this tagging and this data that embedded into your database. Well, they're doing that, and I think that's the awakening for people to understand, you don't need 20 different platforms necessarily to go and do AI, and I think, in fact, the complexity of AI really scares people. Yeah, right, right, right. And I think that the scariness is something I definitely want to get into, but just the ideas that we've heard bandied around at this table, but also on the main stage of how companies are leveraging AI for everyday tasks, and then also to really revolutionize their businesses and even their entire industry, it's really exciting. And yet, there is a lot of skepticism, fear, anxiety when it comes to it. Not only is this, this is really powerful technology. Are we using it appropriately, or is it going to take my job, or, I mean, there's just so many levels of it, and then also the security and privacy issues too, which we've talked about today with our CISO. Absolutely, and I think it's talking about the data security gets overlooked quite a bit, and I think it was great to end on the note with him about what he's looking at, what he thinks CISO should be thinking about, because he's here, he's in this every single day, and I think that was really good. I think another piece of it that people overlook is really the cost or the efficiency aspect of it, and we didn't really get into the whole sustainability aspect of this in AI, and that's for another day, but really the cost of it, and the fact that Teradata has been putting their software really focused in a server so that it's easy to scale out server by server and unit by unit for years and years or decades, for that matter, before you get to cloud, so being able to use cloud resources extremely efficiently is key because we all know those models, those pricing models in the cloud are absurdly difficult to understand, even from somebody who worked for one of them. Yes, who understands it, so I think this is a key that it was great to hear them leaning into some of the capabilities that have been there for years or decades as well. Right, and the cost as you were pointing out too, because we had Jacqueline Woodson, you already spoken to her for a preview of what was going to be taking place here. You've mentioned Hillary, the CPO, we obviously had Steve McMillan, the president and CEO of Teradata. I mean, I think that when we look back on this conference and we think about all the conversations and all of the chatter that we've had, as I said, we're in the AI-driven era, but what are some other things that really have struck you about what we're talking about here in terms of the future for Teradata as a part of this ecosystem and really driving this ecosystem forward? I think it's that they have an incredibly loyal base of customers who've been using them for decades as well and I think it's being able to build on top of that to bring in some of the people who may have been considering one of those born in the cloud type of data warehouses or data lakes and I think being able to show how they're as good if not better is really key for them. And I think, again, talking about their invasion as Hillary was talking about as well here and in her keynote, I think that's really key to how they can go out and continue to grow as a company and really remain relevant in the data discussions out there because it is really, I would say, a very busy data platform space to put it mildly. Yeah, yeah, and the innovation in how Hillary was talking about keeping her team motivated and focused on building the next great things but also helping customers and their product organizations think big about these new technologies and tools. And I thought that was great and when we started talking about that organization, the data organization and how they're building data products and I think leaning into that, that treating data as a product and even call it a feature catalog that they're partnered up with DBT on and some others as well and I think that's a really neat place for them to be. It's not, we're not talking about this. We actually have it in the product and it's there and people are using it and I think that's really some of the awareness of that stuff has been huge in coming here and understanding, okay, yeah, these pieces beyond, hey, we have the ask.ai companion that can actually do some of the build queries for you, execute them and show you the visualization which I think is awesome and going to make people who have to do data engineering way more productive and I think that gets back to the AI. How do you make people more productive versus having the fear? Exactly, yeah. How do you make people excited about the prospect of saying, you know, we heard, I believe it was William McKnight talking about what are the things you don't like about your job? What is the most tedious task you can imagine doing? Guess what? There's an app for that, you know? There's a technology that can do that part for you so you can either go focus on something you do like doing more or find something else in some other part of the organization to focus your energy and time and resources into and that will lead to more job satisfaction and more happiness which then leads to higher attention and all sorts of good things for organizations too. Right, and I think even when we're saying that there's still a huge gap in how many people we have in these organizations, you need technologies to make people more productive and I think this, you know, definitely looking at your insights into this because this is definitely your bailiwick more so than mine, but when I look at it and go, data teams can never be big enough in these companies right now and anything that is co-pilot like their Ask.ai, co-pilot that they're doing with Microsoft, that changes the game a little bit for those companies that are leveraging in Azure and leveraging Teradata. Yeah, and but I also just want to say that as a journalist too and someone who writes for a living, I am excited by the wins of the Hollywood Writers Association that they got in their contract that are some safeguards for AI because as you were right, the data teams can never be big enough but the humans are also a really critical and important part of this. Absolutely. Yeah, and I think it's not about replacing, it's about enhancing. Yeah, it's cool. I think Swisher was talking about that around the headlines and I think we both had the same reaction which is yeah, I would do that. Like she said, 90% of them or 90 out of 100 sucked but the 10 actually are great. Or they'll give you an idea, a human being an idea for the next great one. So that's the thing. And you still have to go and actually look through those 10 and pick the one that you want as well. Yeah, excellent. Well Rob, always a pleasure co-hosting with you. Absolutely. Thank you so much for tuning in to theCUBE's live coverage of Teradata Possible. We will see you next time.