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[0:00]Hello, I'm here at the IBM booth with Dave and we're talking about IBM Watson and AI and what's going on. And the first thing I want to ask you is, what do you, what are you seeing as far as what enterprises are doing with AI these days? Well, there's been an explosion of interest in AI over the last year, right, with all the generative capabilities and large language models that have come out. What we're seeing is a lot of our enterprise clients are focused on how they can take this technology and infuse it into their business to solve real problems and add real value. So whether that's around improving customer service, whether that's around helping to generate better code more quickly, whether that's around helping accelerate research and development and things of that nature, we're seeing enterprises really start to embrace the technology and put it to work. And that's important, you know, we're doing a lot of things as far as not just, you know, you think about AI, you think about the chatbot or things of that nature. But really, there's a lot of things going on in the background that it can help with a lot of these corporations. Can you give me an example of how a corporation can leverage AI that isn't so front-facing? Yeah, I think you hit on a really important point there. You know, when people think of AI, they often think of things like chatbots or copilots, those front-facing experiences. But a lot of the power of AI can really be applied to the back-office functions and things that are not necessarily client-facing. So for example, in financial services, the ability to go through and really understand anti-money laundering and how to detect things in a very large corpus of data, that's a perfect use case for AI and generative AI. The ability to go through and extract information from documents to help with things like insurance claims or to help with things like processing loans, all of those are behind-the-scenes types of functions that AI can really augment and help make more efficient and help make more powerful. Yeah, and I think that's super important, you know, like you said, just because we think of chatbots, you know, it's not the only thing going on. And especially when you're thinking about data privacy and things of that nature, you know, it's not something you want out there. Can you tell me about the importance of keeping that data private and IBM Watson's role in that? Absolutely, that's a critical point. You know, when you're talking about enterprise data, you're not talking about publicly available data. You're talking about things that are proprietary to a business, things that are confidential, things that are sensitive, things that are regulated. And the ability to make sure that the data stays secure and private is foundational to enterprises being able to embrace this technology and really put it to work. So what IBM does with our Watson X platform is we provide a full technology stack that allows you to take your data and train and tune models with that data within the confines of your enterprise. So what that means is the data doesn't get exposed to the internet. It doesn't get exposed to the public internet. It doesn't become part of the training set for publicly available models. It stays your data, it stays private, and it stays secure. And that's one of the foundational capabilities of Watson X that makes it so compelling for enterprise clients. And how is IBM making AI more accessible and easier to use for everyone? Well, we're really focused on providing capabilities that allow people to bring AI into their business without having to be a data scientist, right? So the ability to take these large models and tune them with your proprietary data to allow you to guide them and constrain them with guardrails and things of that nature, we're providing that capability within the Watson X platform. So you don't have to be an expert in machine learning to be able to take advantage of it. We're trying to empower the business users to really apply the technology to their specific use cases. And how does IBM envision the future of AI and its impact on industries and daily life? Well, we believe that AI is going to fundamentally transform all aspects of business and society. And what we're focused on is really bringing what we call responsible AI to the enterprise. So the ability to apply AI in a way that's transparent, that's explainable, that's fair, that's not biased. Those foundational elements are critical to the success and the adoption of AI at scale. And that's really what we're focused on is helping enterprises understand how to deploy and manage AI at scale, but do it in a responsible way. Because that's what's going to allow people to have trust in the technology and really apply it to the most critical business processes. And what's next for IBM Watson? What can we see moving forward? We're continuing to build out our portfolio of foundational models on the Watson X platform. So we're building out more models to allow people to come in and take advantage of all these generative AI capabilities, but tailored for the enterprise. We're also focused on how we can continue to bring the capabilities and make them even more consumable and easier to use for enterprises. So that means more tooling, that means more capabilities to allow them to take advantage of these foundational models and put them to work within their specific business. So you can look for us to be continuing to deliver more models, more tooling, more capabilities within the Watson X portfolio. And for somebody that's looking to learn more, where can they go to learn more about IBM Watson? You can go to ibm.com/watsonx. That's where you can learn everything about our new platform and what we're doing in generative AI. Thank you, Dave. Thank you so much for your time. Thanks for being here. Thank you.