AI for Data: When data Meet Intelligence

AI is driving a remarkable transformation throughout the industry, delivering unprecedented productivity gains and enabling rapid insights from vast amounts of data. In this two-episode season premiere, Tirthankar Lahiri, SVP of Mission-Critical Data and AI Engines, discusses how Oracle AI Vector and embedded machine learning search are harnessing the power of AI to unlock value from enterprise data, and allow developers to build sophisticated RAG and Agentic frameworks that leverage the full power of the converged database architecture of Oracle Database — including its class-leading scalability, fault-tolerance, and enterprise-grade security. Furthermore, Oracle database provides several mechanisms to make data "AI-ready" by enabling declarative data intent for AI. In this session, we will describe these techniques, and more, to explain how to truly build an AI for data solution in this rapidly changing AI landscape! ------------------------------------ Episode Transcript: 00:00:00:00 - 00:00:34:07 Unknown Welcome to the Oracle Academy Tech Chat. This podcast provides educators and students in-depth discussions with thought leaders around computer science, cloud technologies, and software design to help students on their journey to becoming industry ready technology leaders of the future. Let's get started. Welcome to Oracle Academy Tech Chat, where we discuss how Oracle Academy prepares the next generation's workforce. 00:00:34:09 - 00:01:03:23 Unknown I'm your host, Tara Pierce. This is the first of two episodes on AI for data when data meets intelligence. Our guest speaker is to thank Carly Harris, senior vice president for mission critical data and AI engines at Oracle. Here's responsible for the data engine for Oracle database, including areas like AI, vector search, indexing and data compression. He also manages the Oracle Times ten in memory and the Oracle NoSQL database product teams to thank her. 00:01:03:23 - 00:01:33:13 Unknown Has 30 years of experience in the database industry and has worked on a variety of areas such as performance, scalability, manageability, caching, in-memory architectures and developer focused functionality. He has 71 issued and several pending patents. A bachelor's in computer Science from the Indian Institute of Technology and a master's in electrical engineering from Stanford University. In the first episode to thank our talks about how data makes AI intelligent and how enterprises are using AI to get greater value from their data. 00:01:33:15 - 00:01:59:19 Unknown Over to you to thank her. Hi. Hey, guys. Thank you very much for joining. It's a great pleasure to be presenting AI for data. This is an exciting time in technology. AI is ubiquitous. AI changes everything. And I actually makes data intelligent. Let's talk about that today. So you know Oracle is working on AI. As many of you know, at many levels in the enterprise stack. 00:01:59:21 - 00:02:31:22 Unknown We have AI initiatives for applications, AI initiatives for services. I for data. And we're building a lot of AI infrastructure, as you seen from the news. Now I'm going to focus on AI for data. That's the focus of my presentation today. How we bring AI, the power of AI and unleash it on enterprise data. So Oracle's goal is to make AI for data extremely simple for basically everything. 00:02:32:00 - 00:02:54:08 Unknown So no matter what kind of end user you are, whether you're an expert, an AI, or a developer, or a DBA random list, every single persona should be able to leverage AI for data. We want to make it possible for all applications to leverage AI for data and benefit all workloads with the AI for data. So this is the goal that we have for AI for data. 00:02:54:08 - 00:03:25:05 Unknown Now, there's again basically two classic kinds of AI in the classical sense. So let's quickly talk about one before I get to what's new. So the traditional AI, was basically called algorithmic AI. Algorithmic here is based on machine learning models, typically non neural net designed to do predictions classifications, forecasting etc. and for data science people, you know that there's many different machine learning algorithms. 00:03:25:07 - 00:03:44:06 Unknown And these are all now available in Oracle database. So if you want you can use one of these models. This is the ever evolving list. You can use one of these models to load to first of all to train, you know, a sorry, you could use one of these algorithms. Excuse me. I keep that in the trunk. 00:03:44:08 - 00:04:05:22 Unknown These are algorithms. You can use one of these to train models and then to run inferencing using these models. So you imagine you can take, you know, linear linear regression. The algorithm used that to train a model and then applied that to data in real time to basically do predictions. So that's what in database machine learning lets you do. 00:04:06:00 - 00:04:30:18 Unknown And we've had this, capability for a while now. So what ...