『Homegrown Intelligence: AI Features for On-Prem MySQL Enterprise』のカバーアート

Homegrown Intelligence: AI Features for On-Prem MySQL Enterprise

Homegrown Intelligence: AI Features for On-Prem MySQL Enterprise

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 leFred and Scott sit down with Gaurav Chadha to explore MySQL AI, a new solution that brings advanced AI features available in HeatWave to organizations running MySQL Enterprise Edition on-premises. Discover how MySQL AI bridges the gap between cloud innovation and on-premise infrastructure, making transformative AI capabilities more accessible, secure, and efficient for teams that rely on MySQL Enterprise Edition wherever their databases reside. -------------------------------------------------------------- Episode Transcript: 00:00.000 --> 00:25.000 Welcome to Inside MySQL: Sakila Speaks, a podcast dedicated to all things MySQL. We bring you the latest news from the MySQL team, MySQL product updates and insightful interviews with members of the MySQL community. 00:25.000 --> 00:32.000 Sit back and enjoy as your hosts bring you the latest updates on your favorite open source database. Let's get started. 00:32.000 --> 00:37.000 Welcome back to another episode of Inside MySQL: Sakila Speaks. Hi, I'm LeFred. 00:37.000 --> 00:38.000 And I'm Scott Stroz. 00:38.000 --> 00:41.000 Today, we are thrilled to have Guarav Chadha joining us. 00:41.000 --> 00:51.000 Guarav is a Senior Development Manager leading development of MySQL HeatWave Lakehouse with a keen interest in systems, machine learning and computer architecture. 00:51.000 --> 01:10.000 Guarav brings a multifaceted expertise to database technology. Following the completion of his PhD from the University of Michigan, Ann Arbor, Guarav started at Oracle Labs in 2016, working on a research project which eventually graduated into MySQL HeatWave. 01:10.000 --> 01:16.000 But today we will talk with him about MySQL and AI on premise. Welcome Guarav. 01:16.000 --> 01:17.000 Thanks, Fred. Hi, Scott. 01:17.000 --> 01:18.000 Hi, Guarav. How are you? 01:18.000 --> 01:19.000 Doing good. 01:19.000 --> 01:32.000 So we're going to dive right in. And AI, we see AI is taking over the world. It's being touted for the solution to everything. 01:32.000 --> 01:41.000 How do you see AI transforming traditional on-premise database environments, especially in enterprise setups? 01:41.000 --> 01:54.000 Yes, Scott. So, I completely agree. AI is a transformational technology, and it has the potential to improve everything that we see around us. 01:54.000 --> 02:07.000 So, with regards to traditional on-premise database environments, especially in enterprise setups, I see multiple categories here. So, AI is a technology and a toolset. 02:07.000 --> 02:32.000 And like many other operators in databases, it can help with more and different data analysis. So, think of AI as a new set of SQL operators, which can tease out or analyze data and derive insights that are hard to do it with other operators, with other analysis tools. 02:32.000 --> 02:45.000 And hard for folks to call up. And hard for folks to code up. And that's where I think AI enhances it very easily enters into the database environments. 02:45.000 --> 02:56.000 What I mean by that is examples are recommendation systems, anomaly detection, so on and so forth. 02:56.000 --> 03:02.000 The other category is what I would say user assistance. 03:02.000 --> 03:15.000 So, not everyone is a SQL expert. And we want database technology and databases to be accessible to more people who may or may not come from a traditional database background. 03:15.000 --> 03:22.000 And SQL is a very powerful language and where it can be daunting to start with. 03:22.000 --> 03:35.000 So, again, this is a general category where maybe folks who are not very familiar with a specific programming language like SQL could write things out in just plain natural text. 03:35.000 --> 03:42.000 And AI tools could translate this into a programmatic interface or programmatic language or SQL directly. 03:42.000 --> 03:50.000 And that's another facet where I think AI can make database systems more approachable to a larger category of folks. 03:50.000 --> 03:57.000 It can also give you more user friendly responses, like instead of saying, oh, here's the error code, something went wrong. 03:57.000 --> 04:00.000 It can give you more information, more user friendly responses. 04:00.000 --> 04:06.000 So those are some examples of where I would say the second category, user assistance. 04:06.000 --> 04:12.000 The third category of where AI could help is database management. 04:12.000 --> 04:21.000 So databases are systems of record, the sources of truth and have a very high bar of staying up and being available. 04:21.000 --> 04:30.000 AI can help schedule maintenance at the right time where maybe the workload is low. 04:30.000 --> 04:35.000 They can predict things that might get slow. 04:35.000 --> 04:43.000 We have a whole area called predictive maintenance and make databases more highly available, more easily approachable. 04:43.000 --> 04:44.000 Thank you. 04:44.000 --> 04:46.000 This sounds very interesting. 04:46.000 --> 04:50.000 And because we are talking ...
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