Discover this podcast and so much more

Podcasts are free to enjoy without a subscription. We also offer ebooks, audiobooks, and so much more for just $11.99/month.

When And How To Conduct An AI Program

When And How To Conduct An AI Program

FromData Engineering Podcast


When And How To Conduct An AI Program

FromData Engineering Podcast

ratings:
Length:
46 minutes
Released:
Mar 3, 2024
Format:
Podcast episode

Description

Summary
Artificial intelligence technologies promise to revolutionize business and produce new sources of value. In order to make those promises a reality there is a substantial amount of strategy and investment required. Colleen Tartow has worked across all stages of the data lifecycle, and in this episode she shares her hard-earned wisdom about how to conduct an AI program for your organization.
Announcements
Hello and welcome to the Data Engineering Podcast, the show about modern data management
Dagster offers a new approach to building and running data platforms and data pipelines. It is an open-source, cloud-native orchestrator for the whole development lifecycle, with integrated lineage and observability, a declarative programming model, and best-in-class testability. Your team can get up and running in minutes thanks to Dagster Cloud, an enterprise-class hosted solution that offers serverless and hybrid deployments, enhanced security, and on-demand ephemeral test deployments. Go to dataengineeringpodcast.com/dagster (https://www.dataengineeringpodcast.com/dagster) today to get started. Your first 30 days are free!
Data lakes are notoriously complex. For data engineers who battle to build and scale high quality data workflows on the data lake, Starburst powers petabyte-scale SQL analytics fast, at a fraction of the cost of traditional methods, so that you can meet all your data needs ranging from AI to data applications to complete analytics. Trusted by teams of all sizes, including Comcast and Doordash, Starburst is a data lake analytics platform that delivers the adaptability and flexibility a lakehouse ecosystem promises. And Starburst does all of this on an open architecture with first-class support for Apache Iceberg, Delta Lake and Hudi, so you always maintain ownership of your data. Want to see Starburst in action? Go to dataengineeringpodcast.com/starburst (https://www.dataengineeringpodcast.com/starburst) and get $500 in credits to try Starburst Galaxy today, the easiest and fastest way to get started using Trino.
Join us at the top event for the global data community, Data Council Austin. From March 26-28th 2024, we'll play host to hundreds of attendees, 100 top speakers and dozens of startups that are advancing data science, engineering and AI. Data Council attendees are amazing founders, data scientists, lead engineers, CTOs, heads of data, investors and community organizers who are all working together to build the future of data and sharing their insights and learnings through deeply technical talks. As a listener to the Data Engineering Podcast you can get a special discount off regular priced and late bird tickets by using the promo code dataengpod20. Don't miss out on our only event this year! Visit dataengineeringpodcast.com/data-council (https://www.dataengineeringpodcast.com/data-council) and use code dataengpod20 to register today!
Your host is Tobias Macey and today I'm interviewing Colleen Tartow about the questions to answer before and during the development of an AI program
Interview
Introduction
How did you get involved in the area of data management?
When you say "AI Program", what are the organizational, technical, and strategic elements that it encompasses?
How does the idea of an "AI Program" differ from an "AI Product"?
What are some of the signals to watch for that indicate an objective for which AI is not a reasonable solution?
Who needs to be involved in the process of defining and developing that program?
What are the skills and systems that need to be in place to effectively execute on an AI program?
"AI" has grown to be an even more overloaded term than it already was. What are some of the useful clarifying/scoping questions to address when deciding the path to deployment for different definitions of "AI"?
Organizations can easily fall into the trap of green-lighting an AI project before they have done the work of ensuring they have the necessary data and the ability to process it. W
Released:
Mar 3, 2024
Format:
Podcast episode

Titles in the series (100)

Weekly deep dives on data management with the engineers and entrepreneurs who are shaping the industry