Book Image

Creators of Intelligence

By : Dr. Alex Antic
Book Image

Creators of Intelligence

By: Dr. Alex Antic

Overview of this book

A Gartner prediction in 2018 led to numerous articles stating that "85% of AI and machine learning projects fail to deliver.” Although it's unclear whether a mass extinction event occurred for AI implementations at the end of 2022, the question remains: how can I ensure that my project delivers value and doesn't become a statistic? The demand for data scientists has only grown since 2015, when they were dubbed the new “rock stars” of business. But how can you become a data science rock star? As a new senior data leader, how can you build and manage a productive team? And what is the path to becoming a chief data officer? Creators of Intelligence is a collection of in-depth, one-on-one interviews where Dr. Alex Antic, a recognized data science leader, explores the answers to these questions and more with some of the world's leading data science leaders and CDOs. Interviews with: Cortnie Abercrombie, Edward Santow, Kshira Saagar, Charles Martin, Petar Veličković, Kathleen Maley, Kirk Borne, Nikolaj Van Omme, Jason Tamara Widjaja, Jon Whittle, Althea Davis, Igor Halperin, Christina Stathopoulos, Angshuman Ghosh, Maria Milosavljevic, Dr. Meri Rosich, Dat Tran, and Stephane Doyen.
Table of Contents (23 chapters)
1
Chapter 1: Introducing the Creators of Intelligence

Teaching data science

AA: Speaking of students, one of the reasons you left NASA was to establish the world’s first data science program. What do you think are some of the key elements of a modern program these days? What should we really be teaching students that we’re not teaching them at the moment?

KB: That’s a really good question because I’ve been involved in a number of panels where they’ve discussed this, and some of them have gone on for days, and some of the reports have gone on for dozens of pages. You can get really into the weeds with this one.

The key elements are the higher-level things. There are mathematical foundations. There’s modeling. People underestimate the power of modeling. A model is a representation of a thing. It’s not the thing. We use data as a representation of a customer. The data is not the customer. What you purchase is not you; it’s a representation of the things you like or are interested...