The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

In this episode of our AI in Sports series, I'm joined by Jennifer Hobbs, Senior Data Scientist at STATS, a collector and distributor of sports data, to discuss the STATS data pipeline and how they collect and store different types of data for easy consumption and application. We also look into a paper she co-authored, Mythbusting Set-Pieces in Soccer, which was presented at the MIT Sloan Conference this year. https://twimlai.com/talk/157

In today’s episode of our AI in Sports series I'm joined by Mike Schumacher, director of business analytics for the Portland Trail Blazers, and Chenhui Hu, a data scientist at Microsoft to discuss how the Blazers are using machine learning to produce better-targeted sales campaigns, for both single-game and season-ticket buyers.

This week we’re excited to kick off a series of shows on AI in sports. In this episode I'm joined by Sinead Flahive, data scientist at Dublin, Ireland based Kitman Labs to discuss Kitman’s Athlete Optimization System, which allows sports trainers and coaches to collect and analyze data for player performance optimization and injury reduction. Enjoy!

In this, the final episode of our PegaWorld series I’m joined by Vince Jeffs, Senior Director of Product Strategy for AI and Decisioning at Pegasystems. Vince and I had a great talk about the role AI and advanced analytics will play in defining future customer experiences. We do this in the context provided by one of his presentations from the conference, which explores four technology scenarios from Pegasystems’ innovation labs. These look at a connected car experience, the use of deep learning for diagnostics, dynamic notifications, and continuously optimized marketing. We also get into an interesting discussion about how much is too much when it comes to hyperpersonalized experiences, and how businesses can manage this challenge. The notes for this show can be found at twimlai.com/talk/154. For more information on the Pegaworld series, visit twimlai.com/pegaworld2018.

In this episode of our PegaWorld series, I’m joined by Michael Kempe, chief operating officer at global share registry and financial services provider Link Market Services. In the interview, Michael and I dig into Link’s use of workforce intelligence software to allow it to track and analyze the performance of its workforce and business processes. Michael and I discuss some of the initial challenges associated with implementing this type of system, including skepticism amongst employees, and how it ultimately sets the stage for the Link’s broader use of machine learning, AI and so called “robotic process automation” to increase workforce productivity. The notes for this show can be found at twimlai.com/talk/153. For more information on our PegaWorld series, visit twimlai.com/pegaworld2018.

In this show, part of our PegaWorld 18 series, I'm joined by Jim Saleh, Senior Director of process and decision automation at Scotiabank. Jim is tasked with helping the bank transition from a world where customer interactions are based on historical analytics to one where they’re based on real-time decisioning and automation. In our conversation we discuss what’s required to deliver real-time decisioning, starting from the ground up with the data platform. In this vein we explore topics like data lakes, data warehouses, integration, and more, and the effort required to take advantage of these. The notes for this show can be found at twimlai.com/talk/152. For more info on our PegaWorld 2018 series, visit twimlai.com/pegaworld2018.

In this show, the first of our PegaWorld 18 series, I'm joined by Kirk Borne, Principal Data Scientist at management consulting firm Booz Allen Hamilton. In our conversation, Kirk shares his views on automation as it applies to enterprises and their customers. We discuss his experiences evangelizing data science within the context of a large organization, and the role of AI in helping organizations achieve automation. Along the way Kirk, shares a great analogy for intelligent automation, comparing it to an autonomous vehicle . We covered a ton of ground in this chat, which I think you’ll get a kick out of. The notes for this show can be found at twimlai.com/talk/151. For more info about our PegaWorld 2018 Series, visit twimlai.com/pegaworld2018.

On today’s show I’m excited to share this interview with Nick Osborn, a longtime listener of the show and Leader of the Global Machine Learning Project Management Office at AES Corporation, a Fortune 200 power company. Nick and I met at my AI Summit a few weeks back, and after a brief chat about some of the things he was up to at AES, I knew I needed to get him on the show! In this interview, Nick and I explore how AES is implementing machine learning across multiple domains at the company. We dig into several examples falling under the Natural Language, Computer Vision, and Cognitive Assets categories he’s established for his projects. Along the way we cover some of the key podcast episodes that helped Nick discover potentially applicable ML techniques, and how those are helping his team broaden the use of machine learning at AES. This was a fun and informative conversation that has a lot to offer. Thanks, Nick! The notes for this episode can be found at twimlai.com/talk/150.

In this episode, i'm joined by Romer Rosales, Director of AI at LinkedIn. We begin with a discussion of graphical models and approximate probability inference, and he helps me make an important connection in the way I think about that topic. We then review some of the applications of machine learning at LinkedIn, and how what Romer calls their ‘holistic approach’ guides the evolution of ML projects at LinkedIn. This leads us into a really interesting discussion about problem formulation and selecting the right objective function for a given problem. We then talk through some of the tools they’ve built to scale their data science efforts, including large-scale constrained optimization solvers, online hyperparameter optimization and more. This was a really fun conversation, that I’m sure you’ll enjoy! The notes for this show can be found at twimlai.com/talk/149.

In this episode I’m joined by Greg Mulholland, Founder and CEO of Citrine Informatics, which is applying AI to the discovery and development of new materials. Greg and I start out with an exploration of some of the challenges of the status quo in materials science, and what’s to be gained by introducing machine learning into this process. We discuss how limitations in materials manifest themselves, and Greg shares a few examples from the company’s work optimizing battery components and solar cells. We dig into the role and sources of data used in applying ML in materials, and some of the unique challenges to collecting it, and discuss the pipeline and algorithms Citrine uses to deliver its service. This was a fun conversation that spans physics, chemistry, and of course machine learning, and I hope you enjoy it. The notes for this show can be found at twimlai.com/talk/148.