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Pragmatic Deep Learning for Medical Imagery with Prashant Warier - TWiML Talk #165

In this episode I'm joined by Prashant Warier, CEO and Co-Founder of, a company building AI-powered software for radiology. In our conversation, Prashant and I discuss the company’s work building products for interpreting head CT scans and chest x-rays. Prashant shares with us some great insights into some of the things he and his team have learned in bringing a commercial product to market in this space, including what the gap between academic research papers and commercially...


Taskonomy: Disentangling Transfer Learning for Perception (CVPR 2018 Best Paper Winner) with Amir Zamir - TWiML Talk #164

In this episode I'm joined by Amir Zamir, Postdoctoral researcher at both Stanford & UC Berkeley. Amir joins us fresh off of winning the 2018 CVPR Best Paper Award for co-authoring "Taskonomy: Disentangling Task Transfer Learning." In this work, Amir and his coauthors explore the relationships between different types of visual tasks and use this structure to better understand the types of transfer learning that will be most effective for each, resulting in what they call a “computational...


Predicting Metabolic Pathway Dynamics w/ Machine Learning with Zak Costello - TWiML Talk #163

In today’s episode I’m joined by Zak Costello, post-doctoral fellow at the Joint BioEnergy Institute. Zak joins me to discuss his recent paper, “A machine learning approach to predict metabolic pathway dynamics from time-series multiomics data.” In our conversation, we start with an overview of synthetic biology, and from there dig into Zak’s particular application, which is the use of ML techniques to optimize metabolic reactions for engineering biofuels at scale. We get into an...


Machine Learning to Discover Physics and Engineering Principles with Nathan Kutz - TWiML Talk #162

In this episode, I’m joined by Nathan Kutz, Professor of applied mathematics, electrical engineering and physics at the University of Washington. Nathan and I met a few months ago at the Prepare.AI conference in St. Louis where he gave a talk on “Machine Learning to Discover Physics and Engineering Principles.” Our conversation is laser-focused on his research into the use of machine learning to help discover the fundamental governing equations for physical and engineering systems from...


Automating Complex Internal Processes w/ AI with Alexander Chukovski - TWiML Talk #161

In this episode i'm joined by Alexander Chukovski, Director of Data Services at Munich, Germany based career platform, Experteer. In our conversation, we explore Alex’s journey to implement machine learning at Experteer. Alex and I discuss the Experteer NLP pipeline and how it’s evolved over time to address the company’s need for greater automation in the way it processes jobs on its platform. We also discuss Alex’s work with deep learning based ML models, including models like VDCNN and...


Designing Better Sequence Models with RNNs with Adji Bousso Dieng - TWiML Talk 160

In this episode, i'm joined by Adji Bousso Dieng, PhD Student in the Department of Statistics at Columbia University. In this interview, Adji and I discuss two of her recent papers, the first, an accepted paper from this year’s ICML conference titled “Noisin: Unbiased Regularization for Recurrent Neural Networks,” which, as the name implies, presents a new way to regularize RNNs using noise injection. The second paper, an ICLR submission from last year titled “TopicRNN: A Recurrent Neural...


Love Love: AI and ML in Tennis with Stephanie Kovalchik - TWiML Talk #159

In this, the final show in our AI in Sports series, I’m joined by Stephanie Kovalchik, Research Fellow at Victoria University and Senior Sports Scientist at Tennis Australia. Stephanie and I had a great conversation about a few of the many interesting projects underway at Tennis Australia. We look at their use of data to develop a player rating system based on ability and probability, as opposed to the current official one which is based on points scored and match results. We then get...


Growth Hacking Sports w/ Machine Learning with Noah Gift - TWiML Talk #158

In this episode of our AI in Sports series I'm joined by Noah Gift, Founder and Consulting CTO at Pragmatic Labs and professor at UC Davis. Noah previously worked for a startup called Score Sports, which used machine learning to uncover athlete influence on social media and internet platforms. We look into some of his findings in that role, including how to predict the impact of athletes’ social media engagement. We also discuss some of his more recent work in using social media to...


Fine-Grained Player Prediction in Sports with Jennifer Hobbs - TWiML Talk #157

In this episode of the series, I'm joined by Jennifer Hobbs, Senior Data Scientist at STATS, a collector and distributor of sports data, covering sports like basketball, soccer, American football and rugby. Jennifer and I explore the STATS data pipeline and how they collect and store different types of data for easy consumption and application. We dig into a paper she co-authored, Mythbusting Set-Pieces in Soccer, which takes a look at the data surrounding free kicks and corner kicks in...


Targeted Ticket Sales Using Azure ML with the Trail Blazers w/ Mike Schumacher & Chenhui Hu - TWiML Talk #156

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. In our conversation, Mike, Chenhui and I discuss how the Blazers are using machine learning to produce better-targeted sales campaigns, for both single-game and season-ticket buyers. Mike describes some of the early use cases the Trail Blazers explored in their drive to apply analytics to the process of...


AI for Athlete Optimization with Sinead Flahive - TWiML Talk #155

Perhaps especially appropriate given that much of the globe is glued to the World Cup at the moment, this week we’re excited to kick off a series of shows on AI in sports. While I'm not personally the biggest sports fan, my producer Imari is a huge sports follower, and this series has been something he’s wanted to see since we started working together. So, if you like these shows, be sure to hit him up on Twitter at @twiml_imari. In this episode I'm joined by Sinead Flahive, data...


Omni-Channel Customer Experiences with Vince Jeffs - TWiML Talk #154

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...


Workforce Intelligence for Automation & Productivity with Michael Kempe - TWiML Talk #153

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,...


Data Platforms for Decision Automation at Scotiabank with Jim Saleh - TWiML Talk #152

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...


Towards the Self-Driving Enterprise with Kirk Borne - TWiML Talk #151

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,...


How a Global Energy Company Adopts ML & AI with Nicholas Osborn - TWiML Talk #150

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...


Problem Formulation for Machine Learning with Romer Rosales - TWiML Talk #149

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...


AI for Materials Discovery with Greg Mulholland

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...


Data Innovation & AI at Capital One with Adam Wenchel - #TWiML Talk 147

In this episode I’m joined by Adam Wenchel, vice president of AI and Data Innovation at Capital One, to discuss how Machine Learning & AI are being integrated into their day-to-day practices, and how those advances benefit the customer. In our conversation, we look into a few of the many applications of AI at the bank, including fraud detection, money laundering, customer service, and automating back office processes. Adam describes some of the challenges of applying ML in financial...


Deep Gradient Compression for Distributed Training with Song Han - TWiML Talk #146

On today’s show I chat with Song Han, assistant professor in MIT’s EECS department, about his research on Deep Gradient Compression. In our conversation, we explore the challenge of distributed training for deep neural networks and the idea of compressing the gradient exchange to allow it to be done more efficiently. Song details the evolution of distributed training systems based on this idea, and provides a few examples of centralized and decentralized distributed training architectures...