The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Sam Charrington
Machine learning and artificial intelligence are dramatically changing the way businesses operate and people live. The TWIML AI Podcast brings the top minds and ideas from the world of ML and AI to a broad and influential community of ML/AI researchers, data scientists, engineers and tech-savvy business and IT leaders. Hosted by Sam Charrington, a sought after industry analyst, speaker, commentator and thought leader. Technologies covered include machine learning, artificial intelligence, deep learning, natural language processing, neural networks, analytics, computer science, data science and more.
Episodes
Mentioned books
Aug 6, 2018 • 46min
Learning Semantically Meaningful and Actionable Representations with Ashutosh Saxena - TWiML Talk #170
In this episode i'm joined by Ashutosh Saxena, a veteran of Andrew Ng’s Stanford Machine Learning Group, and co-founder and CEO of Caspar.ai. Ashutosh and I discuss his RoboBrain project, a computational system that creates semantically meaningful and actionable representations of the objects, actions and observations that a robot experiences in its environment, and allows these to be shared and queried by other robots to learn new actions.
For complete show notes, visit https://twimlai.com/talk/170.
Aug 2, 2018 • 42min
AI Innovation for Clinical Decision Support with Joe Connor - TWiML Talk #169
In this episode I speak with Joe Connor, Founder of Experto Crede.
In our conversation, we explore his experiences bringing AI powered healthcare projects to market in collaboration with the UK National Health Service and its clinicians, some of the various challenges he’s run into when applying ML and AI in healthcare, as well as some of his successes. We also discuss data protections, especially GDPR, potential ways to include clinicians in the building of applications.
Jul 30, 2018 • 45min
Dynamic Visual Localization and Segmentation with Laura Leal-Taixé -TWiML Talk #168
In this episode I'm joined by Laura Leal-Taixé, Professor at the Technical University of Munich where she leads the Dynamic Vision and Learning Group.
In our conversation, we discuss several of her recent projects including work on image-based localization techniques that fuse traditional model-based computer vision approaches with a data-driven approach based on deep learning, her paper on one-shot video object segmentation and the broader vision for her research.
Jul 26, 2018 • 37min
Conversational AI for the Intelligent Workplace with Gillian McCann - TWiML Talk #167
In this episode I'm joined by Gillian McCann, Head of Cloud Engineering and AI at Workgrid Software. In our conversation, which focuses on Workgrid’s use of cloud-based AI services, Gillian details some of the underlying systems that make Workgrid tick, their engineering pipeline & how they build high quality systems that incorporate external APIs and her view on factors that contribute to misunderstandings and impatience on the part of users of AI-based products.
Jul 22, 2018 • 48min
Computer Vision and Intelligent Agents for Wildlife Conservation with Jason Holmberg - TWiML Talk #166
In this episode, I'm joined by Jason Holmberg, Executive Director and Director of Engineering at WildMe. Jason and I discuss Wildme's pair of open source computer vision based conservation projects, Wildbook and Whaleshark.org, Jason kicks us off with the interesting story of how Wildbook came to be, the eventual expansion of the project and the evolution of these projects’ use of computer vision and deep learning.
For the complete show notes, visit twimlai.com/talk/166
Jul 19, 2018 • 37min
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 Qure.ai. We discuss the company’s work building products for interpreting head CT scans and chest x-rays. We look at knowledge gained in bringing a commercial product to market, including what the gap between academic research papers and commercially viable software, the challenge of data acquisition and more. We also touch on the application of transfer learning.
For the complete show notes, visit https://twimlai.com/talk/165.
Jul 16, 2018 • 48min
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, who joins us fresh off of winning the 2018 CVPR Best Paper Award for co-authoring "Taskonomy: Disentangling Task Transfer Learning." In our conversation, we discuss the nature and consequences of the relationships that Amir and his team discovered, and how they can be used to build more effective visual systems with machine learning.
https://twimlai.com/talk/164
Jul 11, 2018 • 40min
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 to discuss his recent paper, “A machine learning approach to predict metabolic pathway dynamics from time-series multiomics data.” Zak gives us an overview of synthetic biology and the use of ML techniques to optimize metabolic reactions for engineering biofuels at scale.
Visit twimlai.com/talk/163 for the complete show notes.
Jul 9, 2018 • 43min
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 to discuss his research into the use of machine learning to help discover the fundamental governing equations for physical and engineering systems from time series measurements.
For complete show notes visit twimlai.com/talk/162
Jul 5, 2018 • 40min
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, the Experteer NLP pipeline and how it’s evolved, Alex’s work with deep learning based ML models, including models like VDCNN and Facebook’s FastText offering and a few recent papers that look at transfer learning for NLP.
Check out the complete show notes at twimlai.com/talk/161
