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.
6 Aug 201845min
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.
2 Aug 201842min
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.
30 Juli 201844min
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.
26 Juli 201836min
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
22 Juli 201848min
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.
19 Juli 201836min
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
16 Juli 201847min
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.
11 Juli 201839min
