Edge AI for Smart Manufacturing with Trista Chen - TWiML Talk #253
Today we’re joined by Trista Chen, chief scientist of machine learning at Inventec, who spoke on “Edge AI in Smart Manufacturing: Defect Detection and Beyond” at GTC. In our conversation, we discuss the challenges that Industry 4.0 initiatives aim to address and dig into a few of the various use cases she’s worked on, such as the deployment of ML in an industrial setting to perform various tasks. We also discuss the challenges associated with estimating the ROI of industrial AI projects.
18 Apr 201938min
Machine Learning for Security and Security for Machine Learning with Nicole Nichols - TWiML Talk #252
Today we’re joined by Nicole Nichols, a senior research scientist at the Pacific Northwest National Lab. We discuss her recent presentation at GTC, which was titled “Machine Learning for Security, and Security for Machine Learning.” We explore two use cases, insider threat detection, and software fuzz testing, discussing the effectiveness of standard and bidirectional RNN language models for detecting malicious activity, the augmentation of software fuzzing techniques using deep learning, and much mor
16 Apr 201941min
Domain Adaptation and Generative Models for Single Cell Genomics with Gerald Quon - TWiML Talk #251
Today we’re joined by Gerald Quon, assistant professor at UC Davis. Gerald presented his work on Deep Domain Adaptation and Generative Models for Single Cell Genomics at GTC this year, which explores single cell genomics as a means of disease identification for treatment. In our conversation, we discuss how he uses deep learning to generate novel insights across diseases, the different types of data that was used, and the development of ‘nested’ Generative Models for single cell measurement.
15 Apr 201932min
Mapping Dark Matter with Bayesian Neural Networks w/ Yashar Hezaveh - TWiML Talk #250
Today we’re joined by Yashar Hezaveh, Assistant Professor at the University of Montreal. Yashar and I caught up to discuss his work on gravitational lensing, which is the bending of light from distant sources due to the effects of gravity. In our conversation, Yashar and I discuss how ML can be applied to undistort images, the intertwined roles of simulation and ML in generating images, incorporating other techniques such as domain transfer or GANs, and how he assesses the results of this project.
11 Apr 201934min
Deep Learning for Population Genetic Inference with Dan Schrider - TWiML Talk #249
Today we’re joined by Dan Schrider, assistant professor in the department of genetics at UNC Chapel Hill. My discussion with Dan starts with an overview of population genomics, looking into his application of ML in the field. We then dig into Dan’s paper “The Unreasonable Effectiveness of Convolutional Neural Networks in Population Genetic Inference,” which examines the idea that CNNs are capable of outperforming expert-derived statistical methods for some key problems in the field.
9 Apr 201949min
Empathy in AI with Rob Walker - TWiML Talk #248
Today we’re joined by Rob Walker, Vice President of Decision Management at Pegasystems. Rob joined us back in episode 127 to discuss “Hyperpersonalizing the customer experience.” Today, he’s back for a discussion about the role of empathy in AI systems. In our conversation, we dig into the role empathy plays in consumer-facing human-AI interactions, the differences between empathy and ethics, and a few examples of ways empathy should be considered when enterprise AI systems.
5 Apr 201940min
Benchmarking Custom Computer Vision Services at Urban Outfitters with Tom Szumowski - TWiML Talk #247
Today we’re joined by Tom Szumowski, Data Scientist at URBN, parent company of Urban Outfitters and other consumer fashion brands. Tom and I caught up to discuss his project “Exploring Custom Vision Services for Automated Fashion Product Attribution.” We look at the process Tom and his team took to build custom attribution models, and the results of their evaluation of various custom vision APIs for this purpose, with a focus on the various roadblocks and lessons he and his team encountered along the
3 Apr 201950min
Pragmatic Quantum Machine Learning with Peter Wittek - TWiML Talk #245
Today we’re joined by Peter Wittek, Assistant Professor at the University of Toronto working on quantum-enhanced machine learning and the application of high-performance learning algorithms. In our conversation, we discuss the current state of quantum computing, a look ahead to what the next 20 years of quantum computing might hold, and how current quantum computers are flawed. We then dive into our discussion on quantum machine learning, and Peter’s new course on the topic, which debuted in Februar
1 Apr 20191h 5min
