Practical AI

David Yakobovitch joins the show to talk about the evolution of data science tools and techniques, the work he’s doing to teach these things at Galvanize, what his HumAIn Podcast is all about, and more.

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Redis is a an open source, in-memory data structure store, widely used as a database, cache and message broker. It now also support tensor data types and deep learning models via the RedisAI module. Why did they build this module? Who is or should be using it? We discuss this and...

Chris and Daniel take the opportunity to catch up on some recent AI news. Among other things, they discuss the increasing impact of AI on studies of the ancient world and “good” uses of GANs. They also provide some more learning resources to help you level up your AI and machine ...

We’re talking with Joel Grus, author of Data Science from Scratch, 2nd Edition, senior research engineer at the Allen Institute for AI (AI2), and maintainer of AllenNLP. We discussed Joel’s book, which has become a personal favorite of the hosts, and why he decided to approach da...

Woo hoo! As we celebrate reaching episode 50, we come full circle to discuss the basics of neural networks. If you are just jumping into AI, then this is a great primer discussion with which to take that leap.
Our commitment to making artificial intelligence practical, productive...

This week we bend reality to expose the deceptions of deepfake videos. We talk about what they are, why they are so dangerous, and what you can do to detect and resist their insidious influence. In a political environment rife with distrust, disinformation, and conspiracy theorie...

Interpreting complicated models is a hot topic. How can we trust and manage AI models that we can’t explain? In this episode, Janis Klaise, a data scientist with Seldon, joins us to talk about model interpretation and Seldon’s new open source project called Alibi. Janis also give...

Daniel and Chris explore three potentially confusing topics - generative adversarial networks (GANs), deep reinforcement learning (DRL), and transfer learning. Are these types of neural network architectures? Are they something different? How are they used? Well, If you have ever...

Andreas Madsen, a freelance ML/AI engineer and Distill.pub author, joins us to discuss his work visualizing neural networks and recurrent neural units. Andreas discusses various neural unites, RNNs in general, and the “why” of neural network visualization. He also gives us his pe...

Chris and Daniel take you on a tour of local and global AI events, and discuss how to get the most out of your experiences. From access to experts to developing new industry relationships, learn how to get your foot in the door and make connections that help you grow as an AI pra...

At the recent O’Reilly AI Conference in New York City, Chris met up with O’Reilly Chief Data Scientist Ben Lorica, the Program Chair for Strata Data, the AI Conference, and TensorFlow World.
O’Reilly’s ‘AI Adoption in the Enterprise’ report had just been released, so naturally Be...

Can AI help quantum physicists? Can quantum physicists help the AI community? The answers are yes and yes! Dr. Shohini Ghose from Wilfrid Laurier University and Marcus Edwards from the University of Waterloo join us to discuss ML/AI’s impact on physics and quantum computing poten...