Practical AI

Evan Sparks, from Determined AI, helps us understand why many are still stuck in the “dark ages” of AI infrastructure. He then discusses how we can build better systems by leveraging things like faul…

SpaCy is awesome for NLP! It’s easy to use, has widespread adoption, is open source, and integrates the latest language models. Ines Montani and Matthew Honnibal (core developers of spaCy and co-foun…

GANs are at the center of AI hype. However, they are also starting to be extremely practical and be used to develop solutions to real problems. Jakub Langr and Vladimir Bok join us for a deep dive in…

Streamlit recently burst onto the scene with their intuitive, open source solution for building custom ML/AI tools. It allows data scientists and ML engineers to rapidly build internal or external UI…

There’s a lot of hype about knowledge graphs and AI-methods for building or using them, but what exactly is a knowledge graph? How is it different from a database or other data store? How can I build…

Everyone is talking about it. OpenAI trained a pair of neural nets that enable a robot hand to solve a Rubik’s cube. That is super dope! The results have also generated a lot of commentary and contro…

What’s the most practical of practical AI things? Data labeling of course! It’s also one of the most time consuming and error prone processes that we deal with in AI development. Michael Malyuk of He…

Times series data is everywhere! I mean, seriously, try to think of some data that isn’t a time series. You have stock prices and weather data, which are the classics, but you also have a time series…

We’ve mentioned ML/AI in the browser and in JS a bunch on this show, but we haven’t done a deep dive on the subject… until now! Victor Dibia helps us understand why people are interested in porting m…

The United States has blacklisted several Chinese AI companies working in facial recognition and surveillance. Why? What are these companies doing exactly, and how does this fit into the internationa…

Chris and Daniel talk with Keith Lynn, AlphaPilot Program Manager at Lockheed Martin. AlphaPilot is an open innovation challenge, developing artificial intelligence for high-speed racing drones, crea…

Chris and Daniel take some time to cover recent trends in AI and some noteworthy publications. In particular, they discuss the increasing AI momentum in the majority world (Africa, Asia, South and Ce…

The All Things Open conference is happening soon, and we snagged one of their speakers to discuss open source and AI. Samuel Taylor talks about the essential role that open source is playing in AI de…

In this very special fully-connected episode of Practical AI, Daniel interviews Chris. They discuss High Performance Computing (HPC) and how it is colliding with the world of AI. Chris explains how H…

We’re talking with Sherol Chen, a machine learning developer, about AI at Google and AutoML methods. Sherol explains how the various AI groups within Google work together and how AutoML fits into tha…

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 mo…

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. …

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 al…

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, whi…

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 tak…