Practical AI

Kyle Daigle, COO of GitHub, joins the hosts to discuss the evolving role of AI in software development, GitHub Copilot’s impact, and the challenges of AI-assisted coding. The conversation covers lice…

We often judge AI models by leaderboard scores, but what if efficiency matters more? Kate Soule from IBM joins us to discuss how Granite AI is rethinking AI at the edge—breaking tasks into smaller, e…

How can every single person build a personal AI protégé and then accumulate (and share) a host of other assistants? In this episode, we dive into the world of no-code AI with Scott Meyer from Chipp.a…

It seems like all we hear about are the great use cases for GenAI, but where should you NOT be using the technology? On this episode Chris and Daniel share their hot takes and bad use cases. Some may…

It seems like everyone is uses the term “agent” differently these days. In this episode, Chris and Daniel dig into the details of tool calling and its connection to agents. They help clarify how LLMs…

There is crazy hype and a lot of confusion related to DeepSeek’s latest model DeepSeek R1. The products provided by DeepSeek (their version of a ChatGPT-like app) has exploded in popularity. However,…

We seem to be experiencing a surge of video generation tools, models, and applications. However, video generation models generally struggle with some basic physics, like realistic walking motion. Thi…

Daniel and Chris groove with Jeff Smith, Founder and CEO at CHRP.ai. Jeff describes how CHRP anonymously analyzes emotional wellness data, derived from employees’ music preferences, giving HR leaders…

Today, Chris explores Shopify Magic and other AI offerings with Mike Tamir, Distinguished ML Engineer and Head of Machine Learning, and Matt Colyer, Director of Product Management for Sidekick. They …

Kyutai, an open science research lab, made headlines over the summer when they released their real-time speech-to-speech AI assistant (beating OpenAI to market with their teased GPT-driven speech-to-…

Chris and Daniel dive into what Trump’s impending second term could mean for AI companies, model developers, and regulators, unpacking the potential shifts in policy and innovation. Next, they discus…

We are at GenAI saturation, so let’s talk about scikit-learn, a long time favorite for data scientists building classifiers, time series analyzers, dimensionality reducers, and more! Scikit-learn is …

It can be frustrating to get an AI application working amazingly well 80% of the time and failing miserably the other 20%. How can you close the gap and create something that you rely on? Chris and D…

This week, Chris is joined by Gregory Richardson, Vice President and Global Advisory CISO at BlackBerry, and Ismael Valenzuela, Vice President of Threat Research & Intelligence at BlackBerry. They ad…

Elham Tabassi, the Chief AI Advisor at the U.S. National Institute of Standards & Technology (NIST), joins Chris for an enlightening discussion about the path towards trustworthy AI. Together they ex…

We are on the other side of “big data” hype, but what is the future of analytics and how does AI fit in? Till and Adithya from MotherDuck join us to discuss why DuckDB is taking the analytics and AI …

Workflow orchestration has always been a pain for data scientists, but this is exacerbated in these AI hype days by agentic workflows executing arbitrary (not pre-defined) workflows with a variety of…

As Argilla puts it: “Data quality is what makes or breaks AI.” However, what exactly does this mean and how can AI team probably collaborate with domain experts towards improved data quality? David B…

We are constantly hearing about disillusionment as it relates to AI. Some of that is probably valid, but Mike Lewis, an AI architect from Cincinnati, has proven that he can consistently get LLM and G…

Seems like we are hearing a lot about GraphRAG these days, but there are lots of questions: what is it, is it hype, what is practical? One of our all time favorite podcast friends, Prashanth Rao, joi…