Practical AI
Daniel Whitenack and Chris Benson
300 episodes
Making artificial intelligence practical, productive & accessible to everyone. Practical AI is a show in which technology professionals, business people, students, enthusiasts, and expert guests engage in lively discussions about Artificial Intelligence and related topics (Machine Learning, Deep Learning, Neural Networks, GANs, MLOps, AIOps, LLMs & more).
More about the show
The focus is on productive implementations and real-world scenarios that are accessible to everyone. If you want to keep up with the latest advances in AI, while keeping one foot in the real world, then this is the show for you!
Episodes page 2 of 6
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Cracking the code of failed AI pilots
In this Fully Connected episode, we dig into the recent MIT report revealing that 95% of AI pilots fail before reaching production and explore what it actually takes to succeed with AI solutions. We dive into the…
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GenAI risks and global adoption
Daniel and Chris sit with Citadel AI’s Rick Kobayashi and Kenny Song and unpack AI safety and security challenges in the generative AI era. They compare Japan’s approach to AI adoption with the US’s, and explore the…
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Inside America’s AI Action Plan
Dan and Chris break down Winning the Race: America's AI Action Plan, issued by the White House in July 2025. Structured as three "pillars" — Accelerate AI Innovation, Build American AI Infrastructure, and Lead in…
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Confident, strategic AI leadership
Allegra Guinan of Lumiera helps leaders turn uncertainty about AI into confident, strategic leadership. In this conversation, she brings some actionable insights for navigating the hype and complexity of AI. The…
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Educating a data-literate generation
Dan sits down with guests Mark Daniel Ward and Katie Sanders from The Data Mine at Purdue University to explore how higher education is evolving to meet the demands of the AI-driven workforce. They share how their…
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Workforce dynamics in an AI-assisted world
We unpack how AI is reshaping hiring decisions, shifting job roles, and creating new expectations for professionals — from engineers to marketers. They explore the rise of AI-assisted teams, the growing compensation…
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Reimagining actuarial science with AI
In this episode, Chris sits down with Igor Nikitin, CEO and co-founder of Nice Technologies, to explore how AI and modern engineering practices are transforming the actuarial field and setting the stage for the future…
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Agentic AI for Drone & Robotic Swarming
In this episode of Practical AI, Chris and Daniel explore the fascinating world of agentic AI for drone and robotic swarms, which is Chris's passion and professional focus. They unpack how autonomous vehicles (UxV),…
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AI in the shadows: From hallucinations to blackmail
In the first episode of an "AI in the shadows" theme, Chris and Daniel explore the increasing concerning world of agentic misalignment. Starting out with a reminder about hallucinations and reasoning models, they break…
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Finding Nemotron
In this episode, we sit down with Joey Conway to explore NVIDIA's open source AI, from the reasoning-focused Nemotron models built on top of Llama, to the blazing-fast Parakeet speech model. We chat about what makes…
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AI hot takes and debates: Autonomy
Can AI-driven autonomy reduce harm, or does it risk dehumanizing decision-making? In this “AI Hot Takes & Debates” series episode, Daniel and Chris dive deep into the ethical crossroads of AI, autonomy, and military…
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Behind-the-Scenes: VC Funding for AI Startups
It seems like we are bombarded by news about millions of dollars pouring into AI startups, which have crazy valuations. In this episode, Chris and Dan dive deep into the highs, lows, and hard choices behind funding an…
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AI-Automated Film Making
An recent article in Variety was titled: "Sylvester Stallone-Backed Largo.ai Teams With Brilliant Pictures for ‘World’s First Fully AI-Automated Film Company’". Obviously this caught our attention! We sit down with…
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Federated learning in production (part 2)
Chong Shen from Flower Labs joins us to discuss what it really takes to build production-ready federated learning systems that work across data silos. We talk about the Flower framework and it's architecture…
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Federated learning in production (part 1)
In this first of a two part series of episodes on federated learning, we dive into the evolving world of federated learning and distributed AI frameworks with Patrick Foley from Intel. We explore how frameworks like…
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Emailing like a superhuman
Loïc Houssier, Head of Engineering at Superhuman, joins us to discuss how AI and LLMs are reshaping the email experience. He highlights challenges related to the variability of user prompts and infrastructure…
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Model Context Protocol Deep Dive
In this episode, Daniel and Chris unpack the Model Context Protocol (MCP), a rising standard for enabling agentic AI interactions with external systems, APIs, and data sources. They explore how MCP supports…
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Seeing beyond the scan in neuroimaging
In this episode, we explore the intersection of AI, machine learning, and healthcare through the lens of neuroimaging and epilepsy diagnosis. Dr. Gavin Winston shares insights from his work using MRI data and machine…
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Open source AI to tackle your backlog
Vibe coding, agentic workflows, and AI-assisted pull requests? In this episode, Daniel and Chris chat with Robert Brennan and Graham Neubig of All Hands AI about how AI is transforming software development—from senior…
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Orchestrating agents, APIs, and MCP servers
In this episode, Daniel sits down with Pavel Veller, EPAM’s Chief Technologist, to explore the practical challenges of orchestrating many AI agents and managing connections to disparate systems/tools. Pavel shares…
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Software and hardware acceleration with Groq
How do you enable AI acceleration (at both the hardware and software layers) that stays ahead of rapid industry shifts? In this episode, Dhananjay Singh from Groq dives into the evolving landscape of AI inference and…
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AI-assisted coding with GitHub's COO
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 licensing concerns,…
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Optimizing for efficiency with IBM’s Granite
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, efficient components…
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Build a workspace of AI agents
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.ai. We discuss AI…
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GenAI hot takes and bad use cases
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 surprise you!…
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Tool calling and agents
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 can “talk to” and…
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Deep-dive into DeepSeek
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, ties to China have…
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Video generation with realistic motion
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. This leaves some…
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Mozart to Megadeth at CHRP
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 actionable…
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Sidekick is an AI Shopify expert
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 talk about how…
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Full-duplex, real-time dialogue with Kyutai
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-speech…
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Clones, commerce & campaigns
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 discuss the latest…
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scikit-learn & data science you own
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 deployed across…
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Creating tested, reliable AI applications
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 Daniel talk through…
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AI is changing the cybersecurity threat landscape
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 address how AI is…
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The path towards trustworthy AI
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 explore NIST’s ‘AI…
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Big data is dead, analytics is alive
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 world by storm. We…
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Practical workflow orchestration
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 failure modes.…
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Towards high-quality (maybe synthetic) datasets
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 Berenstein & Ben…
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Understanding what's possible, doable & scalable
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 GenAI apps to the…
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GraphRAG (beyond the hype)
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, joins us to dig into…
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Pausing to think about scikit-learn & OpenAI o1
Recently the company stewarding the open source library scikit-learn announced their seed funding. Also, OpenAI released “o1” with new behavior in which it pauses to “think” about complex tasks. Chris and Daniel take…
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Cybersecurity in the GenAI age
Dinis Cruz drops by to chat about cybersecurity for generative AI and large language models. In addition to discussing The Cyber Boardroom, Dinis also delves into cybersecurity efforts at OWASP and that organization’s…
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AI is more than GenAI
GenAI is often what people think of when someone mentions AI. However, AI is much more. In this episode, Daniel breaks down a history of developments in data science, machine learning, AI, and GenAI in this episode to…
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Metrics Driven Development
How do you systematically measure, optimize, and improve the performance of LLM applications (like those powered by RAG or tool use)? Ragas is an open source effort that has been trying to answer this question…
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Threat modeling LLM apps
If you have questions at the intersection of Cybersecurity and AI, you need to know Donato at WithSecure! Donato has been threat modeling AI applications and seriously applying those models in his day-to-day work. He…
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Only as good as the data
You might have heard that “AI is only as good as the data.” What does that mean and what data are we talking about? Chris and Daniel dig into that topic in the episode exploring the categories of data that you might…
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Gaudi processors & Intel's AI portfolio
There is an increasing desire for and effort towards GPU alternatives for AI workloads and an ability to run GenAI models on CPUs. Ben and Greg from Intel join us in this episode to help us understand Intel’s strategy…
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Broccoli AI at its best 🥦
We discussed “🥦 Broccoli AI” a couple weeks ago, which is the kind of AI that is actually good/healthy for a real world business. Bengsoon Chuah, a data scientist working in the energy sector, joins us to discuss…
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Hyperventilating over the Gartner AI Hype Cycle
This week Daniel & Chris hang with repeat guest and good friend Demetrios Brinkmann of the MLOps Community. Together they review, debate, and poke fun at the 2024 Gartner Hype Cycle chart for Artificial Intelligence.…
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