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 interoperability, community contributions, and a rapidly developing ecosystem of AI integrations. The conversation also highlights some real-world tooling such as FastAPI-MCP.Featuring:Chris Benson – Website, GitHub, LinkedIn, XDaniel Whitenack – Website, GitHub, XLinks:Protocol websiteAnthropic blog postBlog post - Model Context Protocol (MCP) an overviewFastAPI-MCPHow to Use FastAPI MCP Server: A Complete Guide Candle (Rust framework)
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42:23
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 learning to uncover subtle abnormalities in brain function. We discuss the cultural and ethical barriers to AI adoption in medicine, how predictive data analysis could transform the diagnostic workflow, and what the future holds for medical imaging in a world increasingly shaped by intelligent systems.Featuring:Gavin Winston – LinkedIn, WebsiteChris Benson – Website, GitHub, LinkedIn, XDaniel Whitenack – Website, GitHub, XLinks:Detection of Epileptogenic Focal Cortical Dysplasia Using Graph Neural Networks: A MELD StudyMachine Learning in Neuroimaging across DisciplinesAutomated and Interpretable Detection of Hippocampal Sclerosis in Temporal Lobe Epilepsy: AID-HSLiterature review and protocol for a prospective multicentre cohort study on multimodal prediction of seizure recurrence after unprovoked first seizureDeep learning in neuroimaging of epilepsyNon-parametric combination of multimodal MRI for lesion detection in focal epilepsyDetection of covert lesions in focal epilepsy using computational analysis of multimodal magnetic resonance imaging data
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42:58
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 engineer productivity to open source agents that address GitHub issues. They dive into trust, tooling, collaboration, and what it means to build software in the era of AI agents. Whether you're coding from your laptop or your phone on a morning walk, the future is hands-free (and All Hands).Featuring:Robert Brennan – LinkedIn, XGraham Neubig – LinkedIn, XChris Benson – Website, GitHub, LinkedIn, XDaniel Whitenack – Website, GitHub, XLinks:All HandsAll Hands on GitHubAll Hands on Hugging Face
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42:04
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 insights from his hands-on work with agentic architectures and internal tools like "DIAL". Pavel also helps us understand things like MCP servers and why connecting assistants via APIs is easy—but making them useful is hard. Featuring:Pavel Veller – LinkedIn, XDaniel Whitenack – Website, GitHub, XLinks:EPAMDIALSWE-bench results
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42:52
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 acceleration. We explore how Groq optimizes the serving layer, adapts to industry shifts, and supports emerging model architectures. Featuring:Dhananjay Singh – LinkedIn, XChris Benson – Website, GitHub, LinkedIn, XDaniel Whitenack – Website, GitHub, XLinks:GroqSponsors:Augment Code - Developer AI that uses deep understanding of your large codebase and how you build software to deliver personalized code suggestions and insights. Augment provides relevant, contextualized code right in your IDE or Slack. It transforms scattered knowledge into code or answers, eliminating time spent searching docs or interrupting teammates.
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).
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!
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