Practical AI

They explore whether open vs closed models still matter as AI moves into edge devices and physical systems. Small models and new chips making embedded AI affordable get spotlighted. Discussion shifts to systems, workflows, and agentic architectures becoming the real sources of value. They examine risks of relying on third-party APIs and the need for governance and modular tooling.

A frontier model sparks talk about cybersecurity fears, hype cycles, and the growing push for AI governance. Then things get weird with a sneaker company trying to become a neocloud player. The conversation also hits tokenmaxxing, pricey coding habits, AI chat logs turning into legal evidence, and the market for private AI messaging.

Autonomous driving is not just a big tech or closed-source game, it's becoming accessible through open innovation and real-world deployment. Dan and Chris sit down with Harald Schäfer, CTO at Comma AI, to explore how OpenPilot is bringing self-driving to everyday vehicles using open source AI. We dive into the intersection of machine learning, robotics, and simulation, including how world models are enabling training at scale and shaping the future of autonomy.Featuring:Harald Schäfer – LinkedInChris Benson – Website, LinkedIn, Bluesky, GitHub, XDaniel Whitenack – Website, GitHub, XLinks:CommaUpcoming Events: Register for upcoming webinars here!

They dissect a major code leak and how it unfolded, from .map exposures to a malicious package that spread widely. The conversation explores why agent orchestration and memory design are the real intellectual property. They cover rapid community reconstructions, legal and supply-chain fallout, and what builders should change about sandboxing and verification.

Miklós Koren, economist and CEU professor studying technology and competitiveness. He discusses how AI-driven vibe coding shifts incentives away from traditional open source. Short takes cover changing collaboration patterns, attention economics, experiments on AI recommendations, and implications for libraries, tooling, and developer roles.

Brandon Shibley, Edge AI solutions engineering lead at Edge Impulse (Qualcomm), helps deploy and optimize ML on constrained devices. He explains what counts as edge in 2026. He contrasts tiny specialized models with large cloud LLMs and shows how cascades save power. He covers real-world constraints like latency, power, privacy, and how tooling and hardware advances make practical edge AI possible.

Steve Klabnik, a Rust contributor and co-author of The Rust Programming Language, experimented with AI agents to build the Rue programming language. He shares his shift from AI skeptic to hands-on experimenter. Topics include agentic coding, using AI to accelerate language design, tradeoffs in developer workflows, and trust and safety when letting agents modify code.

Ben Buchanan, Assistant Professor at Johns Hopkins SAIS and former White House AI advisor, brings a policy and geopolitical lens to computing power. He discusses why compute, not data, drives AI progress. He explores chip supply chains, Taiwan’s strategic role, government–industry relations, export controls, and the challenges of international AI governance.

Deborah Golden, Chief Innovation Officer at Deloitte, brings decades of experience leading AI and digital transformations. She discusses how empathy and vulnerability reshape leadership. She introduces cognitive synthesis and the idea of 'neural athletes' to describe modern mental strain. She talks about anti-fragile system design and practical low-risk AI experiments to build comfort.

Sean McGregor, co-founder of the AI Verification & Evaluation Research Institute and creator of the AI Incident Database, is an AI safety and incident-collection specialist. He discusses why incident reporting matters and how databases track harms. He contrasts benchmarks with real-world audits, recounts red-team findings at DEF CON, and highlights common failure modes and the need for scalable verification.