Synthetic data has been around for a long time, decades even. But as KPMG’s Fabiana Clemente points out, “That doesn’t mean there aren’t a lot of misconceptions.” Fabiana sat down with Ben to clarify some of the current applications of synthetic data and new directions the field is taking—working with offshore teams when privacy controls […]

As the founder, editor, and lead writer of Turing Post, Ksenia Se spends her days peering into the emerging future of artificial intelligence. She joined Ben to discuss the current state of adoption: what people are actually doing right now, the big topics that got the most traction this year, and the trends to look […]

MLOps is dead. Well, not really, but for many the job is evolving into LLMOps. In this episode, Abide AI founder and LLMOps author Abi Aryan joins Ben to discuss what LLMOps is and why it’s needed, particularly for agentic AI systems. Listen in to hear why LLMOps requires a new way of thinking about […]

In this episode, Laurence Moroney, director of AI at Arm, joins Ben Lorica to chat about the state of deep learning frameworks—and why you may be better off thinking a step higher, on the solution level. Listen in for Laurence’s thoughts about posttraining; the evolution of on-device AI (and how tools like ExecuTorch and LiteRT […]

In this episode, Ben Lorica and Chris Butler, director of product operations for GitHub’s Synapse team, chat about the experimentation Chris is doing to incorporate generative AI into the product development process—particularly with the goal of reducing toil for cross-functional teams. It isn’t just automating busywork (although there’s some of that). He and his team […]

In this episode, Ben Lorica and Drew Breunig, a strategist at the Overture Maps Foundation, talk all things context engineering: what’s working, where things are breaking down, and what comes next. Listen in to hear why huge context windows aren’t solving the problems we hoped they might, why companies shouldn’t discount evals and testing, and […]

In this episode, Ben Lorica and Anthropic interpretability researcher Emmanuel Ameisen get into the work Emmanuel’s team has been doing to better understand how LLMs like Claude work. Listen in to find out what they’ve uncovered by taking a microscopic look at how LLMs function—and just how far the analogy to the human brain holds. […]

Everyone is talking about agents: single agents and, increasingly, multi-agent systems. What kind of applications will we build with agents, and how will we build with them? How will agents communicate with each other effectively? Why do we need a protocol like A2A to specify how they communicate? Join Ben Lorica as he talks with […]

Jay Alammar, director and Engineering Fellow at Cohere, joins Ben Lorica to talk about building AI applications for the enterprise, using RAG effectively, and the evolution of RAG into agents. Listen in to find out what kinds of metadata you need when you’re onboarding a new model or agent; discover how an emphasis on evaluation […]

Phillip Carter, formerly of Honeycomb, and Ben Lorica talk about observability and AI—what observability means, how generative AI causes problems for observability, and how generative AI can be used as a tool to help SREs analyze telemetry data. There’s tremendous potential because AI is great at finding patterns in massive datasets, but it’s still a […]