Why Image Generation Needs More Than Bigger Models with Fatih Porikli - #773
Text-to-image models have become remarkably good at producing realistic images. But realism isn’t the same as correctness. Ask for several distinct people, a specific composition, or a high-resolution...
12 Aug 56min
Why Models Are AI’s Next Training Dataset with Damian Borth - #772
For more than a decade, AI has advanced by training ever-larger models on ever-larger datasets. But as high-quality training data becomes harder to find and pretraining grows increasingly expensive, r...
27 Juli 47min
Why AI Agents Break the GenAI Security Model with Devvret Rishi - #770
In this episode, Sam talks with Dev Rishi, GM of AI at Rubrik, about what happens when agents move beyond answering questions and start taking action across tools, systems, and business processes. We...
16 Juni 56min
Is RAG Dead? Lessons from Building AI for Tax Law with Alex Bowcut - #769
As context windows grow into the millions of tokens, many AI practitioners are questioning whether retrieval-augmented generation (RAG) is still necessary. If modern models can ingest entire libraries...
9 Juni 51min
Relational Foundation Models for Enterprise Data with Jure Leskovec - #768
In this episode, Jure Leskovec, co-founder and chief scientist at Kumo and professor of computer science at Stanford, joins us to explore two fronts of his work: AI for science and relational deep lea...
21 Maj 1h 6min
How to Find the Agent Failures Your Evals Miss with Scott Clark - #767
In this episode, Scott Clark, co-founder and CEO of Distributional, joins us to explore how teams can reliably operate and improve complex LLM systems and agents in production. Scott introduces a Masl...
7 Maj 53min
How to Engineer AI Inference Systems with Philip Kiely - #766
In this episode, Philip Kiely, head of AI education at Baseten, joins us to unpack the fast-evolving discipline of inference engineering. We explore why inference has become the stickiest and most cri...
30 Apr 54min
