World Models and the Future of Spatial AI with Justin Johnson - #775
In this episode, Justin Johnson, co-founder of World Labs, joins us to discuss world models and the emerging field of spatial AI. We explore why many researchers see capabilities beyond language as an...
1 Sep 1h 6min
Why the Next AI Breakthrough May Come from Physics with Max Welling - #774
The conventional wisdom in AI is that the next breakthrough will come from more compute, more data, and larger models. But what if the next leap comes from somewhere else? In this episode, Max Wellin...
26 Aug 58min
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 Jul 47min
How AI Learns to Smell with Alex Wiltschko - #771
In this episode, Alex Wiltschko, founder and CEO of Osmo, joins the show to discuss his goal of giving computers a sense of smell and what it takes to build olfactory intelligence. We explore the sci...
8 Jul 59min
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 Jun 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 Jun 51min
