The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

Publicly listed emails

team@twimlai.com

Looking for the right person? Join Podseeker to find direct host and producer contacts and manage your podcast outreach.

Why the Next AI Breakthrough May Come from Physics with Max Welling - #774

August 25, 2026

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 Welling—co-founder and CTO of CuspAI and professor at the University of Amsterdam—argues that physics may provide some of the ideas behind the next generation of AI systems. We begin with CuspAI’s work using generative AI to design entirely new materials for semiconductors, batteries, carbon capture, ...

Why Image Generation Needs More Than Bigger Models with Fatih Porikli - #773

August 12, 2026

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 image generated locally, and today’s models still struggle in surprising ways. In this episode, Fatih Porikli, Vice President of Technology at Qualcomm, joins me to discuss what remains unsolved in image generation and several approaches his team presented at CVPR to address those challenges. W...

Why Models Are AI’s Next Training Dataset with Damian Borth - #772

July 27, 2026

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, researchers are looking for new ways to keep foundation models improving. In this episode, Damian Borth, professor of AI and machine learning at the University of St. Gallen, argues we’ve been overlooking an important source of knowledge: the models we’ve already trained. His group’s work on weig...