Episodes

Oded Rechavi is a biologist at Tel Aviv University and the co-founder of QED, a company building AI to review scientific work. He's also spent years studying worms. We start with what's wrong with peer review and grant fundin...

Will AI take our jobs? We put the question to Alex Imas, the new Director of AGI Economics at Google DeepMind and a professor at Chicago Booth, whose entire job now is studying how frontier AI reshapes the economy. His short ...

In this episode, we sit down with Wenhu Chen, research scientist at Meta MSL, assistant professor at the University of Waterloo, and the person behind MMLU-Pro and MMMU. If you've read a frontier model release in the last two...

In the second half of our conversation with Jürgen Schmidhuber, we focus on the key ideas he's pursued since the early 1990s and discuss why he believes these concepts are only now being rediscovered. We start with JEPA. Jürg...

In this episode, we host Jürgen Schmidhuber - the man, the legend, one of the godfathers of modern AI. His lab worked out many ideas behind today’s systems (LSTM, world models, artificial curiosity, Transformer variants, and ...

In this episode, we sit with Max Welling, Professor of Machine Learning at the University of Amsterdam, co-founder and CTO of CuspAI, and a foundational figure behind variational autoencoders (VAEs), equivariant networks, and...

We talk with Mengye Ren , Assistant Professor at NYU's Center for Data Science, about what intelligence actually means once you step outside a benchmark, and why scaling a single centralized model isn't the whole story. We ge...

We host Tal Linzen, Associate Professor at NYU and Research Scientist at Google, for a conversation on the intersection of cognitive science and large language models. We discussed why children can learn language from around ...

We talked with Christian Szegedy, co-inventor of Inception and Batch Normalization, founding scientist at xAI, now at Math Inc, about what it takes to build a frontier lab, and why he left xAI to work on formal mathematics. C...

We sat down with Rao Kambhampati, a Professor of CS at Arizona State University and former President of AAAI, to talk about reasoning models: what they are, when they work, and when they break. Rao has been working on plannin...

We talked with Sasha Rush , researcher at Cursor and professor at Cornell, about what it actually feels like to we in the heart of the AI revolution and build coding agents right now. Sasha shared how these systems are changi...

How Denoising Secretly Powers Everything in AI Peyman Milanfar is a Distinguished Scientist at Google, leading its Computational Imaging team. He's a member of the National Academy of Engineering, an IEEE Fellow, and one of t...

In this episode, we talk with Stefano Ermon, Stanford professor, co-founder & CEO of Inception AI, and co-inventor of DDIM, FlashAttention, DPO, and score-based/diffusion models, about why diffusion-based language models may...

Naomi Saphra, Kempner Research Fellow at Harvard and incoming Assistant Professor at Boston University, joins us to explain why you can't do interpretability without understanding training dynamics, in the same way you can't...

Stefano Soatto, VP for AI at AWS and Professor at UCLA, joins us to explore how the agentic era fundamentally redefines machine learning, from static train-and-test models to dynamic, interactive control systems. This shift u...

Tanishq Abraham , CEO and co-founder of Sophont.ai , joins us to talk about building foundation models specifically for medicine. Sophont is trying to be something like an OpenAI or Anthropic but for healthcare - training mo...

Bayan Bruss, VP of Applied AI at Capital One, joins us to talk about building AI systems that can make autonomous financial decisions, and why money might be the hardest problem in machine learning. Bayan leads Capital One's ...

Cody Blakeney from Datology AI joins us to talk about data curation - the unglamorous but critical work of figuring out what to actually train models on. Cody's path from writing CUDA kernels to spending his days staring at w...

Guest: Niloofar Mireshghallah (Incoming Assistant Professor at CMU, Member of Technical Staff at Humans and AI) In this episode, we dive into AI privacy, frontier model capabilities, and why academia still matters. We kick of...

Atlas Wang (UT Austin faculty, XTX Research Director) joins us to explore two fascinating frontiers: the foundations of symbolic AI and the practical challenges of building AI systems for quantitative finance. On the symbolic...

In this episode, we hosted Judah Goldfeder, a PhD candidate at Columbia University and student researcher at Google, to discuss robotics, reproducibility in ML, and smart buildings. Key topics covered: Robotics challenges: We...

In this episode, we talk with Will Brown, a research lead at Prime Intellect , about his journey into reinforcement learning (RL) and multi-agent systems, exploring their theoretical foundations and practical applications. We...

In this episode, we discuss various topics in AI, including the challenges of the conference review process, the capabilities of Kimi K2 thinking, the advancements in TPU technology, the significance of real-world data in rob...

In this episode, we talked about AI news and recent papers. We explored the complexities of using AI models in healthcare (the Nature Medicine paper on GPT-5's fragile intelligence in medical contexts). We discussed the delic...