Weakly Supervised Causal Representation Learning with Johann Brehmer - #605

Weakly Supervised Causal Representation Learning with Johann Brehmer - #605

Today we’re excited to kick off our coverage of the 2022 NeurIPS conference with Johann Brehmer, a research scientist at Qualcomm AI Research in Amsterdam. We begin our conversation discussing some of the broader problems that causality will help us solve, before turning our focus to Johann’s paper Weakly supervised causal representation learning, which seeks to prove that high-level causal representations are identifiable in weakly supervised settings. We also discuss a few other papers that the team at Qualcomm presented, including neural topological ordering for computation graphs, as well as some of the demos they showcased, which we’ll link to on the show notes page. The complete show notes for this episode can be found at twimlai.com/go/605.

Episoder(782)

Infrastructure Scaling and Compound AI Systems with Jared Quincy Davis - #740

Infrastructure Scaling and Compound AI Systems with Jared Quincy Davis - #740

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Building Voice AI Agents That Don’t Suck with Kwindla Kramer - #739

In this episode, Kwindla Kramer, co-founder and CEO of Daily and creator of the open source Pipecat framework, joins us to discuss the architecture and challenges of building real-time, production-rea...

15 Jul 20251h 13min

Distilling Transformers and Diffusion Models for Robust Edge Use Cases with Fatih Porikli - #738

Distilling Transformers and Diffusion Models for Robust Edge Use Cases with Fatih Porikli - #738

Today, we're joined by Fatih Porikli, senior director of technology at Qualcomm AI Research for an in-depth look at several of Qualcomm's accepted papers and demos featured at this year’s CVPR confere...

9 Jul 20251h

Building the Internet of Agents with Vijoy Pandey - #737

Building the Internet of Agents with Vijoy Pandey - #737

Today, we're joined by Vijoy Pandey, SVP and general manager at Outshift by Cisco to discuss a foundational challenge for the enterprise: how do we make specialized agents from different vendors colla...

24 Jun 202556min

LLMs for Equities Feature Forecasting at Two Sigma with Ben Wellington - #736

LLMs for Equities Feature Forecasting at Two Sigma with Ben Wellington - #736

Today, we're joined by Ben Wellington, deputy head of feature forecasting at Two Sigma. We dig into the team’s end-to-end approach to leveraging AI in equities feature forecasting, covering how they i...

17 Jun 202559min

Zero-Shot Auto-Labeling: The End of Annotation for Computer Vision with Jason Corso - #735

Zero-Shot Auto-Labeling: The End of Annotation for Computer Vision with Jason Corso - #735

Today, we're joined by Jason Corso, co-founder of Voxel51 and professor at the University of Michigan, to explore automated labeling in computer vision. Jason introduces FiftyOne, an open-source platf...

10 Jun 202556min

Grokking, Generalization Collapse, and the Dynamics of Training Deep Neural Networks with Charles Martin - #734

Grokking, Generalization Collapse, and the Dynamics of Training Deep Neural Networks with Charles Martin - #734

Today, we're joined by Charles Martin, founder of Calculation Consulting, to discuss Weight Watcher, an open-source tool for analyzing and improving Deep Neural Networks (DNNs) based on principles fro...

5 Jun 20251h 25min

Google I/O 2025 Special Edition - #733

Google I/O 2025 Special Edition - #733

Today, I’m excited to share a special crossover edition of the podcast recorded live from Google I/O 2025! In this episode, I join Shawn Wang aka Swyx from the Latent Space Podcast, to interview Logan...

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