Equivariant Priors for Compressed Sensing with Arash Behboodi - #584

Equivariant Priors for Compressed Sensing with Arash Behboodi - #584

Today we’re joined by Arash Behboodi, a machine learning researcher at Qualcomm Technologies. In our conversation with Arash, we explore his paper Equivariant Priors for Compressed Sensing with Unknown Orientation, which proposes using equivariant generative models as a prior means to show that signals with unknown orientations can be recovered with iterative gradient descent on the latent space of these models and provide additional theoretical recovery guarantees. We discuss the differences between compression and compressed sensing, how he was able to evolve a traditional VAE architecture to understand equivalence, and some of the research areas he’s applying this work, including cryo-electron microscopy. We also discuss a few of the other papers that his colleagues have submitted to the conference, including Overcoming Oscillations in Quantization-Aware Training, Variational On-the-Fly Personalization, and CITRIS: Causal Identifiability from Temporal Intervened Sequences. The complete show notes for this episode can be found at twimlai.com/go/584

Avsnitt(783)

How Capital One Delivers Multi-Agent Systems with Rashmi Shetty - #765

How Capital One Delivers Multi-Agent Systems with Rashmi Shetty - #765

In this episode, Rashmi Shetty, senior director of enterprise generative AI platform at Capital One, joins us to explore how the company is designing, deploying, and scaling multi-agent systems in a h...

16 Apr 54min

The Race to Production-Grade Diffusion LLMs with Stefano Ermon - #764

The Race to Production-Grade Diffusion LLMs with Stefano Ermon - #764

Today, we're joined by Stefano Ermon, associate professor at Stanford University and CEO of Inception Labs to discuss diffusion language models. We dig into how diffusion approaches—traditionally used...

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Agent Swarms and Knowledge Graphs for Autonomous Software Development with Siddhant Pardeshi - #763

Agent Swarms and Knowledge Graphs for Autonomous Software Development with Siddhant Pardeshi - #763

In this episode, Sid Pardeshi, co-founder and CTO of Blitzy, joins us to discuss building autonomous development systems able to deliver production-ready software at enterprise scale. Sid contrasts AI...

10 Mars 1h 16min

AI Trends 2026: OpenClaw Agents, Reasoning LLMs, and More with Sebastian Raschka - #762

AI Trends 2026: OpenClaw Agents, Reasoning LLMs, and More with Sebastian Raschka - #762

In this episode, Sebastian Raschka, independent LLM researcher and author, joins us to break down how the LLM landscape has changed over the past year and what is likely to matter most in 2026. We dis...

26 Feb 1h 18min

The Evolution of Reasoning in Small Language Models with Yejin Choi - #761

The Evolution of Reasoning in Small Language Models with Yejin Choi - #761

Today, we're joined by Yejin Choi, professor and senior fellow at Stanford University in the Computer Science Department and the Institute for Human-Centered AI (HAI). In this conversation, we explore...

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Intelligent Robots in 2026: Are We There Yet? with Nikita Rudin - #760

Intelligent Robots in 2026: Are We There Yet? with Nikita Rudin - #760

Today, we're joined by Nikita Rudin, co-founder and CEO of Flexion Robotics to discuss the gap between current robotic capabilities and what’s required to deploy fully autonomous robots in the real wo...

8 Jan 1h 6min

Rethinking Pre-Training for Agentic AI with Aakanksha Chowdhery - #759

Rethinking Pre-Training for Agentic AI with Aakanksha Chowdhery - #759

Today, we're joined by Aakanksha Chowdhery, member of technical staff at Reflection, to explore the fundamental shifts required to build true agentic AI. While the industry has largely focused on post...

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Why Vision Language Models Ignore What They See with Munawar Hayat - #758

Why Vision Language Models Ignore What They See with Munawar Hayat - #758

In this episode, we’re joined by Munawar Hayat, researcher at Qualcomm AI Research, to discuss a series of papers presented at NeurIPS 2025 focusing on multimodal and generative AI. We dive into the p...

9 Dec 202557min

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