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 for images—are being adapted for text and code generation, the technical challenges of applying continuous methods to discrete token spaces, and how diffusion models compare to traditional autoregressive LLMs. Stefano introduces Mercury 2, a commercial-scale diffusion LLM that can generate multiple tokens simultaneously and achieve inference speeds 5-10x faster than small frontier models, paving the way for latency-sensitive applications like voice interactions and fast agentic loops. We also cover the open research challenges in diffusion LLM training, serving infrastructure requirements, and post-training for diffusion-based systems. Finally, Stefano shares his perspective on whether diffusion models can rival or surpass autoregressive LLMs at scale, the advantages for highly controllable generation, and what the future of multimodal diffusion models might look like. The complete show notes for this episode can be found at https://twimlai.com/go/764.

Episoder(782)

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

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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...

29 Jan 1h 6min

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...

17 Des 202552min

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 Des 202557min

Scaling Agentic Inference Across Heterogeneous Compute with Zain Asgar - #757

Scaling Agentic Inference Across Heterogeneous Compute with Zain Asgar - #757

In this episode, Zain Asgar, co-founder and CEO of Gimlet Labs, joins us to discuss the heterogeneous AI inference across diverse hardware. Zain argues that the current industry standard of running al...

2 Des 202548min

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