The TWIML AI Podcast with Sam Charrington

Genie 3: A New Frontier for World Models [Jack Parker-Holder and Shlomi Fruchter] - 743

Closing the Loop Between AI Training and Inference [Lin Qiao] - 742

Generative AI product development requires a cohesive, end-to-end platform that integrates training and inference to maintain velocity from experimentation to production. Lin Qiao, CEO of Fireworks AI and former head of PyTorch, emphasizes that model training is meaningless unless it directly improves product metrics, ...

Context Engineering for Productive AI Agents [Filip Kozera] - 741

Infrastructure Scaling and Compound AI Systems [Jared Quincy Davis] - 740

Building Voice AI Agents That Don’t Suck [Kwindla Kramer] - 739

Distilling Transformers and Diffusion Models for Robust Edge Use Cases [Fatih Porikli] - 738

Building the Internet of Agents [Vijoy Pandey] - 737

LLMs for Equities Feature Forecasting at Two Sigma [Ben Wellington] - 736

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

Grokking, Generalization Collapse, and Dynamics of Training Deep Neural Nets [Charles Martin] - 734

Google I/O 2025 Special Edition - 733

RAG Risks: Why Retrieval-Augmented LLMs Are Not Safer [Sebastian Gehrmann] - 732

From Prompts to Policies: How RL Builds Better AI Agents [Mahesh Sathiamoorthy] - 731

How OpenAI Builds AI Agents That Think and Act [Josh Tobin] - 730

CTIBench: How Good Are LLMs at Detecting Cyber Threats? [Nidhi Rastogi] - 729

Generative Benchmarking: Measuring AI Models Beyond Accuracy [Kelly Hong] - 728

Inside the “Neurons” of LLMs: Circuit Tracing Their Hidden Biology [Emmanuel Ameisen] - 727

Self-Reflecting LLMs: Reinforcement Learning That Boosts Reasoning [Maohao Shen] - 726

Inside Waymo’s New Foundation Model Powering Self-Driving Cars [Drago Anguelov] - 725

Dynamic Token Merging: 2× Faster Byte-Level LLMs [Julie Kallini] - 724