The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

Stefano Ermon, Stanford associate professor and CEO of Inception known for work on generative models, discusses adapting diffusion methods from images to text and code. He covers technical hurdles of discrete tokens, Mercury 2’s multi-token, low-latency inference, tradeoffs between denoising iterations and autoregressive sampling, real-world serving challenges, and where diffusion shines like editing and fast voice/agent loops.

Siddhant Pardeshi, co-founder and CTO of Blitzy, builds autonomous systems that generate production-ready code at enterprise scale. He discusses hybrid graph-plus-vector maps for navigating large repos. Short sentences cover agent swarms and orchestration, dynamic agent personas and tool selection, why flat memories fail, and real-world evals and verification for production readiness.

Sebastian Raschka, independent LLM researcher and author of books on building reasoning models. He breaks down 2026 trends: the move from scaling to reasoning-focused post-training and inference tricks. Talks practical agentic workflows and local agents like OpenClaw, tool integration vs model quality, architecture shifts (MOE, attention tweaks), long-context trade-offs, and challenges in continual learning.

Yejin Choi, Stanford professor focused on reasoning, synthetic data, and AI alignment, discusses making small language models reason better. She covers synthetic data generation, imitation learning, reinforcement pretraining that encourages internal “thinking,” and Prismatic Synthesis for diverse math data. The conversation also tackles mode collapse, spectrum tuning to preserve diversity, and pluralistic alignment to reflect varied human values.

Nikita Rudin, Co-founder and CEO of Flexion Robotics, dives into the fascinating world of autonomous robots. He discusses the ongoing challenges of robot locomotion, highlighting the complexities of sim-to-real transfer with visual inputs. The conversation covers the debate between end-to-end models and modular approaches. Nikita introduces 'real-to-sim' calibration, revealing how real-world data refines simulations for better outcomes. He also shares insights on humanoid robots, their upcoming potential in 2026, and practical advice for aspiring roboticists.

Aakanksha Chowdhery, a machine learning researcher from Reflection, dives into the future of agentic AI. She critiques the current reliance on post-training techniques, advocating for a transformative approach to pre-training. Aakanksha highlights the need for evolving attention mechanisms and tailored training data to enhance long-term reasoning and planning. She discusses the importance of 'trajectory' training data and the risks of synthetic data, all while underscoring the significance of rigorous evaluation in building agentic models.

Munawar Hayat, a researcher at Qualcomm AI Research specializing in multimodal generative AI, dives into the intricacies of Vision-Language Models (VLMs). He discusses the puzzling issue of object hallucination, revealing why these models often overlook visual elements in favor of language. Munawar also introduces attention-guided alignment techniques and a novel approach to generalized contrastive learning for efficient multi-modal retrieval. He shares insights on the Multi-Human Testbench designed to tackle identity leakage challenges in generative models, bringing clarity to this evolving field.

Zain Asgar, co-founder and CEO of Gimlet Labs, is an expert in efficient AI compute orchestration and heterogeneous inference. He discusses the challenges of handling token-heavy agentic workloads and the need for diverse hardware solutions. Zain elaborates on Gimlet's innovative three-layer architecture for workload disaggregation and LLM-driven optimization. He shares insights on the complexities of networking, the trade-offs in precision, and the future of resource scheduling, all while emphasizing the importance of cost-effective AI operations.

Join Devi Parikh, co-founder of Yutori and a pioneering AI researcher, as she discusses the futuristic concept of proactive web agents that can streamline our online interactions. Devi explains how these agents operate using visual models that leverage screenshots for improved reliability over traditional methods. She reveals insights into Yutori's innovative training process, the challenges of web navigation, and the pivotal role of feedback in enhancing agent performance. Tune in to explore how these advancements could reshape our digital experiences!

Robin Braun, VP of AI at HPE, and Luke Norris, CEO of Kamiwaza, delve into AI's role in transforming smart cities and enterprises. They explore the 'Agentic Smart City' project in Vail, focusing on automating website accessibility and digitizing legacy data. The discussion highlights the significance of private cloud infrastructure, fresh data, and practical use cases that deliver real ROI. Learn how innovative technologies can enhance fire detection and urban monitoring, reducing costs and improving compliance in complex workflows.