

The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Sam Charrington
Machine learning and artificial intelligence are dramatically changing the way businesses operate and people live. The TWIML AI Podcast brings the top minds and ideas from the world of ML and AI to a broad and influential community of ML/AI researchers, data scientists, engineers and tech-savvy business and IT leaders. Hosted by Sam Charrington, a sought after industry analyst, speaker, commentator and thought leader. Technologies covered include machine learning, artificial intelligence, deep learning, natural language processing, neural networks, analytics, computer science, data science and more.
Episodes
Mentioned books

40 snips
Oct 22, 2025 • 1h 13min
Vibe Coding's Uncanny Valley with Alexandre Pesant - #752
In this conversation, Alexandre Pesant, AI lead at Lovable, delves into vibe coding, a transformative practice in software development. He explains how this approach shifts focus from typing code to expressing intent through higher-level abstractions. Alex shares insights on coding agents and the critical role of context engineering. He discusses Lovable’s evolution from complex agent systems to simpler workflows and back as technologies improved. Listeners also gain perspectives on AI's impact on engineering roles and the importance of robust evaluations in creating successful AI-native development tools.

43 snips
Oct 14, 2025 • 58min
Dataflow Computing for AI Inference with Kunle Olukotun - #751
Kunle Olukotun, a Stanford professor and chief technologist at SambaNova Systems, dives into reconfigurable dataflow architectures for AI. He explains how this innovative approach enhances AI inference by dynamically matching hardware to model dataflows, leading to reduced bandwidth bottlenecks. Kunle also highlights the benefits of fast model switching and efficient multi-model serving, crucial for low-latency applications. Plus, he explores future possibilities of using AI to create compilers for evolving hardware setups, offering insights into significant performance improvements.

190 snips
Oct 7, 2025 • 57min
Recurrence and Attention for Long-Context Transformers with Jacob Buckman - #750
Jacob Buckman, co-founder and CEO of Manifest AI, dives deep into the world of long-context transformers. He discusses innovative techniques like windowed attention and the revolutionary Power Retention approach, which melds attention and recurrence for astonishing training speeds. Buckman also shares insights on Manifest AI's open-source tools, Vidrial and PowerCoder, and explores the significance of metrics in measuring context utility. Learn about the balance between state and weight for optimal compute architectures and the future potential of context length in AI.

100 snips
Sep 30, 2025 • 1h 5min
The Decentralized Future of Private AI with Illia Polosukhin - #749
Illia Polosukhin, co-author of the groundbreaking 'Attention Is All You Need' paper and co-founder of Near AI, dives into the intersection of decentralization and private AI. He shares his journey from Google to revolutionizing blockchain with the NEAR Protocol. Topics include confidential computing for user data protection and the risks of AI centralization. Illia emphasizes a trust-building approach through open model training and formal verification. He also explores tokenized incentives for data contributions and the future of privacy in AI deployment.

154 snips
Sep 23, 2025 • 1h 4min
Inside Nano Banana 🍌 and the Future of Vision-Language Models with Oliver Wang - #748
Oliver Wang, a Principal Scientist at Google DeepMind, shares insights on the transformative capabilities of the Gemini 2.5 Flash Image, codenamed 'Nano Banana.' He explores the evolution from specialized image generators to integrated multimodal agents, highlighting how Nano Banana generates and edits images while preserving consistency. Oliver discusses the balance between aesthetics and accuracy, unexpected creative applications, and the future of AI models that could ‘think’ in images. He also warns about the risks associated with training on synthetic data.

147 snips
Sep 16, 2025 • 58min
Is It Time to Rethink LLM Pre-Training? with Aditi Raghunathan - #747
In this discussion, Aditi Raghunathan, an assistant professor at Carnegie Mellon University, tackles the limitations of large language models (LLMs). She presents insights from her award-winning paper on enhancing creativity beyond next-token prediction. Aditi introduces the innovative 'Roll the dice' method to foster randomness and 'Look before you leap' for deeper thought processes. The conversation also covers the paradox of 'catastrophic overtraining' and her pursuit of more controllable models through concepts like 'memorization sinks.' Her research aims to reshape our understanding of AI adaptability.

122 snips
Sep 9, 2025 • 1h 5min
Building an Immune System for AI Generated Software with Animesh Koratana - #746
Join Animesh Koratana, founder and CEO of PlayerZero, as he delves into the exciting world of AI-assisted coding tools. Discover how rapid advancements in AI have created a gap between code generation speed and effective maintenance processes. Animesh discusses the innovative use of code simulations to build a memory bank of past bugs and predictive models to enhance software reliability. He also explores the future of the software development lifecycle, emphasizing the need to adapt organizational workflows for an AI-driven landscape.

50 snips
Sep 2, 2025 • 1h 12min
Autoformalization and Verifiable Superintelligence with Christian Szegedy - #745
Christian Szegedy, Chief Scientist at Morph Labs and a pioneer of the Inception architecture, discusses the future of AI through autoformalization. He explains how translating mathematical concepts into formal logic can enhance AI safety and reliability. The conversation highlights the contrast between informal reasoning in current models and the provable correctness of formal systems. Szegedy envisions AI surpassing human scientists in specialized fields while serving as a tool for humanity's self-understanding.

83 snips
Aug 26, 2025 • 1h 10min
Multimodal AI Models on Apple Silicon with MLX with Prince Canuma - #744
Prince Canuma, an ML engineer and open-source developer known for his contributions to Apple's MLX ecosystem, discusses his journey in optimizing AI for Apple Silicon. He shares insights on adapting models, the trade-offs between GPU and Neural Engine, and innovative techniques like pruning and quantization for enhanced performance. Prince introduces 'Fusion,' a unique approach to model behavior without retraining, and presents Marvis, a real-time voice agent. His vision for future AI focuses on multimodal models that adapt seamlessly across various media.

162 snips
Aug 19, 2025 • 1h 1min
Genie 3: A New Frontier for World Models with Jack Parker-Holder and Shlomi Fruchter - #743
In this engaging discussion, Jack Parker-Holder and Shlomi Fruchter, both researchers at Google DeepMind, dive into Genie 3, a groundbreaking model that creates playable virtual worlds. They explore the evolution of world models in AI, emphasizing their importance for decision-making and planning. The duo sheds light on Genie 3’s real-time interactivity, visual memory capabilities, and the challenges faced in its development. They also touch on the innovative concept of promptability, showcasing how the model can dynamically manipulate virtual environments, paving the way for exciting applications.