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

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.

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.

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.

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.

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.

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.

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.

Lin Qiao, CEO and co-founder of Fireworks AI and former AI leader at Meta, shares insights on optimizing the AI development lifecycle. She emphasizes the importance of aligning training and inference systems to minimize deployment friction. Lin discusses the shift from viewing models as commodities to essential product assets and explains reinforcement fine-tuning for leveraging proprietary data. She also tackles the complex challenge of balancing cost, latency, and quality in AI optimization while envisioning a future with closed-loop systems for automated model improvement.

Filip Kozera, Founder and CEO of Wordware, is on a mission to revolutionize how we interact with AI through natural language as the new programming interface. He discusses the architecture of AI agents, emphasizing the need for 'graceful recovery' systems that involve humans when agents hit knowledge limits. The conversation explores the shift to user-centric workflows and the challenges of data silos in SaaS platforms. Filip's vision for the 'word artisan' potentially transforms non-technical users into AI managers, reshaping knowledge work.

Jared Quincy Davis, Founder and CEO at Foundry and a former DeepMind core deep learning team member, discusses transformative 'compound AI systems' that merge diverse AI models for superior performance. He introduces 'laconic decoding' and explains how these systems can boost efficiency while cutting costs. The conversation covers the interplay between AI algorithms and cloud infrastructure, the evolution of ensemble models, and the potential of hybrid systems. Davis emphasizes co-design and innovative strategies to revolutionize the AI landscape and enhance developer experience.