Published 23 Jan 2026
Duration: 5524
Researchers discuss AI advancements in areas such as spreadsheet automation, reinforcement learning, and large language models.
From shipping Gemini Deep Think and IMO Gold to launching the Reasoning and AGI team in Singapore, Yi Tay has spent the last 18 months living through...
The podcast explores the integration of AI models in handling spreadsheet tasks, highlighting their ability to generate summaries and reduce the need for manual effort. It also mentions the "Nano Banana" project, which successfully creates calming images and helps maintain system stability. The conversation reflects on returning to a familiar research environment at Google after a long absence, emphasizing the comfort of established infrastructure.
A major focus is placed on reinforcement learning (RL) as a critical research area, particularly in decision-making and model training. The discussion covers the evolution of AI models, the importance of self-awareness in learning algorithms, and the challenges of moving from imitation-based learning to independent decision-making. The potential of large language models (LLMs) in tackling complex problems, such as those found in the International Mathematical Olympiad, is examined, along with the development of systems like Gemini. Other topics include data efficiency, the difficulties of training models on large-scale data, and the future potential of artificial general intelligence (AGI).
30 Mar 2026 Mistral: Voxtral TTS, Forge, Leanstral, & what's next for Mistral 4 w/ Pavan Kumar Reddy & Guillaume Lample
Mistral's Voxtral TTS is a 3B-parameter text-to-speech model leveraging neural audio codecs, semantic/acoustic token splitting, and efficient flow matching for multilingual real-time applications, balancing quality and cost while exploring future refinements in architecture, tokenization, and domain-specific training.
24 Mar 2026 Why There Is No "AlphaFold for Materials" AI for Materials Discovery with Heather Kulik
AI's role in education and materials science is debated, highlighting its potential to accelerate research in chemistry and physics through machine learning, yet acknowledging limitations in complex molecular design, data quality challenges, and the need for interdisciplinary collaboration and robust validation.
20 Mar 2026 Dreamer: the Personal Agent OS David Singleton
Dreamer is an AI platform democratizing access to agentic tools for non-technical users via customizable AI assistants, community-built apps, cross-device integration, and privacy-focused features, with a beta emphasis on accessibility, real-world productivity use cases, and third-party developer opportunities.
17 Mar 2026 Why Anthropic Thinks AI Should Have Its Own Computer Felix Rieseberg of Claude Cowork & Claude Code Desktop
Cowork is a cloud-native tool simplifying Cloud Code access for non-technical users through a balance of simplicity and flexibility, integrating with cloud services and Chrome while supporting diverse workflows via a lightweight virtual machine, developed in 10 days with a focus on modular components and ethical trade-offs in AI infrastructure.
12 Mar 2026 Retrieval After RAG: Hybrid Search, Agents, and Database Design Simon Hrup Eskildsen of Turbopuffer
TurboPuffer is a next-gen database platform focusing on AI-powered vector search, full-text search, and scalability, with a strong emphasis on hiring top talent and customer-driven innovation.