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In this episode, M.G. Siegler and Alex discuss the current state of AI, exploring whether the technology needs a Steve Jobs-like figure, analyzing the AI chaos among big tech companies, and making predictions about the tech landscape in 2026.
Nathan discusses his son Ernie's cancer treatment progress, provides an in-depth analysis of the current AI landscape by examining the strengths and potential weaknesses of Google DeepMind, OpenAI, Anthropic, and xAI, and shares his thoughts on model performance, technological advancements, and the companies' strategies in the AI race.
Demis Hassabis discusses Google DeepMind's path to artificial general intelligence, exploring the challenges of building AI systems with reasoning, creativity, and consistent behavior across cognitive tasks, while also highlighting potential breakthroughs in science, health, and technology.
Sam Rodriguez discusses the potential and current limitations of AI in scientific research, exploring how AI tools like Kosmos can help analyze data and generate novel insights while highlighting the significant challenges that remain in translating AI discoveries into practical scientific breakthroughs.
In this episode, Sebastian Borgeaud, a pre-training lead for Gemini 3 at Google DeepMind, discusses the landmark model's development, exploring the shift from "infinite data" to a data-limited regime, the importance of research taste, and the evolving landscape of AI pre-training and model capabilities.
Reid Hoffman discusses how AI will enhance human capabilities through "superagency," emphasizing that artificial intelligence should be viewed as amplification intelligence that expands human potential rather than replacing humans, and shares an optimistic vision of AI as a collaborative tool that can help solve global challenges and create new opportunities.
A deep dive into AI's potential transformative impact, exploring whether it's just another platform shift or something closer to electricity, examining technological bottlenecks, industry implications, and the uncertain path to realizing AI's full potential.
In a candid conversation with cardiologist Eric Topol, Adam Grant explores cutting-edge insights on longevity, debunking health myths, preventing major diseases, and the potential of AI in transforming medical care.
Pim turned down a $500M OpenAI offer and instead founded General Intuition, a world models startup leveraging Medal's 3.8B action-labeled game clips to build AI agents that can navigate, learn, and transfer skills across games and real-world scenarios.
In this episode, Kevin Roose and Casey Newton discuss OpenAI's "code red" response to competitive pressure from Google's Gemini and Anthropic's Claude, explore the latest AI models, and review recent examples of AI-generated "slop" across various domains.
Tim Cook is rumored to be on the verge of retiring from Apple in early 2026, amid discussions of succession planning and the company's evolving position in the AI landscape.
Moonshots podcast delves into the latest AI and technological advancements, discussing NVIDIA's record revenue, Elon Musk's space data centers, AI's potential to solve major global challenges, and the exponential progress in areas like robotics, energy, and healthcare.
Misha Laskin, co-founder of Reflection AI, discusses the company's mission to build frontier open intelligence, arguing that open-source AI models can compete with closed models and that the West needs to counter the rise of Chinese open-source AI technologies.
Aidan Gomez, co-founder and CEO of Cohere, discusses the transformative potential of AI in enterprise, reflecting on his journey from Google Brain researcher to building an AI platform focused on deploying large language models across critical industries.
Mustafa Suleyman, CEO of Microsoft AI, discusses how artificial intelligence will revolutionize work, education, and daily life over the next decade, emphasizing its potential to democratize knowledge and transform human capabilities.
Nathan Labenz discusses the ongoing progress in AI capabilities, countering arguments that AI is stalling, by highlighting advances in reasoning, context windows, multimodal abilities, and scientific contributions, while also exploring potential societal impacts and challenges in AI development.
Julian Schrittwieser from Anthropic discusses the exponential trajectory of AI capabilities, predicting that models will achieve full-day autonomous task completion by 2026 and expert-level performance across many professions by 2027, while exploring how pre-training combined with reinforcement learning enables AI agents to make novel scientific discoveries and potentially earn Nobel Prizes.
Nathan Labenz and Eric discuss the current state of AI, arguing that contrary to claims of slowing progress, AI is continuing to advance rapidly across various domains, including reasoning, scientific discovery, and multimodal capabilities.