alignment

Robert Miles covers a paper where researchers ran real versions of his earlier mesa-optimizer thought experiments. They show inner misalignment, where an AI learns the wrong goal in training and misbehaves when deployed.

A Bankless podcast interview with Paul Christiano of the Alignment Research Center on the AI alignment problem and possible solutions. It also covers his views on how an AI takeover might unfold.

Robert Miles gives a remastered introduction to AI safety, adapted from a talk in London. It lays out why advanced AI could go wrong and answers common objections.

A three-hour Lex Fridman podcast conversation with AI researcher Eliezer Yudkowsky about the dangers of superintelligent AI and his argument that it could end human civilization. It covers AI alignment, why he thinks LLM capabilities are poorly understood, and the case for extreme caution.

Dwarkesh Patel interviews OpenAI chief scientist Ilya Sutskever on time to AGI, what comes after generative models, data limits, alignment, and competing with Google. The title centers on whether next-token prediction could surpass human intelligence.

Sebastien Bubeck presents the Sparks of AGI paper at MIT, showing early experiments with GPT-4 across many domains and asking whether artificial intelligence has arrived. It includes the TikZ unicorn example.

Robert Miles goes through ten common reasons people give for dismissing AI safety, adapted from Stuart Russell's list, and answers each one. It is aimed at skeptics and newcomers.

Computerphile interviews AI safety researcher Rob Miles about ChatGPT: how it was trained with human feedback, why it tends to produce confident nonsense, and where it may or may not be dangerous.

Veritasium's Derek Muller gives a Perimeter Institute livestream on how AI might change teaching and learning. He draws on past technology shifts and cognitive science to argue that learning requires effortful repetition.

Tristan Harris and Aza Raskin of the Center for Humane Technology present why current AI capabilities pose catastrophic societal risks. They argue companies are racing to deploy without adequate safety, and that institutions must adapt. It was given before GPT-4's launch.

Geoffrey Hinton's 2025 Royal Institution Discourse on what AI has learned from biological intelligence and how it might surpass it. He explains neural networks and argues that human language use resembles what backpropagation-trained networks do.

Lex Fridman's long conversation with Andrej Karpathy on Tesla's self-driving approach, Optimus, neural networks, transformers, AGI and more. It also touches on his OpenAI work and working with Elon Musk.

Yannic Kilcher explains how he trained a language model on three years of 4chan's /pol/ board and let it post on the site. He evaluates how good the model was and discusses the ethics and fallout.

FTC Chair Lina Khan sits down with Jon Stewart on The Daily Show to discuss the agency's work protecting consumers from unfair business practices. Topics include the FTC's antitrust lawsuit against Amazon, healthcare industry actions, and whether tech companies are racing to control AI.

Lex Fridman interviews chip architect Jim Keller about the future of computing, AI, life and consciousness. Topics include CPU design, branch prediction and why imperfect designs often win.

A five-hour Lex Fridman interview with John Carmack covering Doom, Quake, VR, AGI, programming, games and rockets.

Tom Scott describes trying ChatGPT to fix his Gmail labels and being unsettled by how capable it was. He argues that we cannot know where we are on the technology curve, comparing it to Napster.

Victoria Warmerdam's Oscar-winning Dutch short film in which a woman fails a series of Captcha tests and is plunged into a strange new reality. It is a dark, Black Mirror-like sci-fi comedy.

Bloomberg Technology interviews Google engineer Blake Lemoine about the experiments that led him to believe LaMDA was sentient and why he was placed on administrative leave. He also raises concerns about AI ethics at Google.

Brandon Sanderson's keynote on AI-generated art, arguing that the artistic process and the journey matter more than the finished product. He explains why he rebels against generative AI in creative work.

A Munk Debate on the proposition that AI research and development poses an existential threat. Yoshua Bengio and Max Tegmark argue for it, and Melanie Mitchell and Yann LeCun argue against.

A 2023 University of Toronto conversation between Geoffrey Hinton and Fei-Fei Li on responsible AI development. They look back at the history of deep learning and ImageNet and discuss the ethics and risks of AI.

A long conversation between Eric Weinstein and Daniel Schmachtenberger on whether humanity can flourish long term on a single planet, introducing the Game A versus Game B framing. It covers catastrophic risk and alternatives to rivalrous systems.

Sal Khan of Khan Academy gives a TED talk on how AI could transform education, with a personal tutor for every student and a teaching assistant for every teacher. He demos Khanmigo, including features where the AI reasons before responding.

A podcast episode in which GPT-4 red teamer Nathan Labenz describes using the model before release, finding it human-level but not human-like, and discussing its weaknesses and worrying capabilities. It closes with speculation about GPT-5.

A 42-minute CBS interview with Geoffrey Hinton at the Vector Institute in 2023, covering the history of neural networks and the present and future of AI. He discusses AGI timelines and whether language models truly understand.

Physicist and YouTuber Angela Collier argues in this hour-long video that AI as commonly described does not really exist. She covers the limits of the tools, biased datasets, and why they should not be used to make decisions.

Lex Fridman interviews MIT physicist Max Tegmark, co-founder of the Future of Life Institute, about the case for pausing giant AI experiments and the risks of advanced AI.

Lex Fridman's long podcast interview with Yann LeCun on Meta AI, open source, the limits of LLMs, AGI and the future of AI.

Lex Fridman interviews Marcus Hutter of DeepMind about universal artificial intelligence, AIXI, Kolmogorov complexity, Solomonoff induction and the idea of intelligence as compression.

A Kurzgesagt animation on longtermism, arguing that because the future could hold trillions of people, our actions' effect on future generations may be what matters most.

Bryan Cantrill's Monktoberfest 2023 talk takes on AI doomerism, weighing the theoretical existential risks against the reality on the ground. He takes a skeptical but thoughtful view of how to balance AI's potential against its risks.

Jon Stewart on The Daily Show satirizes the AI industry's promises of a better future while it builds technology to replace workers. It mocks executives and AI hype.

Dwarkesh Patel interviews Richard Sutton, reinforcement learning pioneer, Turing Award winner and author of The Bitter Lesson. Sutton argues LLMs are a dead end because they cannot learn on the job, and that continual learning from experience will require a new architecture.

OpenAI cofounder Greg Brockman explains the design principles behind ChatGPT and demos unreleased plug-ins at TED 2023. In the follow-up, TED head Chris Anderson presses him on the timeline of development and the risks of releasing such a tool.

Stripe's John Collison interviews Anthropic CEO Dario Amodei about growth to around $5 billion ARR, model economics, agentic AI and vitalism.

Lex Fridman's long interview with OpenAI CEO Sam Altman about GPT-4, ChatGPT, and the future of AI. Topics include models as reasoning engines, AI risk, and consciousness.

A short pre-recorded talk by Rich Sutton for the World AI Conference in Shanghai arguing that succession from humanity to AI is inevitable. He lays out his view of that transition.

Sam Altman accepts the 2023 Hawking Fellowship at the Cambridge Union and speaks about OpenAI, AGI and AI safety, recorded November 1, 2023. It includes his comments on what is left for AGI and on discovering new physics.

Part two of a StrictlyVC interview with OpenAI CEO Sam Altman, focused on AI. He discusses regulation, commodification of AI, Google's reluctance to release its own models, and best- and worst-case futures.