deepfakes

Andrej Karpathy gives a one-hour general-audience introduction to large language models, covering what they are, how they are trained, comparisons to operating systems, and security challenges such as jailbreaks.

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.

Mario Zechner explains why he built pi, a minimal coding agent, out of frustration with existing agent harnesses. He also discusses how AI agents are straining open source projects and argues for slowing down.

Andrej Karpathy walks through how GPT assistants are trained, from tokenization and pretraining to supervised finetuning and RLHF, and gives practical prompting strategies and a view of the tooling ecosystem.

Nicholas Carlini of Anthropic talks at [un]prompted 2026 about how adversaries could misuse current LLMs for attacks. He shows recent models finding zero-day vulnerabilities in heavily tested software, including a SQL injection in Ghost.

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.

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.

UC Berkeley EECS colloquium by OpenAI's John Schulman on reinforcement learning from human feedback. He covers why RL helps with truthfulness, hallucination, and the limits of behavior cloning.

Daniel Stenberg's keynote at FrOSCon 2025 on AI slop attacks on the curl project, with examples of bogus AI-generated security reports. He discusses the toll on maintainers and why various countermeasures don't fit the project.

Andrej Karpathy's keynote at AI Startup School laying out software 1.0, 2.0 and 3.0, with LLMs seen as utilities, fabs and operating systems. It covers LLM quirks, partial-autonomy apps and keeping a human in the generate-and-verify loop.

Tom Gally, a former professional translator and University of Tokyo professor, discusses in March 2023 whether GPT-4 and similar models could translate literary and popular fiction. He gives his assessment of Japanese-to-English quality.

Ilya Sutskever gives a Simons Institute talk on why neural networks generalize, framing learning as finding short descriptions, like compression. It was part of the Large Language Models and Transformers program.

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.

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.

Jensen Huang's two-hour NVIDIA GTC March 2024 keynote announcing AI hardware and software advances, including Blackwell, omniverse, robotics and digital twins.

Yegor Denisov-Blanch of Stanford presents a study of nearly 100,000 developers at hundreds of companies, measuring how AI affects productivity from commit data. It finds an average boost of about 20% with wide variance by codebase, task complexity and stack.