What Can the Theory of Cryptography Tell Us About AI Verification?Theory & Algos·Research Seminar·Language Models & NLP · Shafi Goldwasser · Simons Institute (UC Berkeley)Shafi GoldwasserSimons Institute (UC Berkeley)—1:02:15
The Deep Learning Revolution (Turing Award Lecture)AI & ML·Public Colloquium·Mechanistic Interpretability, Alignment & World Models · Geoffrey Hinton · Association for Computing Machinery (ACM)Geoffrey HintonAssociation for Computing Machinery (ACM)—32:28
Atomic Facts to Structured Knowledge: Rethinking Unlearning & Jailbreaking in Large Language ModelsAI & ML·Research Seminar·Mechanistic Interpretability, Alignment & World Models · Rongzhe Wei · Google Research & TechTalksRongzhe WeiGoogle Research & TechTalks—56:22
Learning Representations: A Challenge for Learning Theory, COLT 2013AI & ML·Conference Talk·Statistical Learning & Causality · Yann LeCun · New York UniversityYann LeCunNew York University—54:33
Objective-Driven AI: World Models that Learn, Remember, Reason, and PlanAI & ML·Research Seminar·Language Models & NLP · Yann LeCun · Harvard UniversityYann LeCunHarvard University—1:16:53
Computing with High-Dimensional VectorsAI & ML·Research Seminar·Deep Learning · Pentti Kanerva · Stanford UniversityPentti KanervaStanford University—59:10
Governance at the Technological Frontier: Translating AI Research into Oversight PolicyAI & ML·Research Seminar·Deep Learning · Inioluwa Deborah Raji · UC BerkeleyInioluwa Deborah RajiUC Berkeley—39:55
The Inadequacy of Offline LLM Evaluations: Personalization and Model BehaviorAI & ML·Research Seminar·Mechanistic Interpretability, Alignment & World Models · Angelina Wang · Cornell UniversityAngelina WangCornell University—31:57
How to Train a Neural Net6.7960 · Deep Learning · Lec 2·Mechanistic Interpretability, Alignment & World Models · Sara Beery · MITSara BeeryMIT—1:19:34
The Alberta Plan for AI Research: Continual Reinforcement LearningAI & ML·Research Seminar·Mechanistic Interpretability, Alignment & World Models · Richard S. Sutton · University of Alberta (Amii)Richard S. SuttonUniversity of Alberta (Amii)—58:57
On the Measure of Intelligence: Program Synthesis and Fluid AbstractionAI & ML·Public Colloquium·Statistical Learning & Causality · François Chollet · Google Research & TechTalksFrançois CholletGoogle Research & TechTalks—1:10:44
Learning Programming Abstractions for Automating Formal VerificationAI & ML·Research Seminar·Mechanistic Interpretability, Alignment & World Models · Jocelyn Qiaochu Chen · University of Alberta (Amii)Jocelyn Qiaochu ChenUniversity of Alberta (Amii)—1:03:23
What Humans Want: Models of Preference and Reward in Minds and MachinesTheory & Algos·Research Seminar·Language Models & NLP · Brian Christian · UC BerkeleyBrian ChristianUC Berkeley—1:06:50
AI Seminar: Actionable Interpretability for Language Model ReasoningAI & ML·Research Seminar·Mechanistic Interpretability, Alignment & World Models · Xi Ye · University of Alberta (Amii)Xi YeUniversity of Alberta (Amii)—57:31
AI in Science and Engineering: Proportionality in Multiwinner VotingAI & ML·Research Seminar·AI Alignment, Safety & Scalable Oversight · Edith Elkind · Northwestern UniversityEdith ElkindNorthwestern University3 ch1:23:31
Mythbusting AI: Understanding Large Language Models and Their LimitationsAI & ML·Public Colloquium·Mechanistic Interpretability, Alignment & World Models · Jim Harris · National Capital Area Skeptics (NCAS)Jim HarrisNational Capital Area Skeptics (NCAS)—1:28:36
From deepfakes to DNA: The science of watermarking AIAI & ML·Standalone Lecture·Genetics & Molecular Biology · Pushmeet Kohli · Google DeepMindPushmeet KohliGoogle DeepMind6 ch38:10
Conceptual Abstraction and Analogy in Natural and Artificial IntelligenceAI & ML·Research Seminar·Language Models & NLP · Melanie Mitchell · Santa Fe InstituteMelanie MitchellSanta Fe Institute—1:17:48
Building makemore Part 4: Becoming a Backprop Ninja (Manual Tensor Gradients)Neural Networks: Zero to Hero · Lec 5·Mechanistic Interpretability, Alignment & World Models · Andrej Karpathy · Independent / Eureka LabsAndrej KarpathyIndependent / Eureka Labs8 ch1:55:24
The Future of Creativity in the Age of AIAI & ML·Public Colloquium·Deep Learning · Daniel Susskind · Gresham CollegeDaniel SusskindGresham College13 ch45:57