Graduate lecture series in reinforcement learning, deep learning foundations, and frontier AI research delivered in partnership with UCL.
Complete semester courses and structured lecture series recorded at Google DeepMind.
Foundational reinforcement learning course taught by AlphaGo lead researcher David Silver: Markov Decision Processes, Bellman optimality, dynamic programming, Monte Carlo, TD learning, and function approximation.
Self-contained research seminars, public lectures, and invited colloquia.
This colloquium explores the mathematical principles and practical applications of SynthID, Google DeepMind's imperceptible watermarking technology. It details the extension of robust provenance tracking from generative AI outputs in media to the design and verification of synthetic biological sequences, ensuring integrity without functional alteration.
This colloquium with Peter Battaglia explores the application of deep learning models, such as WeatherNext 3, to global weather forecasting. It contrasts traditional numerical physics models with AI-driven approaches, focusing on their efficacy in predicting chaotic atmospheric systems and enabling probabilistic forecasts.
Professors, researchers, and invited lecturers recorded at Google DeepMind.
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