Épisodes

  • E3: Chris Watkins on existential risk and paths to Artificial General Intelligence (AGI)
    Feb 16 2024

    How far away are we from creating AI systems whose capabilities rival our own? And would doing so pose an existential risk? In this episode, we speak to Chris Watkins, Professor of Machine Learning at Royal Holloway, University of London. Professor Watkins introduced the hugely influential Q-learning algorithm during his PhD at Cambridge, which, when combined with neural networks, ultimately led to DeepMind’s incredible Atari playing agent in 2013. He has done fascinating research in kernel methods, the role of communication in pandemic modelling, and information-theoretic analysis of evolution.

    Date of episode recording: 2023-10-17T00:00:00Z
    Duration: 01:34:20
    Language of episode: English
    Presenter: Reuben Adams
    Guests: Chris Watkins
    Producer: Reuben Adams

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    1 h et 34 min
  • E2: Lewis Griffin on how Large Language Models (LLMs) could be used for political influence
    Feb 16 2024

    Will Large Language Models (LLM) allow states to wage propaganda campaigns of unprecedented scale and persuasiveness? Or is this just another moral panic about new technology? In this episode, we talk with Lewis Griffin, Professor of Computer Vision at UCL. He has recently found some evidence that humans and LLMs can be persuaded in similar ways, and warns that it may soon be possible for states to optimise the persuasiveness of propaganda by testing it on LLMs, just like we test drugs on mice.


    Date of episode recording: 2023-10-17T00:00:00Z
    Duration: 01:23:33
    Language of episode: English
    Presenter: Reuben Adams
    Guests: Lewis Griffin
    Producer: Reuben Adams

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    1 h et 24 min
  • E1: Marc Deisenroth on AI for science and the future of work
    Feb 16 2024

    How can AI help mitigate the climate crisis? What are the advantages of simple models such as Gaussian Processes? And what will AI mean for the future of work? In this episode, we talk with Professor Marc Deisenroth, DeepMind Chair of Machine Learning and AI at UCL, and Deputy Director of the UCL Centre for Artificial Intelligence, where he leads the Statistical Machine Learning Group. His research interests centre around data-efficient machine learning, probabilistic modelling and autonomous decision-making with applications in climate/weather science and robotics.


    Date of episode recording: 2023-10-10T00:00:00Z
    Duration: 01:01:21
    Language of episode: English
    Presenter: Reuben Adams
    Guests: Professor Marc Deisenroth
    Producer: Reuben Adams

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    1 h et 1 min