August 20, 2019 Company

The Podcast: Episode 4: AI, Robot

Forget what sci-fi has told you about superintelligent robots that are uncannily human-like; the reality is more prosaic. Inside DeepMind’s robotics laboratory, Hannah explores what researchers call ‘embodied AI’: robot arms that are learning tasks like picking up plastic bricks, which humans find comparatively easy.

Discover the cutting-edge challenges of bringing AI and robotics together, and learning from scratch how to perform tasks. She also explores some of the key questions about using AI safely in the real world.

Interviewees: Software engineer Jackie Kay and research scientists Murray Shanahan, Victoria Krakovna, Raia Hadsell and Jan Leike.

Notes

Listen to this episode and subscribe to the whole series on Apple podcasts, Google podcasts, Spotify, Deezer or your favourite podcast app by searching for “DeepMind: The Podcast”.

Find out more about the themes in this episode:

DeepMind blogs on AI safety and further resources from Victoria KrakovnaThe Future of Life Institute: the risks and benefits of AIThe Wall Street Journal: Protecting Against AI’s Existential ThreatTED Talks: Max Tegmark - How to get empowered, not overpowered, by AIRoyal Society lecture series sponsored by DeepMind: You & AINick Bostrom: Superintelligence: Paths, Dangers and Strategies bookDeepMind blog: Learning from human preferencesDeepMind blog: Learning by playing - how robots can tidy up after themselvesDeepMind blog: AI safetyGeorge Zarkadakis: Move 37, or how AI can change the worldOpen AI: Learning from Human Preferences

If you know of other resources we should link to, please help other listeners by either replying to us on Twitter (#DMpodcast) or emailing us at podcast@deepmind.com. You can also use that address to send us questions or feedback on the series.

Credits:

Presenter: Hannah Fry
Editor: David Prest
Senior Producer: Louisa Field
Producers: Amy Racs, Dan Hardoon
Binaural Sound: Lucinda Mason-Brown
Music composition: Eleni Shaw (with help from Sander Dieleman and WaveNet)

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