Hannah wraps up the series by meeting DeepMind co-founder and CEO, Demis Hassabis. In an extended interview, Demis describes why he believes AGI is possible, how we can get there, and the problems he hopes it will solve. Along the way, he highlights the important role of consciousness and why he’s so optimistic that AI can help solve many of the world’s major challenges. As a final note, Demis shares the story of a personal meeting with Stephen Hawking to discuss the future of AI and discloses Hawking’s parting message. For questions or feedback on the series, message us on Twitter @DeepMind or email podcast@deepmind.com. Interviewee: Deepmind co-founder and CEO, Demis Hassabis CreditsPresenter: Hannah FrySeries Producer: Dan HardoonProduction support: Jill AchinekuSounds design: Emma BarnabyMusic composition: Eleni ShawSound Engineer: Nigel AppletonEditor: David PrestCommissioned by DeepMind Thank you to everyone who made this season possible! Further reading:DeepMind, The Podcast: https://deepmind.com/blog/article/welcome-to-the-deepmind-podcastDeepMind’s Demis Hassabis on its breakthrough scientific discoveries, WIRED: https://www.youtube.com/watch?v=2WRow9FqUbwRiemann hypothesis, Wikipedia: https://en.wikipedia.org/wiki/Riemann_hypothesisUsing AI to accelerate scientific discovery by Demis Hassabis, Kendrew Lecture 2021: https://www.youtube.com/watch?v=sm-VkgVX-2oProtein Folding &amp; the Next Technological Revolution by Demis Hassabis, Bloomberg: https://www.youtube.com/watch?v=vhd4ENh5ON4The Algorithm, MIT Technology Review: https://forms.technologyreview.com/newsletters/ai-the-algorithm/Machine learning resources, The Royal Society: https://royalsociety.org/topics-policy/education-skills/teacher-resources-and-opportunities/resources-for-teachers/resources-machine-learning/How to get empowered, not overpowered, by AI, TED: https://www.youtube.com/watch?v=2LRwvU6gEbA

Hannah wraps up the series by meeting DeepMind co-founder and CEO, Demis Hassabis. In an extended interview, Demis describes why he believes AGI is possible, how we can get there, and the problems he hopes it will solve. Along the way, he highlights the important role of consciousness and why he’s so optimistic that AI can help solve many of the world’s major challenges. As a final note, Demis shares the story of a personal meeting with Stephen Hawking to discuss the future of AI and discloses Hawking’s parting message. For questions or feedback on the series, message us on Twitter @DeepMind or email podcast@deepmind.com. Interviewee: Deepmind co-founder and CEO, Demis Hassabis CreditsPresenter: Hannah FrySeries Producer: Dan HardoonProduction support: Jill AchinekuSounds design: Emma BarnabyMusic composition: Eleni ShawSound Engineer: Nigel AppletonEditor: David PrestCommissioned by DeepMind Thank you to everyone who made this season possible! Further reading:DeepMind, The Podcast: <a href="https://deepmind.com/blog/article/welcome-to-the-deepmind-podcast" rel="nofollow" target="_blank">https://deepmind.com/blog/article/welcome-to-the-deepmind-podcast</a>DeepMind’s Demis Hassabis on its breakthrough scientific discoveries, WIRED: <a href="https://www.youtube.com/watch?v=2WRow9FqUbw" rel="nofollow" target="_blank">https://www.youtube.com/watch?v=2WRow9FqUbw</a>Riemann hypothesis, Wikipedia: <a href="https://en.wikipedia.org/wiki/Riemann_hypothesis" rel="nofollow" target="_blank">https://en.wikipedia.org/wiki/Riemann_hypothesis</a>Using AI to accelerate scientific discovery by Demis Hassabis, Kendrew Lecture 2021: <a href="https://www.youtube.com/watch?v=sm-VkgVX-2o" rel="nofollow" target="_blank">https://www.youtube.com/watch?v=sm-VkgVX-2o</a>Protein Folding &amp; the Next Technological Revolution by Demis Hassabis, Bloomberg: <a href="https://www.youtube.com/watch?v=vhd4ENh5ON4" rel="nofollow" target="_blank">https://www.youtube.com/watch?v=vhd4ENh5ON4</a>The Algorithm, MIT Technology Review: <a href="https://forms.technologyreview.com/newsletters/ai-the-algorithm/" rel="nofollow" target="_blank">https://forms.technologyreview.com/newsletters/ai-the-algorithm/</a>Machine learning resources, The Royal Society: <a href="https://royalsociety.org/topics-policy/education-skills/teacher-resources-and-opportunities/resources-for-teachers/resources-machine-learning/" rel="nofollow" target="_blank">https://royalsociety.org/topics-policy/education-skills/teacher-resources-and-opportunities/resources-for-teachers/resources-machine-learning/</a>How to get empowered, not overpowered, by AI, TED: <a href="https://www.youtube.com/watch?v=2LRwvU6gEbA" rel="nofollow" target="_blank">https://www.youtube.com/watch?v=2LRwvU6gEbA</a>

The promise of AI with Demis Hassabis

AI needs to benefit everyone, not just those who build it. But fulfilling this promise requires careful thought before new technologies are built and released into the world. In this episode, Hannah delves into some of the most pressing and difficult ethical and social questions surrounding AI today. She explores complex issues like racial and gender bias and the misuse of AI technologies, and hears why diversity and representation is vital for building technology that works for all. For questions or feedback on the series, message us on Twitter @DeepMind or email podcast@deepmind.com.  Interviewees: DeepMind’s Sasha Brown, William Isaac, Shakir Mohamed, Kevin Mckee &amp; Obum Ekeke CreditsPresenter: Hannah FrySeries Producer: Dan HardoonProduction support: Jill AchinekuSounds design: Emma BarnabyMusic composition: Eleni ShawSound Engineer: Nigel AppletonEditor: David PrestCommissioned by DeepMind Thank you to everyone who made this season possible!  Further reading: What a machine learning tool that turns Obama white can (and can’t) tell us about AI bias, The Verge: https://www.theverge.com/21298762/face-depixelizer-ai-machine-learning-tool-pulse-stylegan-obama-biasTuskegee Syphilis Study, Wikipedia: https://en.wikipedia.org/wiki/Tuskegee_Syphilis_StudyEthics &amp; Society, DeepMind: https://deepmind.com/about/ethics-and-societyRow over AI that 'identifies gay faces', BBC: https://www.bbc.co.uk/news/technology-41188560The Trevor Project: https://www.thetrevorproject.org/AI takes root, helping farmers identify diseased plants, Google: https://www.blog.google/technology/ai/ai-takes-root-helping-farmers-identity-diseased-plants/How Can You Use Technology to Support a Culture of Inclusion and Diversity?, myHRfuture: https://www.myhrfuture.com/blog/2019/7/16/how-can-you-use-technology-to-support-a-culture-of-inclusion-and-diversityScholarships at DeepMind: https://www.deepmind.com/scholarshipsAI, Ain’t I a Woman? Joy Buolamwini, YouTube:  https://www.youtube.com/watch?v=QxuyfWoVV98How to be Human in the Age of the Machine, Hannah Fry: https://royalsociety.org/grants-schemes-awards/book-prizes/science-book-prize/2018/hello-world/

AI needs to benefit everyone, not just those who build it. But fulfilling this promise requires careful thought before new technologies are built and released into the world. In this episode, Hannah delves into some of the most pressing and difficult ethical and social questions surrounding AI today. She explores complex issues like racial and gender bias and the misuse of AI technologies, and hears why diversity and representation is vital for building technology that works for all. For questions or feedback on the series, message us on Twitter @DeepMind or email podcast@deepmind.com.  Interviewees: DeepMind’s Sasha Brown, William Isaac, Shakir Mohamed, Kevin Mckee &amp; Obum Ekeke CreditsPresenter: Hannah FrySeries Producer: Dan HardoonProduction support: Jill AchinekuSounds design: Emma BarnabyMusic composition: Eleni ShawSound Engineer: Nigel AppletonEditor: David PrestCommissioned by DeepMind Thank you to everyone who made this season possible!  Further reading: What a machine learning tool that turns Obama white can (and can’t) tell us about AI bias, The Verge: <a href="https://www.theverge.com/21298762/face-depixelizer-ai-machine-learning-tool-pulse-stylegan-obama-bias" rel="nofollow" target="_blank">https://www.theverge.com/21298762/face-depixelizer-ai-machine-learning-tool-pulse-stylegan-obama-bias</a>Tuskegee Syphilis Study, Wikipedia: <a href="https://en.wikipedia.org/wiki/Tuskegee_Syphilis_Study" rel="nofollow" target="_blank">https://en.wikipedia.org/wiki/Tuskegee_Syphilis_Study</a>Ethics &amp; Society, DeepMind: <a href="https://deepmind.com/about/ethics-and-society" rel="nofollow" target="_blank">https://deepmind.com/about/ethics-and-society</a>Row over AI that 'identifies gay faces', BBC: <a href="https://www.bbc.co.uk/news/technology-41188560" rel="nofollow" target="_blank">https://www.bbc.co.uk/news/technology-41188560</a>The Trevor Project: <a href="https://www.thetrevorproject.org/" rel="nofollow" target="_blank">https://www.thetrevorproject.org/</a>AI takes root, helping farmers identify diseased plants, Google: <a href="https://www.blog.google/technology/ai/ai-takes-root-helping-farmers-identity-diseased-plants/" rel="nofollow" target="_blank">https://www.blog.google/technology/ai/ai-takes-root-helping-farmers-identity-diseased-plants/</a>How Can You Use Technology to Support a Culture of Inclusion and Diversity?, myHRfuture: <a href="https://www.myhrfuture.com/blog/2019/7/16/how-can-you-use-technology-to-support-a-culture-of-inclusion-and-diversity" rel="nofollow" target="_blank">https://www.myhrfuture.com/blog/2019/7/16/how-can-you-use-technology-to-support-a-culture-of-inclusion-and-diversity</a>Scholarships at DeepMind: <a href="https://www.deepmind.com/scholarships" rel="nofollow" target="_blank">https://www.deepmind.com/scholarships</a>AI, Ain’t I a Woman? Joy Buolamwini, YouTube:  <a href="https://www.youtube.com/watch?v=QxuyfWoVV98" rel="nofollow" target="_blank">https://www.youtube.com/watch?v=QxuyfWoVV98</a>How to be Human in the Age of the Machine, Hannah Fry: <a href="https://royalsociety.org/grants-schemes-awards/book-prizes/science-book-prize/2018/hello-world/" rel="nofollow" target="_blank">https://royalsociety.org/grants-schemes-awards/book-prizes/science-book-prize/2018/hello-world/</a>

Fair for all

AI doesn’t just exist in the lab, it’s already solving a range of problems in the real world. In this episode, Hannah encounters a realistic recreation of her voice by WaveNet, the voice synthesising system that powers the Google Assistant and helps people with speech difficulties and illnesses regain their voices. Hannah also discovers how ‘deepfake’ technology can be used to improve weather forecasting and how DeepMind researchers are collaborating with Liverpool Football Club, aiming to take sports to the next level. For questions or feedback on the series, message us on Twitter @DeepMind or email podcast@deepmind.com.  Interviewees: DeepMind’s Demis Hassabis, Raia Hadsell, Karl Tuyls, Zach Gleicher &amp; Jackson Broshear; Niall Robinson of the UK Met Office CreditsPresenter: Hannah FrySeries Producer: Dan HardoonProduction support: Jill AchinekuSounds design: Emma BarnabyMusic composition: Eleni ShawSound Engineer: Nigel AppletonEditor: David PrestCommissioned by DeepMind Thank you to everyone who made this season possible!  Further reading: A generative model for raw audio, DeepMind: https://deepmind.com/blog/article/wavenet-generative-model-raw-audioWaveNet case study, DeepMind: https://deepmind.com/research/case-studies/wavenetUsing WaveNet technology to reunite speech-impaired users with their original voices, DeepMind:| https://deepmind.com/blog/article/Using-WaveNet-technology-to-reunite-speech-impaired-users-with-their-original-voicesProject Euphonia, Google Research: https://sites.research.google/euphonia/about/Nowcasting the next hour of rain, DeepMind: https://deepmind.com/blog/article/nowcastingNow DeepMind is using AI to transform football, WIRED: https://www.wired.co.uk/article/deepmind-football-liverpool-aiAdvancing sports analytics through AI, DeepMind: https://deepmind.com/blog/article/advancing-sports-analytics-through-aiMetOffice, BBC: https://www.metoffice.gov.uk/The village ‘washed on to the map’, BBC: https://www.bbc.co.uk/news/uk-england-cornwall-28523053Michael Fish got the storm of 1987 wrong, Sky News: https://news.sky.com/story/michael-fish-got-the-storm-of-1987-wrong-but-modern-supercomputers-may-have-missed-it-too-11076659#:~:text=In%20a%20lunchtime%20broadcast%20on,%2C%22%20he%20confidently%20told%20viewers.

AI doesn’t just exist in the lab, it’s already solving a range of problems in the real world. In this episode, Hannah encounters a realistic recreation of her voice by WaveNet, the voice synthesising system that powers the Google Assistant and helps people with speech difficulties and illnesses regain their voices. Hannah also discovers how ‘deepfake’ technology can be used to improve weather forecasting and how DeepMind researchers are collaborating with Liverpool Football Club, aiming to take sports to the next level. For questions or feedback on the series, message us on Twitter @DeepMind or email podcast@deepmind.com.  Interviewees: DeepMind’s Demis Hassabis, Raia Hadsell, Karl Tuyls, Zach Gleicher &amp; Jackson Broshear; Niall Robinson of the UK Met Office CreditsPresenter: Hannah FrySeries Producer: Dan HardoonProduction support: Jill AchinekuSounds design: Emma BarnabyMusic composition: Eleni ShawSound Engineer: Nigel AppletonEditor: David PrestCommissioned by DeepMind Thank you to everyone who made this season possible!  Further reading: A generative model for raw audio, DeepMind: <a href="https://deepmind.com/blog/article/wavenet-generative-model-raw-audio" rel="nofollow" target="_blank">https://deepmind.com/blog/article/wavenet-generative-model-raw-audio</a>WaveNet case study, DeepMind: <a href="https://deepmind.com/research/case-studies/wavenet" rel="nofollow" target="_blank">https://deepmind.com/research/case-studies/wavenet</a>Using WaveNet technology to reunite speech-impaired users with their original voices, DeepMind:| <a href="https://deepmind.com/blog/article/Using-WaveNet-technology-to-reunite-speech-impaired-users-with-their-original-voices" rel="nofollow" target="_blank">https://deepmind.com/blog/article/Using-WaveNet-technology-to-reunite-speech-impaired-users-with-their-original-voices</a>Project Euphonia, Google Research: <a href="https://sites.research.google/euphonia/about/" rel="nofollow" target="_blank">https://sites.research.google/euphonia/about/</a>Nowcasting the next hour of rain, DeepMind: <a href="https://deepmind.com/blog/article/nowcasting" rel="nofollow" target="_blank">https://deepmind.com/blog/article/nowcasting</a>Now DeepMind is using AI to transform football, WIRED: <a href="https://www.wired.co.uk/article/deepmind-football-liverpool-ai" rel="nofollow" target="_blank">https://www.wired.co.uk/article/deepmind-football-liverpool-ai</a>Advancing sports analytics through AI, DeepMind: <a href="https://deepmind.com/blog/article/advancing-sports-analytics-through-ai" rel="nofollow" target="_blank">https://deepmind.com/blog/article/advancing-sports-analytics-through-ai</a>MetOffice, BBC: <a href="https://www.metoffice.gov.uk/" rel="nofollow" target="_blank">https://www.metoffice.gov.uk/</a>The village ‘washed on to the map’, BBC: <a href="https://www.bbc.co.uk/news/uk-england-cornwall-28523053" rel="nofollow" target="_blank">https://www.bbc.co.uk/news/uk-england-cornwall-28523053</a>Michael Fish got the storm of 1987 wrong, Sky News: <a href="https://news.sky.com/story/michael-fish-got-the-storm-of-1987-wrong-but-modern-supercomputers-may-have-missed-it-too-11076659#:~:text=In%20a%20lunchtime%20broadcast%20on,%2C%22%20he%20confidently%20told%20viewers" rel="nofollow" target="_blank">https://news.sky.com/story/michael-fish-got-the-storm-of-1987-wrong-but-modern-supercomputers-may-have-missed-it-too-11076659#:~:text=In%20a%20lunchtime%20broadcast%20on,%2C%22%20he%20confidently%20told%20viewers</a>.

Me, myself and AI

Step inside DeepMind's laboratories and you'll find researchers studying DNA to understand the mysteries of life, seeking new ways to use nuclear energy, or putting AI to the test in mind-bending areas of maths. In this episode, Hannah meets Pushmeet Kohli, the head of science at DeepMind, to understand how AI is accelerating scientific progress. Listeners also join Hannah on a [virtual] safari in the Serengeti in East Africa to find out how researchers are using AI to conserve wildlife in one of the world’s most spectacular ecosystems.  For questions or feedback on the series, message us on Twitter @DeepMind or email podcast@deepmind.com.  Interviewees: DeepMind’s Demis Hassabis, Pushmeet Kohli &amp; Sarah Jane Dunn; Meredith Palmer of the Princeton University CreditsPresenter: Hannah FrySeries Producer: Dan HardoonProduction support: Jill AchinekuSounds design: Emma BarnabyMusic composition: Eleni ShawSound Engineer: Nigel AppletonEditor: David PrestCommissioned by DeepMind Thank you to everyone who made this season possible!  Further reading:Using AI for scientific discovery, DeepMind: https://deepmind.com/blog/article/AlphaFold-Using-AI-for-scientific-discoveryDeepMind’s Demis Hassabis on its breakthrough scientific discoveries, WIRED: https://www.youtube.com/watch?v=2WRow9FqUbwThe AI revolution in scientific research, The Royal Society: https://royalsociety.org/-/media/policy/projects/ai-and-society/AI-revolution-in-science.pdfDOE Explains...Tokamaks, Office of Science: https://www.energy.gov/science/doe-explainstokamaksHow AI Accidentally Learned Ecology by Playing StarCraft, Discover: https://www.discovermagazine.com/technology/how-ai-accidentally-learned-ecology-by-playing-starcraftGoogle AI can identify wildlife from trap-camera footage, VentureBeat:https://venturebeat.com/2019/12/17/googles-ai-can-identify-wildlife-from-trap-camera-footage-with-up-to-98-6-accuracy/Snapshot Serengeti, Zooniverse:https://www.zooniverse.org/projects/zooniverse/snapshot-serengetiThe Human Genome Project, National Human Genome Research Institute: https://www.genome.gov/human-genome-projectExploring the beauty of pure mathematics in novel ways, DeepMind: https://deepmind.com/blog/article/exploring-the-beauty-of-pure-mathematics-in-novel-waysPredicting gene expression with AI, DeepMind: https://deepmind.com/blog/article/enformerUsing machine learning to accelerate ecological research, DeepMind: https://deepmind.com/blog/article/using-machine-learning-to-accelerate-ecological-researchAccelerating fusion science through learned plasma control, DeepMind: https://deepmind.com/blog/article/Accelerating-fusion-science-through-learned-plasma-controlSimulating matter on the quantum scale with AI, DeepMind: https://deepmind.com/blog/article/Simulating-matter-on-the-quantum-scale-with-AIHow AI is helping the natural sciences, Nature: https://www.nature.com/articles/d41586-021-02762-6Inside DeepMind's epic mission to solve science's trickiest problem, WIRED: https://www.wired.co.uk/article/deepmind-protein-foldingHow Artificial Intelligence Is Changing Science, Quanta: https://www.quantamagazine.org/how-artificial-intelligence-is-changing-science-20190311/

Step inside DeepMind's laboratories and you'll find researchers studying DNA to understand the mysteries of life, seeking new ways to use nuclear energy, or putting AI to the test in mind-bending areas of maths. In this episode, Hannah meets Pushmeet Kohli, the head of science at DeepMind, to understand how AI is accelerating scientific progress. Listeners also join Hannah on a [virtual] safari in the Serengeti in East Africa to find out how researchers are using AI to conserve wildlife in one of the world’s most spectacular ecosystems.  For questions or feedback on the series, message us on Twitter @DeepMind or email podcast@deepmind.com.  Interviewees: DeepMind’s Demis Hassabis, Pushmeet Kohli &amp; Sarah Jane Dunn; Meredith Palmer of the Princeton University CreditsPresenter: Hannah FrySeries Producer: Dan HardoonProduction support: Jill AchinekuSounds design: Emma BarnabyMusic composition: Eleni ShawSound Engineer: Nigel AppletonEditor: David PrestCommissioned by DeepMind Thank you to everyone who made this season possible!  Further reading:Using AI for scientific discovery, DeepMind: <a href="https://deepmind.com/blog/article/AlphaFold-Using-AI-for-scientific-discovery" rel="nofollow" target="_blank">https://deepmind.com/blog/article/AlphaFold-Using-AI-for-scientific-discovery</a>DeepMind’s Demis Hassabis on its breakthrough scientific discoveries, WIRED: <a href="https://www.youtube.com/watch?v=2WRow9FqUbw" rel="nofollow" target="_blank">https://www.youtube.com/watch?v=2WRow9FqUbw</a>The AI revolution in scientific research, The Royal Society: <a href="https://royalsociety.org/-/media/policy/projects/ai-and-society/AI-revolution-in-science.pdf" rel="nofollow" target="_blank">https://royalsociety.org/-/media/policy/projects/ai-and-society/AI-revolution-in-science.pdf</a>DOE Explains...Tokamaks, Office of Science: <a href="https://www.energy.gov/science/doe-explainstokamaks" rel="nofollow" target="_blank">https://www.energy.gov/science/doe-explainstokamaks</a>How AI Accidentally Learned Ecology by Playing StarCraft, Discover: <a href="https://www.discovermagazine.com/technology/how-ai-accidentally-learned-ecology-by-playing-starcraft" rel="nofollow" target="_blank">https://www.discovermagazine.com/technology/how-ai-accidentally-learned-ecology-by-playing-starcraft</a>Google AI can identify wildlife from trap-camera footage, VentureBeat: <a href="https://venturebeat.com/2019/12/17/googles-ai-can-identify-wildlife-from-trap-camera-footage-with-up-to-98-6-accuracy/" rel="nofollow" target="_blank">https://venturebeat.com/2019/12/17/googles-ai-can-identify-wildlife-from-trap-camera-footage-with-up-to-98-6-accuracy/</a>Snapshot Serengeti, Zooniverse: <a href="https://www.zooniverse.org/projects/zooniverse/snapshot-serengeti" rel="nofollow" target="_blank">https://www.zooniverse.org/projects/zooniverse/snapshot-serengeti</a>The Human Genome Project, National Human Genome Research Institute: <a href="https://www.genome.gov/human-genome-project" rel="nofollow" target="_blank">https://www.genome.gov/human-genome-project</a>Exploring the beauty of pure mathematics in novel ways, DeepMind: <a href="https://deepmind.com/blog/article/exploring-the-beauty-of-pure-mathematics-in-novel-ways" rel="nofollow" target="_blank">https://deepmind.com/blog/article/exploring-the-beauty-of-pure-mathematics-in-novel-ways</a>Predicting gene expression with AI, DeepMind: <a href="https://deepmind.com/blog/article/enformer" rel="nofollow" target="_blank">https://deepmind.com/blog/article/enformer</a>Using machine learning to accelerate ecological research, DeepMind: <a href="https://deepmind.com/blog/article/using-machine-learning-to-accelerate-ecological-research" rel="nofollow" target="_blank">https://deepmind.com/blog/article/using-machine-learning-to-accelerate-ecological-research</a>Accelerating fusion science through learned plasma control, DeepMind: <a href="https://deepmind.com/blog/article/Accelerating-fusion-science-through-learned-plasma-control" rel="nofollow" target="_blank">https://deepmind.com/blog/article/Accelerating-fusion-science-through-learned-plasma-control</a>Simulating matter on the quantum scale with AI, DeepMind: <a href="https://deepmind.com/blog/article/Simulating-matter-on-the-quantum-scale-with-AI" rel="nofollow" target="_blank">https://deepmind.com/blog/article/Simulating-matter-on-the-quantum-scale-with-AI</a>How AI is helping the natural sciences, Nature: <a href="https://www.nature.com/articles/d41586-021-02762-6" rel="nofollow" target="_blank">https://www.nature.com/articles/d41586-021-02762-6</a>Inside DeepMind's epic mission to solve science's trickiest problem, WIRED: <a href="https://www.wired.co.uk/article/deepmind-protein-folding" rel="nofollow" target="_blank">https://www.wired.co.uk/article/deepmind-protein-folding</a>How Artificial Intelligence Is Changing Science, Quanta: <a href="https://www.quantamagazine.org/how-artificial-intelligence-is-changing-science-20190311/" rel="nofollow" target="_blank">https://www.quantamagazine.org/how-artificial-intelligence-is-changing-science-20190311/</a>

AI for science

Hannah meets DeepMind co-founder and chief scientist Shane Legg, the man who coined the phrase ‘artificial general intelligence’, and explores how it might be built. Why does Shane think AGI is possible? When will it be realised? And what could it look like? Hannah also explores a simple theory of using trial and error to reach AGI and takes a deep dive into MuZero, an AI system which mastered complex board games from chess to Go, and is now generalising to solve a range of important tasks in the real world. For questions or feedback on the series, message us on Twitter @DeepMind or email podcast@deepmind.com.  Interviewees: DeepMind’s Shane Legg, Doina Precup, Dave Silver &amp; Jackson Broshear CreditsPresenter: Hannah FrySeries Producer: Dan HardoonProduction support: Jill AchinekuSounds design: Emma BarnabyMusic composition: Eleni ShawSound Engineer: Nigel AppletonEditor: David PrestCommissioned by DeepMind Thank you to everyone who made this season possible!  Further reading: Real-world challenges for AGI, DeepMind: https://deepmind.com/blog/article/real-world-challenges-for-agiAn executive primer on artificial general intelligence, McKinsey: https://www.mckinsey.com/business-functions/operations/our-insights/an-executive-primer-on-artificial-general-intelligenceMastering Go, chess, shogi and Atari without rules, DeepMind: https://deepmind.com/blog/article/muzero-mastering-go-chess-shogi-and-atari-without-rulesWhat is AGI?, Medium: https://medium.com/intuitionmachine/what-is-agi-99cdb671c88eA Definition of Machine Intelligence by Shane Legg, arXiv: https://arxiv.org/abs/0712.3329Reward is enough by David Silver, ScienceDirect: https://www.sciencedirect.com/science/article/pii/S0004370221000862

Hannah meets DeepMind co-founder and chief scientist Shane Legg, the man who coined the phrase ‘artificial general intelligence’, and explores how it might be built. Why does Shane think AGI is possible? When will it be realised? And what could it look like? Hannah also explores a simple theory of using trial and error to reach AGI and takes a deep dive into MuZero, an AI system which mastered complex board games from chess to Go, and is now generalising to solve a range of important tasks in the real world. For questions or feedback on the series, message us on Twitter @DeepMind or email podcast@deepmind.com.  Interviewees: DeepMind’s Shane Legg, Doina Precup, Dave Silver &amp; Jackson Broshear CreditsPresenter: Hannah FrySeries Producer: Dan HardoonProduction support: Jill AchinekuSounds design: Emma BarnabyMusic composition: Eleni ShawSound Engineer: Nigel AppletonEditor: David PrestCommissioned by DeepMind Thank you to everyone who made this season possible!  Further reading: Real-world challenges for AGI, DeepMind: <a href="https://deepmind.com/blog/article/real-world-challenges-for-agi" rel="nofollow" target="_blank">https://deepmind.com/blog/article/real-world-challenges-for-agi</a>An executive primer on artificial general intelligence, McKinsey: <a href="https://www.mckinsey.com/business-functions/operations/our-insights/an-executive-primer-on-artificial-general-intelligence" rel="nofollow" target="_blank">https://www.mckinsey.com/business-functions/operations/our-insights/an-executive-primer-on-artificial-general-intelligence</a>Mastering Go, chess, shogi and Atari without rules, DeepMind: <a href="https://deepmind.com/blog/article/muzero-mastering-go-chess-shogi-and-atari-without-rules" rel="nofollow" target="_blank">https://deepmind.com/blog/article/muzero-mastering-go-chess-shogi-and-atari-without-rules</a>What is AGI?, Medium: <a href="https://medium.com/intuitionmachine/what-is-agi-99cdb671c88e" rel="nofollow" target="_blank">https://medium.com/intuitionmachine/what-is-agi-99cdb671c88e</a>A Definition of Machine Intelligence by Shane Legg, arXiv: <a href="https://arxiv.org/abs/0712.3329" rel="nofollow" target="_blank">https://arxiv.org/abs/0712.3329</a>Reward is enough by David Silver, ScienceDirect: <a href="https://www.sciencedirect.com/science/article/pii/S0004370221000862" rel="nofollow" target="_blank">https://www.sciencedirect.com/science/article/pii/S0004370221000862</a>

The road to AGI

Do you need a body to have intelligence? And can one exist without the other? Hannah takes listeners behind the scenes of DeepMind's robotics lab in London where she meets robots that are trying to independently learn new skills, and explores why physical intelligence is a necessary part of intelligence. Along the way, she finds out how researchers trained their robots at home during lockdown, uncovers why so many robotics demonstrations are faking it, and what it takes to train a robotic football team.  For questions or feedback on the series, message us on Twitter @DeepMind or email podcast@deepmind.com.  Interviewees: DeepMind’s Raia Hadsell, Viorica Patraucean, Jan Humplik, Akhil Raju &amp; Doina Precup CreditsPresenter: Hannah FrySeries Producer: Dan HardoonProduction support: Jill AchinekuSounds design: Emma BarnabyMusic composition: Eleni ShawSound Engineer: Nigel AppletonEditor: David PrestCommissioned by DeepMind Thank you to everyone who made this season possible!  Further reading: Stacking our way to more general robots, DeepMind: https://deepmind.com/blog/article/stacking-our-way-to-more-general-robotsResearchers Propose Physical AI As Key To Lifelike Robots, Forbes: ​​https://www.forbes.com/sites/simonchandler/2020/11/11/researchers-propose-physical-ai-as-key-to-lifelike-robots/The robots going where no human can, BBC: https://www.bbc.co.uk/news/av/technology-41584738The Robot Assault On Fukushima, WIRED: https://www.wired.com/story/fukushima-robot-cleanup/Leaps, Bounds, and Backflips, Boston Dynamics: http://blog.bostondynamics.com/atlas-leaps-bounds-and-backflipsNow DeepMind is using AI to transform football, WIRED: https://www.wired.co.uk/article/deepmind-football-liverpool-ai

Do you need a body to have intelligence? And can one exist without the other? Hannah takes listeners behind the scenes of DeepMind's robotics lab in London where she meets robots that are trying to independently learn new skills, and explores why physical intelligence is a necessary part of intelligence. Along the way, she finds out how researchers trained their robots at home during lockdown, uncovers why so many robotics demonstrations are faking it, and what it takes to train a robotic football team.  For questions or feedback on the series, message us on Twitter @DeepMind or email podcast@deepmind.com.  Interviewees: DeepMind’s Raia Hadsell, Viorica Patraucean, Jan Humplik, Akhil Raju &amp; Doina Precup CreditsPresenter: Hannah FrySeries Producer: Dan HardoonProduction support: Jill AchinekuSounds design: Emma BarnabyMusic composition: Eleni ShawSound Engineer: Nigel AppletonEditor: David PrestCommissioned by DeepMind Thank you to everyone who made this season possible!  Further reading: Stacking our way to more general robots, DeepMind: <a href="https://deepmind.com/blog/article/stacking-our-way-to-more-general-robots" rel="nofollow" target="_blank">https://deepmind.com/blog/article/stacking-our-way-to-more-general-robots</a>Researchers Propose Physical AI As Key To Lifelike Robots, Forbes: ​​<a href="https://www.forbes.com/sites/simonchandler/2020/11/11/researchers-propose-physical-ai-as-key-to-lifelike-robots/" rel="nofollow" target="_blank">https://www.forbes.com/sites/simonchandler/2020/11/11/researchers-propose-physical-ai-as-key-to-lifelike-robots/</a>The robots going where no human can, BBC: <a href="https://www.bbc.co.uk/news/av/technology-41584738" rel="nofollow" target="_blank">https://www.bbc.co.uk/news/av/technology-41584738</a>The Robot Assault On Fukushima, WIRED: <a href="https://www.wired.com/story/fukushima-robot-cleanup/" rel="nofollow" target="_blank">https://www.wired.com/story/fukushima-robot-cleanup/</a>Leaps, Bounds, and Backflips, Boston Dynamics: <a href="http://blog.bostondynamics.com/atlas-leaps-bounds-and-backflips" rel="nofollow" target="_blank">http://blog.bostondynamics.com/atlas-leaps-bounds-and-backflips</a>Now DeepMind is using AI to transform football, WIRED: <a href="https://www.wired.co.uk/article/deepmind-football-liverpool-ai" rel="nofollow" target="_blank">https://www.wired.co.uk/article/deepmind-football-liverpool-ai</a>

Let's get physical

Cooperation is at the heart of our society. Inventing the railway, giving birth to the Renaissance, and creating the Covid-19 vaccine all required people to combine efforts. But cooperation is so much more. It governs our education systems, healthcare, and food production. In this episode, Hannah meets the researchers working on cooperative AI, and hears about their work and influences from the famous American psychologist - and pigeon trainer -  BF Skinner to the strategic board game Diplomacy. For questions or feedback on the series, message us on Twitter @DeepMind or email podcast@deepmind.com Interviewees: DeepMind’s Thore Graepel, Kevin Mckee, Doina Precup &amp; Laura Weidinger CreditsPresenter: Hannah FrySeries Producer: Dan HardoonProduction support: Jill AchinekuSounds design: Emma BarnabyMusic composition: Eleni ShawSound Engineer: Nigel AppletonEditor: David PrestCommissioned by DeepMind Thank you to everyone who made this season possible!  Further reading: Machines must learn to find common ground, Nature: https://www.nature.com/articles/d41586-021-01170-0Introduction to Reinforcement Learning, DeepMind: https://www.youtube.com/watch?v=2pWv7GOvuf0B.F. Skinner, Wikipedia: https://en.wikipedia.org/wiki/B._F._SkinnerThe Tragedy of the Commons, Wikipedia: https://en.wikipedia.org/wiki/Tragedy_of_the_commonsStaving Off The Ultimate Tragedy Of The Commons, Forbes: https://www.forbes.com/sites/georgebradt/2021/11/02/staving-off-the-ultimate-tragedy-of-the-commons-by-making-better-complex-decisions-cooperatively-in-glasgow/Understanding Agent Cooperation, DeepMind: https://deepmind.com/blog/article/understanding-agent-cooperationThe emergence of complex cooperative agents, DeepMind: https://deepmind.com/blog/article/capture-the-flag-science

Cooperation is at the heart of our society. Inventing the railway, giving birth to the Renaissance, and creating the Covid-19 vaccine all required people to combine efforts. But cooperation is so much more. It governs our education systems, healthcare, and food production. In this episode, Hannah meets the researchers working on cooperative AI, and hears about their work and influences from the famous American psychologist - and pigeon trainer -  BF Skinner to the strategic board game Diplomacy. For questions or feedback on the series, message us on Twitter @DeepMind or email podcast@deepmind.com Interviewees: DeepMind’s Thore Graepel, Kevin Mckee, Doina Precup &amp; Laura Weidinger CreditsPresenter: Hannah FrySeries Producer: Dan HardoonProduction support: Jill AchinekuSounds design: Emma BarnabyMusic composition: Eleni ShawSound Engineer: Nigel AppletonEditor: David PrestCommissioned by DeepMind Thank you to everyone who made this season possible!  Further reading: Machines must learn to find common ground, Nature: <a href="https://www.nature.com/articles/d41586-021-01170-0" rel="nofollow" target="_blank">https://www.nature.com/articles/d41586-021-01170-0</a>Introduction to Reinforcement Learning, DeepMind: <a href="https://www.youtube.com/watch?v=2pWv7GOvuf0" rel="nofollow" target="_blank">https://www.youtube.com/watch?v=2pWv7GOvuf0</a>B.F. Skinner, Wikipedia: <a href="https://en.wikipedia.org/wiki/B._F._Skinner" rel="nofollow" target="_blank">https://en.wikipedia.org/wiki/B._F._Skinner</a>The Tragedy of the Commons, Wikipedia: <a href="https://en.wikipedia.org/wiki/Tragedy_of_the_commons" rel="nofollow" target="_blank">https://en.wikipedia.org/wiki/Tragedy_of_the_commons</a>Staving Off The Ultimate Tragedy Of The Commons, Forbes: <a href="https://www.forbes.com/sites/georgebradt/2021/11/02/staving-off-the-ultimate-tragedy-of-the-commons-by-making-better-complex-decisions-cooperatively-in-glasgow/" rel="nofollow" target="_blank">https://www.forbes.com/sites/georgebradt/2021/11/02/staving-off-the-ultimate-tragedy-of-the-commons-by-making-better-complex-decisions-cooperatively-in-glasgow/</a>Understanding Agent Cooperation, DeepMind: <a href="https://deepmind.com/blog/article/understanding-agent-cooperation" rel="nofollow" target="_blank">https://deepmind.com/blog/article/understanding-agent-cooperation</a>The emergence of complex cooperative agents, DeepMind: <a href="https://deepmind.com/blog/article/capture-the-flag-science" rel="nofollow" target="_blank">https://deepmind.com/blog/article/capture-the-flag-science</a>

Better together

In December 2019, DeepMind’s AI system, AlphaFold, solved a 50-year-old grand challenge in biology, known as the protein-folding problem. A headline in the journal Nature read, “It will change everything” and the President of the UK's Royal Society called it a “stunning advance [that arrived] decades before many in the field would have predicted”. In this episode, Hannah uncovers the inside story of AlphaFold from the people who made it happen and finds out how it could help transform the future of healthcare and medicine.For questions or feedback on the series, message us on Twitter @DeepMind or email podcast@deepmind.com. Interviewees: DeepMind’s Demis Hassabis, John Jumper, Kathryn Tunyasunakool and Sasha Brown; Charles Mowbray and Monique Wasuna of the Drugs for Neglected Diseases initiative (DNDi]) &amp; John McGeehan of the Centre for Enzyme Innovation at the University of Portsmouth CreditsPresenter: Hannah FrySeries Producer: Dan HardoonProduction support: Jill AchinekuSounds design: Emma BarnabyMusic composition: Eleni ShawSound Engineer: Nigel AppletonEditor: David PrestCommissioned by DeepMind Thank you to everyone who made this season possible!  Further reading: AlphaFold blog, DeepMind: https://deepmind.com/blog/article/alphafold-a-solution-to-a-50-year-old-grand-challenge-in-biologyAlphaFold case study, DeepMind: https://deepmind.com/research/case-studies/alphafoldIt will change everything, Nature: https://www.nature.com/articles/d41586-020-03348-4AlphaFold Is The Most Important Achievement In AI—Ever, Forbes: https://www.forbes.com/sites/robtoews/2021/10/03/alphafold-is-the-most-important-achievement-in-ai-ever/?sh=359278426e0aBacteria found to eat PET plastics, NewScientist: https://www.newscientist.com/article/2080279-bacteria-found-to-eat-pet-plastics-could-help-do-the-recycling/Protein Structure Prediction Center: https://predictioncenter.org/An interview with Professor John McGeehan, BBSRC: https://bbsrc.ukri.org/news/features/enzyme-science/an-interview-with-professor-john-mcgeehan/John McGeehan profile, University of Portsmouth: https://researchportal.port.ac.uk/en/persons/john-mcgeehanDrugs for Neglected Diseases initiative (DNDi): https://dndi.org/A doctor’s dream, DNDi: https://www.youtube.com/watch?v=Tk31iucWYdEThe Curious Cases of Rutherford and Fry, BBC: https://www.bbc.co.uk/programmes/b07dx75g/episodes/downloadsHannah Fry: https://hannahfry.co.uk/

In December 2019, DeepMind’s AI system, AlphaFold, solved a 50-year-old grand challenge in biology, known as the protein-folding problem. A headline in the journal Nature read, “It will change everything” and the President of the UK's Royal Society called it a “stunning advance [that arrived] decades before many in the field would have predicted”. In this episode, Hannah uncovers the inside story of AlphaFold from the people who made it happen and finds out how it could help transform the future of healthcare and medicine.For questions or feedback on the series, message us on <a href="https://twitter.com/deepmind" rel="nofollow" target="_blank">Twitter @DeepMind</a> or email podcast@deepmind.com. Interviewees: DeepMind’s Demis Hassabis, John Jumper, Kathryn Tunyasunakool and Sasha Brown; Charles Mowbray and Monique Wasuna of the Drugs for Neglected Diseases initiative (DNDi]) &amp; John McGeehan of the Centre for Enzyme Innovation at the University of Portsmouth CreditsPresenter: Hannah FrySeries Producer: Dan HardoonProduction support: Jill AchinekuSounds design: Emma BarnabyMusic composition: Eleni ShawSound Engineer: Nigel AppletonEditor: David PrestCommissioned by DeepMind Thank you to everyone who made this season possible!  Further reading: AlphaFold blog, DeepMind: <a href="https://deepmind.com/blog/article/alphafold-a-solution-to-a-50-year-old-grand-challenge-in-biology" rel="nofollow" target="_blank">https://deepmind.com/blog/article/alphafold-a-solution-to-a-50-year-old-grand-challenge-in-biology</a>AlphaFold case study, DeepMind: <a href="https://deepmind.com/research/case-studies/alphafold" rel="nofollow" target="_blank">https://deepmind.com/research/case-studies/alphafold</a>It will change everything, Nature: <a href="https://www.nature.com/articles/d41586-020-03348-4" rel="nofollow" target="_blank">https://www.nature.com/articles/d41586-020-03348-4</a>AlphaFold Is The Most Important Achievement In AI—Ever, Forbes: <a href="https://www.forbes.com/sites/robtoews/2021/10/03/alphafold-is-the-most-important-achievement-in-ai-ever/?sh=359278426e0a" rel="nofollow" target="_blank">https://www.forbes.com/sites/robtoews/2021/10/03/alphafold-is-the-most-important-achievement-in-ai-ever/?sh=359278426e0a</a>Bacteria found to eat PET plastics, NewScientist: <a href="https://www.newscientist.com/article/2080279-bacteria-found-to-eat-pet-plastics-could-help-do-the-recycling/" rel="nofollow" target="_blank">https://www.newscientist.com/article/2080279-bacteria-found-to-eat-pet-plastics-could-help-do-the-recycling</a>/Protein Structure Prediction Center: <a href="https://predictioncenter.org/" rel="nofollow" target="_blank">https://predictioncenter.org/</a>An interview with Professor John McGeehan, BBSRC: <a href="https://bbsrc.ukri.org/news/features/enzyme-science/an-interview-with-professor-john-mcgeehan/" rel="nofollow" target="_blank">https://bbsrc.ukri.org/news/features/enzyme-science/an-interview-with-professor-john-mcgeehan/</a>John McGeehan profile, University of Portsmouth: <a href="https://researchportal.port.ac.uk/en/persons/john-mcgeehan" rel="nofollow" target="_blank">https://researchportal.port.ac.uk/en/persons/john-mcgeehan</a>Drugs for Neglected Diseases initiative (DNDi): <a href="https://dndi.org/" rel="nofollow" target="_blank">https://dndi.org/</a>A doctor’s dream, DNDi: <a href="https://www.youtube.com/watch?v=Tk31iucWYdE" rel="nofollow" target="_blank">https://www.youtube.com/watch?v=Tk31iucWYdE</a>The Curious Cases of Rutherford and Fry, BBC: <a href="https://www.bbc.co.uk/programmes/b07dx75g/episodes/downloads" rel="nofollow" target="_blank">https://www.bbc.co.uk/programmes/b07dx75g/episodes/downloads</a>Hannah Fry: <a href="https://hannahfry.co.uk/" rel="nofollow" target="_blank">https://hannahfry.co.uk/</a>

A breakthrough unfolds

Hannah explores the potential of language models, the questions they raise, and if teaching a computer about language is enough to create artificial general intelligence (AGI). Beyond helping us communicate ideas, language plays a crucial role in memory, cooperation, and thinking – which is why AI researchers have long aimed to communicate with computers using natural language. Recently, there has been extraordinary progress using large-language models (LLM), which learn how to speak by processing huge amounts of data from the internet. The results can be very convincing, but pose significant ethical challenges.  For questions or feedback on the series, message us on Twitter @DeepMind or email podcast@deepmind.com.  Interviewees: DeepMind’s Geoffrey Irving, Chris Dyer, Angeliki Lazaridou, Lisa-Anne Hendriks &amp; Laura Weidinger  CreditsPresenter: Hannah FrySeries Producer: Dan HardoonProduction support: Jill AchinekuSounds design: Emma BarnabyMusic composition: Eleni ShawSound Engineer: Nigel AppletonEditor: David PrestCommissioned by DeepMind Thank you to everyone who made this season possible!  Further reading: GPT-3 Powers the Next Generation of Apps, OpenAI: https://openai.com/blog/gpt-3-apps/https://web.stanford.edu/class/linguist238/p36-weizenabaum.pdfNever Mind the Computer 1983 about the ELIZA program, BBC: https://www.bbc.co.uk/programmes/p023kpf8How Large Language Models Will Transform Science, Society, and AI, Stanford University: https://hai.stanford.edu/news/how-large-language-models-will-transform-science-society-and-aiChallenges in Detoxifying Language Models, DeepMind: https://deepmind.com/research/publications/2021/Challenges-in-Detoxifying-Language-ModelsExtending Machine Language Models toward Human-Level Language Understanding, DeepMind: https://deepmind.com/research/publications/2020/Extending-Machine-Language-Models-toward-Human-Level-Language-UnderstandingLanguage modelling at scale, DeepMind: https://deepmind.com/blog/article/language-modelling-at-scaleArtificial general intelligence, Technology Review: https://www.technologyreview.com/2020/10/15/1010461/artificial-general-intelligence-robots-ai-agi-deepmind-google-openai/A Definition of Machine Intelligence by Shane Legg, arXiv: https://arxiv.org/abs/0712.3329Stuart Russell - Living With Artificial Intelligence, BBC: https://www.bbc.co.uk/programmes/m001216k/episodes/player

Hannah explores the potential of language models, the questions they raise, and if teaching a computer about language is enough to create artificial general intelligence (AGI). Beyond helping us communicate ideas, language plays a crucial role in memory, cooperation, and thinking – which is why AI researchers have long aimed to communicate with computers using natural language. Recently, there has been extraordinary progress using large-language models (LLM), which learn how to speak by processing huge amounts of data from the internet. The results can be very convincing, but pose significant ethical challenges.  For questions or feedback on the series, message us on <a href="https://twitter.com/deepmind" rel="nofollow" target="_blank">Twitter @DeepMind</a> or email podcast@deepmind.com.  Interviewees: DeepMind’s Geoffrey Irving, Chris Dyer, Angeliki Lazaridou, Lisa-Anne Hendriks &amp; Laura Weidinger  CreditsPresenter: Hannah FrySeries Producer: Dan HardoonProduction support: Jill AchinekuSounds design: Emma BarnabyMusic composition: Eleni ShawSound Engineer: Nigel AppletonEditor: David PrestCommissioned by DeepMind Thank you to everyone who made this season possible!  Further reading: GPT-3 Powers the Next Generation of Apps, OpenAI: <a href="https://openai.com/blog/gpt-3-apps/" rel="nofollow" target="_blank">https://openai.com/blog/gpt-3-apps/</a><a href="https://web.stanford.edu/class/linguist238/p36-weizenabaum.pdf" rel="nofollow" target="_blank">https://web.stanford.edu/class/linguist238/p36-weizenabaum.pdf</a>Never Mind the Computer 1983 about the ELIZA program, BBC: <a href="https://www.bbc.co.uk/programmes/p023kpf8" rel="nofollow" target="_blank">https://www.bbc.co.uk/programmes/p023kpf8</a>How Large Language Models Will Transform Science, Society, and AI, Stanford University: <a href="https://hai.stanford.edu/news/how-large-language-models-will-transform-science-society-and-ai" rel="nofollow" target="_blank">https://hai.stanford.edu/news/how-large-language-models-will-transform-science-society-and-ai</a>Challenges in Detoxifying Language Models, DeepMind: <a href="https://deepmind.com/research/publications/2021/Challenges-in-Detoxifying-Language-Models" rel="nofollow" target="_blank">https://deepmind.com/research/publications/2021/Challenges-in-Detoxifying-Language-Models</a>Extending Machine Language Models toward Human-Level Language Understanding, DeepMind: <a href="https://deepmind.com/research/publications/2020/Extending-Machine-Language-Models-toward-Human-Level-Language-Understanding" rel="nofollow" target="_blank">https://deepmind.com/research/publications/2020/Extending-Machine-Language-Models-toward-Human-Level-Language-Understanding</a>Language modelling at scale, DeepMind: <a href="https://deepmind.com/blog/article/language-modelling-at-scale" rel="nofollow" target="_blank">https://deepmind.com/blog/article/language-modelling-at-scale</a>Artificial general intelligence, Technology Review: <a href="https://www.technologyreview.com/2020/10/15/1010461/artificial-general-intelligence-robots-ai-agi-deepmind-google-openai/" rel="nofollow" target="_blank">https://www.technologyreview.com/2020/10/15/1010461/artificial-general-intelligence-robots-ai-agi-deepmind-google-openai/</a>A Definition of Machine Intelligence by Shane Legg, arXiv: <a href="https://arxiv.org/abs/0712.3329" rel="nofollow" target="_blank">https://arxiv.org/abs/0712.3329</a>Stuart Russell - Living With Artificial Intelligence, BBC: <a href="https://www.bbc.co.uk/programmes/m001216k/episodes/player" rel="nofollow" target="_blank">https://www.bbc.co.uk/programmes/m001216k/episodes/player</a>

Speaking of intelligence

Hannah Fry

The chart-topping podcast which uncovers the extraordinary ways artificial intelligence (AI) is transforming our world is back for a second season. Join mathematician and broadcaster Professor Hannah Fry behind the scenes of world-leading AI research lab DeepMind to get the inside story of how AI is being created – and how it can benefit our lives and the society we live in.Recorded over six months and featuring over 30 original interviews, including DeepMind co-founders Demis Hassabis and Shane Legg, the podcast gives listeners exclusive access to the brilliant people building the technology of the future. Throughout nine original episodes, Hannah discovers how DeepMind is using AI to advance science in critical areas, like solving a 50-year-old grand challenge in biology and developing nuclear fusion.Listeners hear stories of teaching robots to walk at home during lockdown, as well as using AI to forecast weather, help people regain their voices, and enhance game strategies with Liverpool Football Club. Hannah also takes an in-depth look at the challenges and potential of building artificial general intelligence (AGI) and explores what it takes to ensure AI is built to benefit society.“I hope this series gives people a better understanding of AI and a feeling for just how exhilarating an endeavour it is.” – Demis Hassabis, CEO and Co-Founder of DeepMindFor questions or feedback on the series, message us on Twitter @DeepMind or email podcast@deepmind.com.CreditsPresenter: Hannah FrySeries Producer: Dan HardoonProduction support: Jill AchinekuSounds design: Emma BarnabyMusic composition: Eleni ShawSound Engineer: Nigel AppletonEditor: David PrestCommissioned by DeepMind

The chart-topping podcast which uncovers the extraordinary ways artificial intelligence (AI) is transforming our world is back for a second season. Join mathematician and broadcaster Professor Hannah Fry behind the scenes of world-leading AI research lab DeepMind to get the inside story of how AI is being created – and how it can benefit our lives and the society we live in.Recorded over six months and featuring over 30 original interviews, including DeepMind co-founders Demis Hassabis and Shane Legg, the podcast gives listeners exclusive access to the brilliant people building the technology of the future. Throughout nine original episodes, Hannah discovers how DeepMind is using AI to advance science in critical areas, like solving a 50-year-old grand challenge in biology and developing nuclear fusion.Listeners hear stories of teaching robots to walk at home during lockdown, as well as using AI to forecast weather, help people regain their voices, and enhance game strategies with Liverpool Football Club. Hannah also takes an in-depth look at the challenges and potential of building artificial general intelligence (AGI) and explores what it takes to ensure AI is built to benefit society.“I hope this series gives people a better understanding of AI and a feeling for just how exhilarating an endeavour it is.” – Demis Hassabis, CEO and Co-Founder of DeepMindFor questions or feedback on the series, message us on Twitter @DeepMind or email <a href="mailto:podcast@deepmind.com">podcast@deepmind.com</a>.Credits Presenter: Hannah Fry Series Producer: Dan Hardoon Production support: Jill Achineku Sounds design: Emma Barnaby Music composition: Eleni Shaw Sound Engineer: Nigel Appleton Editor: David Prest Commissioned by DeepMind

DeepMind: The Podcast with Hannah Fry – Season 2 coming soon!

Get the inside story of how AI is being created and uncover the extraordinary ways artificial intelligence (AI) is transforming our world.In the highly-praised, award-nominated "DeepMind: The Podcast", mathematician and broadcaster Hannah Fry goes behind the scenes of world-leading research lab DeepMind to find out how AI can benefit our lives and the society we live in. The first season explores the link between neuroscience and AI, the importance of games, and building safe AI. Now in its second season, Hannah uncovers how AI is accelerating science in critical areas, takes an in-depth look at building artificial general intelligence (AGI), and so much more.

In this special extended episode, Hannah Fry meets Demis Hassabis, the CEO and co-founder of DeepMind. She digs into his former life as a chess player, games designer and neuroscientist and explores how his love of chess helped him to get start-up funding, what drives him and his vision, and why AI keeps him up at night.If you have a question or feedback on the series, message us on Twitter (@DeepMind using the hashtag #DMpodcast) or email us at podcast@deepmind.com.Further reading:Wired: Inside DeepMind's epic mission to solve science's trickiest problemQuanta magazine: How Artificial Intelligence Is Changing ScienceDemis Hassabis: A systems neuroscience approach to building AGI. Talk at the 2010 Singularity Summit Demis Hassabis: The power of self-learning systems. Talk at MIT 2019Demis Hassabis: Talk on Creativity and AI Financial Times: The mind in the machine: Demis Hassabis on artificial intelligence (2017)The Times: Interview with Demis HassabisThe Economist Babbage podcast: DeepMind GamesInterview with Demis Hassabis from the book Game Changer, which also features an introduction from DemisInterviewees: Deepmind CEO and co-founder, Demis HassabisCredits:Presenter: Hannah FryEditor: David PrestSenior Producer: Louisa FieldProducers: Amy Racs, Dan HardoonBinaural Sound: Lucinda Mason-BrownMusic composition: Eleni Shaw (with help from Sander Dieleman and WaveNet)Commissioned by DeepMind

In this special extended episode, Hannah Fry meets Demis Hassabis, the CEO and co-founder of DeepMind. She digs into his former life as a chess player, games designer and neuroscientist and explores how his love of chess helped him to get start-up funding, what drives him and his vision, and why AI keeps him up at night.If you have a question or feedback on the series, message us on Twitter (<a href="https://twitter.com/deepmind?lang=en" rel="nofollow" target="_blank">@DeepMind</a> using the hashtag #DMpodcast) or email us at <a href="mailto:podcast@deepmind.com">podcast@deepmind.com</a>.Further reading:<ul><li><a href="https://www.wired.co.uk/article/deepmind-protein-folding" rel="nofollow" target="_blank">Wired: Inside DeepMind's epic mission to solve science's trickiest problem</a></li><li><a href="https://www.quantamagazine.org/how-artificial-intelligence-is-changing-science-20190311/" rel="nofollow" target="_blank">Quanta magazine: How Artificial Intelligence Is Changing Science</a></li><li><a href="https://www.youtube.com/watch?v=Qgd3OK5DZWI" rel="nofollow" target="_blank">Demis Hassabis: A systems neuroscience approach to building AGI. Talk at the 2010 Singularity Summit</a> </li><li><a href="https://cbmm.mit.edu/video/power-self-learning-systems" rel="nofollow" target="_blank">Demis Hassabis: The power of self-learning systems. Talk at MIT 2019</a></li><li><a href="https://www.youtube.com/watch?v=d-bvsJWmqlc" rel="nofollow" target="_blank">Demis Hassabis: Talk on Creativity and AI</a> </li><li><a href="https://www.ft.com/content/048f418c-2487-11e7-a34a-538b4cb30025" rel="nofollow" target="_blank">Financial Times: The mind in the machine: Demis Hassabis on artificial intelligence (2017)</a></li><li><a href="https://www.thetimes.co.uk/article/demis-hassabis-interview-the-brains-behind-deepmind-on-the-future-of-artificial-intelligence-mzk0zhsp8" rel="nofollow" target="_blank">The Times: Interview with Demis Hassabis</a></li><li><a href="https://play.acast.com/s/theeconomistbabbage/99af5224-b955-4a3c-930c-91a68bfe6c88?autoplay=true" rel="nofollow" target="_blank">The Economist Babbage podcast: DeepMind Games</a></li><li><a href="https://storage.googleapis.com/deepmind-media/podcast/Game%20Changer%20-%20Demis%20Hassabis%20Interview.pdf" rel="nofollow" target="_blank">Interview with Demis Hassabis</a> from <a href="https://www.newinchess.com/game-changer" rel="nofollow" target="_blank">the book Game Changer</a>, which also features an introduction from Demis</li></ul>Interviewees: Deepmind CEO and co-founder, Demis HassabisCredits: 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) Commissioned by DeepMind

Demis Hassabis: The interview

AI researchers around the world are trying to create a general purpose learning system that can learn to solve a broad range of problems without being taught how. Koray Kavukcuoglu, DeepMind’s Director of Research, describes the journey to get there, and takes Hannah on a whistle-stop tour of DeepMind’s HQ and its research.If you have a question or feedback on the series, message us on Twitter (@DeepMind using the hashtag #DMpodcast) or email us at podcast@deepmind.com.Further reading:OpenAI: An overview of neural networks and the progress that has been made in AIShane Legg, DeepMind co-founder: Measuring machine intelligence at the 2010 Singularity SummitShane Legg and Marcus Hutter: Paper on defining machine intelligenceDemis Hassabis: Talk on the history, frontiers and capabilities of AIRobert Wiblin: Positively shaping the development of artificial intelligenceAsilomar AI PrinciplesRichard S. Sutton and Andrew G. Barto: Reinforcement Learning: An IntroductionInterviewees: Koray Kavukcuoglu, Director of Research; Trevor Back, Product Manager for DeepMind’s science research; research scientists Raia Hadsell and Murray Shanahan; and DeepMind CEO and co-founder, Demis Hassabis.Credits:Presenter: Hannah FryEditor: David PrestSenior Producer: Louisa FieldProducers: Amy Racs, Dan HardoonBinaural Sound: Lucinda Mason-BrownMusic composition: Eleni Shaw (with help from Sander Dieleman and WaveNet)Commissioned by DeepMind

AI researchers around the world are trying to create a general purpose learning system that can learn to solve a broad range of problems without being taught how. Koray Kavukcuoglu, DeepMind’s Director of Research, describes the journey to get there, and takes Hannah on a whistle-stop tour of DeepMind’s HQ and its research.If you have a question or feedback on the series, message us on Twitter (<a href="https://twitter.com/deepmind?lang=en" rel="nofollow" target="_blank">@DeepMind</a> using the hashtag #DMpodcast) or email us at <a href="mailto:podcast@deepmind.com">podcast@deepmind.com</a>.Further reading: <a href="https://www.youtube.com/watch?v=YHCSNsLKHfM" rel="nofollow" target="_blank">OpenAI: An overview of neural networks and the progress that has been made in AI</a> <a href="https://www.youtube.com/watch?v=0ghzG14dT-w" rel="nofollow" target="_blank">Shane Legg, DeepMind co-founder: Measuring machine intelligence at the 2010 Singularity Summit</a> <a href="https://arxiv.org/abs/0712.3329" rel="nofollow" target="_blank">Shane Legg and Marcus Hutter: Paper on defining machine intelligence</a> <a href="https://www.youtube.com/watch?v=zYfzux7JKHE" rel="nofollow" target="_blank">Demis Hassabis: Talk on the history, frontiers and capabilities of AI</a> <a href="https://80000hours.org/problem-profiles/positively-shaping-artificial-intelligence/?source=post_page" rel="nofollow" target="_blank">Robert Wiblin: Positively shaping the development of artificial intelligence</a> <a href="https://futureoflife.org/ai-principles/" rel="nofollow" target="_blank">Asilomar AI Principles</a> <a href="http://incompleteideas.net/book/bookdraft2017nov5.pdf" rel="nofollow" target="_blank">Richard S. Sutton and Andrew G. Barto: Reinforcement Learning: An Introduction</a>Interviewees: Koray Kavukcuoglu, Director of Research; Trevor Back, Product Manager for DeepMind’s science research; research scientists Raia Hadsell and Murray Shanahan; and DeepMind CEO and co-founder, Demis Hassabis.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) Commissioned by DeepMind

Towards the future

While there is a lot of excitement about AI research, there are also concerns about the way it might be implemented, used and abused. In this episode Hannah investigates the more human side of the technology, some ethical issues around how it is developed and used, and the efforts to create a future of AI that works for everyone.If you have a question or feedback on the series, message us on Twitter (@DeepMind using the hashtag #DMpodcast) or email us at podcast@deepmind.com.Further reading:The Partnership on AIProPublica: investigation into machine bias in criminal sentencingScience Museum – free exhibition: Driverless: who is in control (until Oct 2020)Survival of the best fit: An interactive game that demonstrates some of the ways in which bias can be introduced into AI systems, in this case for hiringJoy Buolamwini: AI, Ain’t I a Woman: A spoken word piece exploring AI bias, and systems not recognising prominent black womenHannah Fry: Hello World - How to be Human in the Age of the MachineDeepMind: Safety and EthicsFuture of Humanity Institute: AI Governance:A Research AgendaInterviewees: Verity Harding, Co-Lead of DeepMind Ethics and Society; DeepMind’s COO Lila Ibrahim, and research scientists William Isaac and Silvia Chiappa.Credits:Presenter: Hannah FryEditor: David PrestSenior Producer: Louisa FieldProducers: Amy Racs, Dan HardoonBinaural Sound: Lucinda Mason-BrownMusic composition: Eleni Shaw (with help from Sander Dieleman and WaveNet)Commissioned by DeepMind

While there is a lot of excitement about AI research, there are also concerns about the way it might be implemented, used and abused. In this episode Hannah investigates the more human side of the technology, some ethical issues around how it is developed and used, and the efforts to create a future of AI that works for everyone.If you have a question or feedback on the series, message us on Twitter (<a href="https://twitter.com/deepmind?lang=en" rel="nofollow" target="_blank">@DeepMind</a> using the hashtag #DMpodcast) or email us at <a href="mailto:podcast@deepmind.com">podcast@deepmind.com</a>.Further reading:<ol><li><a href="https://www.partnershiponai.org/" rel="nofollow" target="_blank">The Partnership on AI</a></li><li><a href="https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing" rel="nofollow" target="_blank">ProPublica: investigation into machine bias in criminal sentencing</a></li><li><a href="https://www.sciencemuseum.org.uk/see-and-do/driverless-who-is-in-control" rel="nofollow" target="_blank">Science Museum – free exhibition: Driverless: who is in control (until Oct 2020)</a></li><li><a href="https://www.survivalofthebestfit.com/resources" rel="nofollow" target="_blank">Survival of the best fit: An interactive game that demonstrates some of the ways in which bias can be introduced into AI systems, in this case for hiring</a></li><li><a href="https://www.youtube.com/watch?v=QxuyfWoVV98" rel="nofollow" target="_blank">Joy Buolamwini: AI, Ain’t I a Woman: A spoken word piece exploring AI bias, and systems not recognising prominent black women</a></li><li><a href="https://www.penguin.co.uk/books/111/1114076/hello-world/9781784163068.html" rel="nofollow" target="_blank">Hannah Fry: Hello World - How to be Human in the Age of the Machine</a></li><li><a href="https://deepmind.com/safety-and-ethics" rel="nofollow" target="_blank">DeepMind: Safety and Ethics</a></li><li><a href="https://www.fhi.ox.ac.uk/wp-content/uploads/GovAIAgenda.pdf" rel="nofollow" target="_blank">Future of Humanity Institute: AI Governance:A Research Agenda</a></li></ol>Interviewees: Verity Harding, Co-Lead of DeepMind Ethics and Society; DeepMind’s COO Lila Ibrahim, and research scientists William Isaac and Silvia Chiappa.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) Commissioned by DeepMind

AI for everyone

The ambition of much of AI research is to create systems that can help to solve problems in the real world. In this episode, Hannah meets the people building systems that could be used to save the sight of thousands, help us solve one of the most fundamental problems in biology and reduce energy consumption in an effort to combat climate change. But whilst there is great potential, there are also important obstacles that will need to be tackled for AI to be used effectively, safely and fairly.If you have a question or feedback on the series, message us on Twitter (@DeepMind using the hashtag #DMpodcast) or email us at podcast@deepmind.com.Further reading:Wired: Inside DeepMind's epic mission to solve science's trickiest problemDeepMind blogs on the partnership with Moorfields NHS eye hospital and predicting eye disease, and Moorfields’ news announcement on its research with DeepMindDeepMind blog: AlphaFold: Using AI for scientific discoveryDeepMind blogs on reducing Google’s energy bill for datacentre cooling and how this project has progressedResearch paper: Tackling Climate Change with Machine LearningQuanta magazine: How Artificial Intelligence Is Changing ScienceDeepMind blog: How evolutionary selection can train more capable self-driving carsOther examples of the application of AI for real-world impact include:Francis Crick Institute: machine learning models that can help predict heart diseaseNASA: AUDREY machine learning system to better guide first responders through firesUniversity of Southern California: Protection Assistant for Wildlife Security using AI to help wildlife conservationInterviewees: Pearse Keane, consultant ophthalmologist at Moorfields Eye Hospital; Sandy Nelson, Product Manager for DeepMind’s Science Program; and DeepMind Program Manager Sims Witherspoon.Credits:Presenter: Hannah FryEditor: David PrestSenior Producer: Louisa FieldProducers: Amy Racs, Dan HardoonBinaural Sound: Lucinda Mason-BrownMusic composition: Eleni Shaw (with help from Sander Dieleman and WaveNet)Commissioned by DeepMind

The ambition of much of AI research is to create systems that can help to solve problems in the real world. In this episode, Hannah meets the people building systems that could be used to save the sight of thousands, help us solve one of the most fundamental problems in biology and reduce energy consumption in an effort to combat climate change. But whilst there is great potential, there are also important obstacles that will need to be tackled for AI to be used effectively, safely and fairly.If you have a question or feedback on the series, message us on Twitter (<a href="https://twitter.com/deepmind?lang=en" rel="nofollow" target="_blank">@DeepMind</a> using the hashtag #DMpodcast) or email us at <a href="mailto:podcast@deepmind.com">podcast@deepmind.com</a>.Further reading:<ul><li><a href="https://www.wired.co.uk/article/deepmind-protein-folding" rel="nofollow" target="_blank">Wired: Inside DeepMind's epic mission to solve science's trickiest problem</a></li><li>DeepMind blogs <a href="https://deepmind.com/blog/moorfields-major-milestone/" rel="nofollow" target="_blank">on the partnership with Moorfields NHS eye hospital</a> and <a href="https://deepmind.com/blog/predicting-eye-disease-moorfields/" rel="nofollow" target="_blank">predicting eye disease</a>, and <a href="https://www.moorfields.nhs.uk/news/breakthrough-ai-technology-improve-care-patients" rel="nofollow" target="_blank">Moorfields’ news announcement on its research with DeepMind</a></li><li><a href="https://deepmind.com/blog/alphafold/" rel="nofollow" target="_blank">DeepMind blog: AlphaFold: Using AI for scientific discovery</a></li><li>DeepMind blogs on <a href="https://deepmind.com/blog/deepmind-ai-reduces-google-data-centre-cooling-bill-40/" rel="nofollow" target="_blank">reducing Google’s energy bill for datacentre cooling</a> and <a href="https://deepmind.com/blog/safety-first-ai-autonomous-data-centre-cooling-and-industrial-control/" rel="nofollow" target="_blank">how this project has progressed</a></li><li><a href="https://arxiv.org/pdf/1906.05433v1.pdf?source=post_page" rel="nofollow" target="_blank">Research paper: Tackling Climate Change with Machine Learning</a></li><li><a href="https://www.quantamagazine.org/how-artificial-intelligence-is-changing-science-20190311/" rel="nofollow" target="_blank">Quanta magazine: How Artificial Intelligence Is Changing Science</a></li><li>DeepMind blog: <a href="https://deepmind.com/blog/how-evolutionary-selection-can-train-more-capable-self-driving-cars/" rel="nofollow" target="_blank">How evolutionary selection can train more capable self-driving cars</a></li></ul>Other examples of the application of AI for real-world impact include:<ul><li><a href="http://dx.doi.org/10.1371/journal.pone.0202344" rel="nofollow" target="_blank">Francis Crick Institute: machine learning models that can help predict heart disease</a></li><li><a href="https://technology.nasa.gov/features/audrey.html" rel="nofollow" target="_blank">NASA: AUDREY machine learning system to better guide first responders through fires</a></li><li><a href="http://teamcore.usc.edu/people/Paws/index.html#news" rel="nofollow" target="_blank">University of Southern California: Protection Assistant for Wildlife Security using AI to help wildlife conservation</a></li></ul>Interviewees: Pearse Keane, consultant ophthalmologist at Moorfields Eye Hospital; Sandy Nelson, Product Manager for DeepMind’s Science Program; and DeepMind Program Manager Sims Witherspoon.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) Commissioned by DeepMind

Out of the lab

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.If you have a question or feedback on the series, message us on Twitter (@DeepMind using the hashtag #DMpodcast) or email us at podcast@deepmind.com.Further reading: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 &amp; AINick Bostrom: Superintelligence: Paths, Dangers and Strategies (book)OpenAI: Learning from Human PreferencesDeepMind blog: Learning from human preferencesDeepMind blog: Learning by playing - how robots can tidy up after themselvesDeepMind blog: AI safetyInterviewees: Software engineer Jackie Kay and research scientists Murray Shanahan, Victoria Krakovna, Raia Hadsell and Jan Leike.Credits:Presenter: Hannah FryEditor: David PrestSenior Producer: Louisa FieldProducers: Amy Racs, Dan HardoonBinaural Sound: Lucinda Mason-BrownMusic composition: Eleni Shaw (with help from Sander Dieleman and WaveNet)Commissioned by DeepMind

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.If you have a question or feedback on the series, message us on Twitter (<a href="https://twitter.com/deepmind?lang=en" rel="nofollow" target="_blank">@DeepMind</a> using the hashtag #DMpodcast) or email us at <a href="mailto:podcast@deepmind.com">podcast@deepmind.com</a>.Further reading:<ul><li>Blogs on <a href="https://vkrakovna.wordpress.com/2018/04/02/specification-gaming-examples-in-ai/" rel="nofollow" target="_blank">AI safety</a> and <a href="https://vkrakovna.wordpress.com/ai-safety-resources/" rel="nofollow" target="_blank">further resources</a> from Victoria Krakovna</li><li><a href="https://futureoflife.org/background/benefits-risks-of-artificial-intelligence/" rel="nofollow" target="_blank">The Future of Life Institute: The risks and benefits of AI</a></li><li><a href="https://www.wsj.com/articles/protecting-against-ais-existential-threat-1508332313" rel="nofollow" target="_blank">The Wall Street Journal: Protecting Against AI’s Existential Threat</a></li><li><a href="https://www.ted.com/talks/max_tegmark_how_to_get_empowered_not_overpowered_by_ai" rel="nofollow" target="_blank">TED Talks: Max Tegmark - How to get empowered, not overpowered, by AI</a></li><li><a href="https://royalsociety.org/topics-policy/projects/machine-learning/you-and-ai/" rel="nofollow" target="_blank">Royal Society lecture series sponsored by DeepMind: You &amp; AI</a></li><li><a href="http://www.worldcat.org/title/superintelligence-paths-dangers-strategies/oclc/963350788&amp;referer=brief_results" rel="nofollow" target="_blank">Nick Bostrom: Superintelligence: Paths, Dangers and Strategies</a> (book)</li><li><a href="https://openai.com/blog/deep-reinforcement-learning-from-human-preferences/" rel="nofollow" target="_blank">OpenAI: Learning from Human Preferences</a></li><li><a href="https://deepmind.com/research/publications/deep-reinforcement-learning-human-preferences/" rel="nofollow" target="_blank">DeepMind blog: Learning from human preferences</a></li><li><a href="https://deepmind.com/blog/learning-playing/" rel="nofollow" target="_blank">DeepMind blog: Learning by playing - how robots can tidy up after themselves</a></li><li><a href="https://medium.com/@deepmindsafetyresearch" rel="nofollow" target="_blank">DeepMind blog: AI safety</a></li></ul>Interviewees: Software engineer Jackie Kay and research scientists Murray Shanahan, Victoria Krakovna, Raia Hadsell and Jan Leike.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) Commissioned by DeepMind

AI, Robot

Video games have become a favourite tool for AI researchers to test the abilities of their systems. In this episode, Hannah sits down to play StarCraft II - a challenging video game that requires players to control the onscreen action with as many as 800 clicks a minute. She is guided by Oriol Vinyals, an ex-professional StarCraft player and research scientist at DeepMind, who explains how the program AlphaStar learnt to play the game and beat a top professional player. Elsewhere, she explores systems that are learning to cooperate in a digital version of the playground favourite ‘Capture the Flag’.If you have a question or feedback on the series, message us on Twitter (@DeepMind using the hashtag #DMpodcast) or emailing us at podcast@deepmind.com.Further readingThe Economist: Why AI researchers like video gamesDeepMind blogs: Capture the Flag and AlphastarProfessional StarCraft II player MaNa gives his impressions of AlphaStar and DeepMindOpen AI’s work on Dota 2 The New York Times: DeepMind can now beat us at multiplayer games, tooRoyal Society: Machine Learning resourcesDeepMind: The Inside Story of AlphaStar Andrej Karpathy: Deep Reinforcement Learning: Pong from PixelsInterviewees: Research scientists Max Jaderberg and Raia Hadsell; Lead researchers David Silver and Oriol Vinyals, and Director of Research Koray Kavukcuoglu.Credits:Presenter: Hannah FryEditor: David PrestSenior Producer: Louisa FieldProducers: Amy Racs, Dan HardoonBinaural Sound: Lucinda Mason-BrownMusic composition: Eleni Shaw (with help from Sander Dieleman and WaveNet)Commissioned by DeepMind

Video games have become a favourite tool for AI researchers to test the abilities of their systems. In this episode, Hannah sits down to play StarCraft II - a challenging video game that requires players to control the onscreen action with as many as 800 clicks a minute. She is guided by Oriol Vinyals, an ex-professional StarCraft player and research scientist at DeepMind, who explains how the program AlphaStar learnt to play the game and beat a top professional player. Elsewhere, she explores systems that are learning to cooperate in a digital version of the playground favourite ‘Capture the Flag’.If you have a question or feedback on the series, message us on Twitter (<a href="https://twitter.com/deepmindai?lang=en" rel="nofollow" target="_blank">@DeepMind</a> using the hashtag #DMpodcast) or emailing us at <a href="mailto:podcast@deepmind.com">podcast@deepmind.com</a>.Further reading<ul><li><a href="https://www.economist.com/science-and-technology/2017/05/13/why-ai-researchers-like-video-games" rel="nofollow" target="_blank">The Economist: Why AI researchers like video games</a></li><li>DeepMind blogs: <a href="https://deepmind.com/blog/article/capture-the-flag-science" rel="nofollow" target="_blank">Capture the Flag</a> and <a href="https://deepmind.com/blog/article/alphastar-mastering-real-time-strategy-game-starcraft-ii" rel="nofollow" target="_blank">Alphastar</a></li><li><a href="https://www.youtube.com/watch?v=zgIFoepzhIo&amp;feature=youtu.be" rel="nofollow" target="_blank">Professional StarCraft II player MaNa gives his impressions of AlphaStar and DeepMind</a></li><li><a href="https://openai.com/five/" rel="nofollow" target="_blank">Open AI’s work on Dota 2 </a></li><li><a href="https://www.nytimes.com/2019/05/30/science/deep-mind-artificial-intelligence.html" rel="nofollow" target="_blank">The New York Times: DeepMind can now beat us at multiplayer games, too</a></li><li><a href="https://royalsociety.org/topics-policy/projects/machine-learning/?utm_source=royalsociety.org&amp;utm_medium=redirect&amp;utm_campaign=machine-learning" rel="nofollow" target="_blank">Royal Society: Machine Learning resources</a></li><li><a href="https://www.youtube.com/watch?v=UuhECwm31dM" rel="nofollow" target="_blank">DeepMind: The Inside Story of AlphaStar </a></li><li><a href="http://karpathy.github.io/2016/05/31/rl/" rel="nofollow" target="_blank">Andrej Karpathy: Deep Reinforcement Learning: Pong from Pixels</a></li></ul>Interviewees: Research scientists Max Jaderberg and Raia Hadsell; Lead researchers David Silver and Oriol Vinyals, and Director of Research Koray Kavukcuoglu.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) Commissioned by DeepMind

Life is like a game

In March 2016, more than 200 million people watched AlphaGo become first computer program to defeat a professional human player at the game of Go, a milestone in AI research that was considered to be a decade ahead of its time. Since then the team has continued to develop the system and recently unveiled AlphaZero: a program that has taught itself how to play chess, Go, and shogi. Hannah explores the inside story of both with Lead Researcher David Silver and finds out why games are a useful proving ground for AI researchers. She also meets Chess Grandmaster Matthew Sadler and women’s international master Natasha Regan, who have written a book on AlphaZero and its unique gameplay.If you have a question or feedback on the series, message us on Twitter (@DeepMind using the hashtag #DMpodcast) or email us at podcast@deepmind.com.Further readingAlphaGo the documentary The Surrounding Game: Documentary about the ancient game of GoDeepMind website: AlphaGoGarry Kasparov: Deep ThinkingAI: More than Human - Exhibition at the Barbican Centre, 2019 and online exhibitDeepMind blog: AlphaZero: Shedding new light on chess, shogi, and GoMatthew Sadler and Natasha Regan: Game Changer - a book about chess and AI WIRED: What the AI behind AlphaGo can teach us about being humanInterviewees: DeepMind CEO Demis Hassabis, Matthew Sadler, chess Grandmaster; Lead Researcher David Silver, Matt Botvinick, Director of Neuroscience Research; and Natasha Regan, women’s international chess master.Credits:Presenter: Hannah FryEditor: David PrestSenior Producer: Louisa FieldProducers: Amy Racs, Dan HardoonBinaural Sound: Lucinda Mason-BrownMusic composition: Eleni Shaw (with help from Sander Dieleman and WaveNet)Commissioned by DeepMind

In March 2016, more than 200 million people watched AlphaGo become first computer program to defeat a professional human player at the game of Go, a milestone in AI research that was considered to be a decade ahead of its time. Since then the team has continued to develop the system and recently unveiled AlphaZero: a program that has taught itself how to play chess, Go, and shogi. Hannah explores the inside story of both with Lead Researcher David Silver and finds out why games are a useful proving ground for AI researchers. She also meets Chess Grandmaster Matthew Sadler and women’s international master Natasha Regan, who have written a book on AlphaZero and its unique gameplay.If you have a question or feedback on the series, message us on Twitter (<a href="https://twitter.com/deepmind?lang=en" rel="nofollow" target="_blank">@DeepMind</a> using the hashtag #DMpodcast) or email us at <a href="mailto:podcast@deepmind.com">podcast@deepmind.com</a>.Further reading<ul><li><a href="https://www.alphagomovie.com/" rel="nofollow" target="_blank">AlphaGo the documentary</a> </li><li><a href="https://www.surroundinggamemovie.com/" rel="nofollow" target="_blank">The Surrounding Game: Documentary about the ancient game of Go</a></li><li><a href="https://deepmind.com/research/case-studies/alphago-the-story-so-far" rel="nofollow" target="_blank">DeepMind website: AlphaGo</a></li><li><a href="http://www.kasparov.com/deep-thinking-ai/" rel="nofollow" target="_blank">Garry Kasparov: Deep Thinking</a></li><li><a href="https://www.barbican.org.uk/whats-on/2019/event/ai-more-than-human" rel="nofollow" target="_blank">AI: More than Human - Exhibition at the Barbican Centre</a>, 2019 and <a href="https://artsandculture.google.com/exhibit/0wLCk0X1qEe5KA" rel="nofollow" target="_blank">online exhibit</a></li><li><a href="https://deepmind.com/blog/article/alphazero-shedding-new-light-grand-games-chess-shogi-and-go" rel="nofollow" target="_blank">DeepMind blog: AlphaZero: Shedding new light on chess, shogi, and Go</a></li><li><a href="https://www.newinchess.com/game-changer" rel="nofollow" target="_blank">Matthew Sadler and Natasha Regan: Game Changer - a book about chess and AI</a> </li><li><a href="https://www.wired.com/2016/05/google-alpha-go-ai/" rel="nofollow" target="_blank">WIRED: What the AI behind AlphaGo can teach us about being human</a></li></ul>Interviewees: DeepMind CEO Demis Hassabis, Matthew Sadler, chess Grandmaster; Lead Researcher David Silver, Matt Botvinick, Director of Neuroscience Research; and Natasha Regan, women’s international chess master.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) Commissioned by DeepMind

Go to Zero

Circle

What can the human brain teach us about AI? And what can AI teach us about our own intelligence? These questions underpin a lot of AI research. In this first episode, Hannah meets the DeepMind Neuroscience team to explore these connections and discovers how our brains are like birds’ wings, what training a dog and an AI agent have in common, and why the simplest things for people to do are, paradoxically, often the hardest for machines.If you have a question or feedback on the series, message us on Twitter (@DeepMind using the hashtag #DMpodcast) or email us at podcast@deepmind.com.Further readingBBC: An AI playlistWait But Why: The AI RevolutionCoursera: AI for everyoneMedium: Machine Learning for HumansGoogle Arts &amp; Culture: 25 moments that have defined AIRoyal Society: What is Machine Learning?The Algorithm: A weeklyemail newsletter from MIT Tech ReviewDeepMind blog: neuroscience and AI: a virtuous circleNature: Far-sighted birds plan breakfast the evening beforeInterviewees in this episode: Deepmind CEO and co-founder, Demis Hassabis; Matt Botvinick, Director of Neuroscience Research; research scientists Jess Hamrick and Greg Wayne; and Director of Research, Koray Kavukcuoglu.Credits:Presenter: Hannah FryEditor: David PrestSenior Producer: Louisa FieldProducers: Amy Racs, Dan HardoonBinaural Sound: Lucinda Mason-BrownMusic composition: Eleni Shaw (with help from Sander Dieleman and WaveNet)Commissioned by DeepMind

What can the human brain teach us about AI? And what can AI teach us about our own intelligence? These questions underpin a lot of AI research. In this first episode, Hannah meets the DeepMind Neuroscience team to explore these connections and discovers how our brains are like birds’ wings, what training a dog and an AI agent have in common, and why the simplest things for people to do are, paradoxically, often the hardest for machines.If you have a question or feedback on the series, message us on Twitter (<a href="https://twitter.com/deepmind?lang=en" rel="nofollow" target="_blank">@DeepMind</a> using the hashtag #DMpodcast) or email us at <a href="mailto:podcast@deepmind.com">podcast@deepmind.com</a>.Further reading<ul><li><a href="https://www.bbc.co.uk/programmes/topics/Artificial_intelligence" rel="nofollow" target="_blank">BBC: An AI playlist</a></li><li><a href="https://waitbutwhy.com/2015/01/artificial-intelligence-revolution-1.html" rel="nofollow" target="_blank">Wait But Why: The AI Revolution</a></li><li><a href="https://www.coursera.org/learn/ai-for-everyone" rel="nofollow" target="_blank">Coursera: AI for everyone</a></li><li><a href="https://medium.com/machine-learning-for-humans/why-machine-learning-matters-6164faf1df12" rel="nofollow" target="_blank">Medium: Machine Learning for Humans</a></li><li><a href="https://artsandculture.google.com/exhibit/yQJiFZ3lStANKA" rel="nofollow" target="_blank">Google Arts &amp; Culture: 25 moments that have defined AI</a></li><li><a href="https://royalsociety.org/topics-policy/projects/machine-learning/what-is-machine-learning-infographic/" rel="nofollow" target="_blank">Royal Society: What is Machine Learning?</a></li><li><a href="https://go.technologyreview.com/newsletters/the-algorithm/" rel="nofollow" target="_blank">The Algorithm: A weeklyemail newsletter from MIT Tech Review</a></li><li><a href="https://deepmind.com/blog/article/ai-and-neuroscience-virtuous-circle" rel="nofollow" target="_blank">DeepMind blog: neuroscience and AI: a virtuous circle</a></li><li><a href="https://www.nature.com/news/2007/070219/full/070219-6.html" rel="nofollow" target="_blank">Nature: Far-sighted birds plan breakfast the evening before</a></li></ul>Interviewees in this episode: Deepmind CEO and co-founder, Demis Hassabis; Matt Botvinick, Director of Neuroscience Research; research scientists Jess Hamrick and Greg Wayne; and Director of Research, Koray Kavukcuoglu.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) Commissioned by DeepMind

AI and Neuroscience: The virtuous circle

Selected as “New and Noteworthy” by Apple Podcasts, the highly-praised, award-nominated first season of "DeepMind: The Podcast" explores the fascinating world of artificial intelligence (AI). Join mathematician and broadcaster Hannah Fry as she meets world-class scientists and thinkers as they explain the foundations of AI, explore some of the challenges the field is wrestling with, and dives into the research that's led to breakthroughs like AlphaGo and AlphaFold. Whether you’re a beginner or an experienced researcher, join our journey into the past, present, and future of AI.“I hope what people are going to get out of this series is a better understanding of artificial intelligence, and I hope they also get a great feeling for how exhilarating an endeavour and a journey we’re on.” - Demis Hassabis, CEO and co-founder of DeepMindIf you have a question or feedback on the series, message us on Twitter @DeepMind using the hashtag #DMpodcast) or email us at podcast@deepmind.com.

Selected as “New and Noteworthy” by Apple Podcasts, the highly-praised, award-nominated first season of "DeepMind: The Podcast" explores the fascinating world of artificial intelligence (AI). Join mathematician and broadcaster Hannah Fry as she meets world-class scientists and thinkers as they explain the foundations of AI, explore some of the challenges the field is wrestling with, and dives into the research that's led to breakthroughs like AlphaGo and AlphaFold. Whether you’re a beginner or an experienced researcher, join our journey into the past, present, and future of AI. “I hope what people are going to get out of this series is a better understanding of artificial intelligence, and I hope they also get a great feeling for how exhilarating an endeavour and a journey we’re on.” - Demis Hassabis, CEO and co-founder of DeepMind If you have a question or feedback on the series, message us on Twitter @DeepMind using the hashtag #DMpodcast) or email us at podcast@deepmind.com.

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Savoring the anticipation

Get the inside story of how AI is being created and uncover the extraordinary ways artificial intelligence (AI) is transforming our world. In the highly-praised, award-nominated "DeepMind: The Podcast", mathematician and broadcaster Hannah Fry goes behind the scenes of world-leading research lab DeepMind to find out how AI can benefit our lives and the society we live in. The first season explores the link between neuroscience and AI, the importance of games, and building safe AI. Now in its second season, Hannah uncovers how AI is accelerating science in critical areas, takes an in-depth look at building artificial general intelligence (AGI), and so much more.

DeepMind: The Podcast

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