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Speaking of intelligence

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Contenuto fornito da Google DeepMind and Hannah Fry. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da Google DeepMind and Hannah Fry o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.player.fm/legal.

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 & Laura Weidinger

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

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.pdf

Never Mind the Computer 1983 about the ELIZA program, BBC: https://www.bbc.co.uk/programmes/p023kpf8

How 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-ai

Challenges in Detoxifying Language Models, DeepMind: https://deepmind.com/research/publications/2021/Challenges-in-Detoxifying-Language-Models

Extending Machine Language Models toward Human-Level Language Understanding, DeepMind: https://deepmind.com/research/publications/2020/Extending-Machine-Language-Models-toward-Human-Level-Language-Understanding

Language modelling at scale, DeepMind: https://deepmind.com/blog/article/language-modelling-at-scale

Artificial 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/0712.3329

Stuart Russell - Living With Artificial Intelligence, BBC: https://www.bbc.co.uk/programmes/m001216k/episodes/player

Want to share feedback? Why not leave a review on your favorite streaming platform? Have a suggestion for a guest that we should have on next? Leave us a comment on YouTube and stay tuned for future episodes.

  continue reading

27 episodi

Artwork

Speaking of intelligence

Google DeepMind: The Podcast

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iconCondividi
 
Manage episode 318496951 series 2532352
Contenuto fornito da Google DeepMind and Hannah Fry. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da Google DeepMind and Hannah Fry o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.player.fm/legal.

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 & Laura Weidinger

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

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.pdf

Never Mind the Computer 1983 about the ELIZA program, BBC: https://www.bbc.co.uk/programmes/p023kpf8

How 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-ai

Challenges in Detoxifying Language Models, DeepMind: https://deepmind.com/research/publications/2021/Challenges-in-Detoxifying-Language-Models

Extending Machine Language Models toward Human-Level Language Understanding, DeepMind: https://deepmind.com/research/publications/2020/Extending-Machine-Language-Models-toward-Human-Level-Language-Understanding

Language modelling at scale, DeepMind: https://deepmind.com/blog/article/language-modelling-at-scale

Artificial 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/0712.3329

Stuart Russell - Living With Artificial Intelligence, BBC: https://www.bbc.co.uk/programmes/m001216k/episodes/player

Want to share feedback? Why not leave a review on your favorite streaming platform? Have a suggestion for a guest that we should have on next? Leave us a comment on YouTube and stay tuned for future episodes.

  continue reading

27 episodi

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