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#17 - Dan Hendrycks - Are AI worries overblown?

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Manage episode 447010467 series 3611008
Contenu fourni par Liv Boeree. Tout le contenu du podcast, y compris les épisodes, les graphiques et les descriptions de podcast, est téléchargé et fourni directement par Liv Boeree ou son partenaire de plateforme de podcast. Si vous pensez que quelqu'un utilise votre œuvre protégée sans votre autorisation, vous pouvez suivre le processus décrit ici https://fr.player.fm/legal.

The rate of AI progress is accelerating, so how can we minimize the risks of this incredible technology, while maximizing the rewards?

Today I am speaking to leading AI researcher Dan Hendrycks — Dan is the founder of Center for AI Safety, and lead advisor to Elon Musk's X.AI. He was also the architect behind the "Mitigating Risks" letter that was signed by Demis Hassabis, Sam Altman, Bill Gates, Yoshua Bengio and many others.

In this conversation we discuss everything from immediate issues like deepfakes, to upcoming risks like malicious use, centralisation of power, regulatory capture and more. In other words, how do we ensure AI ends up a win/win for humanity instead of a lose/lose.

Chapters

00:00:00 - Intro

00:02:14 - Are current laws sufficient?

00:09:41 - Types of AI Risk

00:23:30 - Arms Races

00:39:10 - What happens inside an AI?

00:46:39 - Rogue AI

00:52:22 - Sentient AI

01:07:36 - Risks from Centralization

01:14:45 - Open Source

01:23:02 - AI speeding up systemic risks

01:29:54 - Synthetic Data & Simulations

01:36:52 - What Dan is excited about in AI

Links

♾️ An Overview of Catastrophic Risk Paper

https://arxiv.org/pdf/2306.12001.pdf

♾️ Center for AI Safety

https://www.safe.ai/ai-risk

♾️ Representation Engineering

https://www.ai-transparency.org/

♾️ Liv's Ted talk on AI & Moloch

https://www.youtube.com/watch?v=WX_vN1QYgmE

♾️ Norbert Wiener

https://en.wikipedia.org/wiki/Norbert_Wiener

♾️ Reinforcement Learning Textbook

https://inst.eecs.berkeley.edu/~cs188/sp20/assets/files/SuttonBartoIPRLBook2ndEd.pdf

♾️ Richard Posner - Economics Engine

https://plato.stanford.edu/entries/legal-econanalysis/

♾️ More Than a Toy: Random Matrix Models Predict How Real-World Neural Representations Generalize

https://arxiv.org/abs/2203.06176

The Win-Win Podcast:

Poker champion Liv Boeree takes to the interview chair to tease apart the complexities of one of the most fundamental parts of human nature: competition. Liv is joined by top philosophers, gamers, artists, technologists, CEOs, scientists, athletes and more to understand how competition manifests in their world, and how to change seemingly win-lose games into Win-Wins.

Watch the previous episode with Boyan Slat of the Ocean Cleanup here:

https://youtu.be/QEYbLN-LC5k

Credits

♾️ Hosted by Liv Boeree

♾️ Produced & Edited by Raymond Wei

♾️ Audio Mix by Keir Schmidt

  continue reading

34 episodes

Artwork
iconPartager
 
Manage episode 447010467 series 3611008
Contenu fourni par Liv Boeree. Tout le contenu du podcast, y compris les épisodes, les graphiques et les descriptions de podcast, est téléchargé et fourni directement par Liv Boeree ou son partenaire de plateforme de podcast. Si vous pensez que quelqu'un utilise votre œuvre protégée sans votre autorisation, vous pouvez suivre le processus décrit ici https://fr.player.fm/legal.

The rate of AI progress is accelerating, so how can we minimize the risks of this incredible technology, while maximizing the rewards?

Today I am speaking to leading AI researcher Dan Hendrycks — Dan is the founder of Center for AI Safety, and lead advisor to Elon Musk's X.AI. He was also the architect behind the "Mitigating Risks" letter that was signed by Demis Hassabis, Sam Altman, Bill Gates, Yoshua Bengio and many others.

In this conversation we discuss everything from immediate issues like deepfakes, to upcoming risks like malicious use, centralisation of power, regulatory capture and more. In other words, how do we ensure AI ends up a win/win for humanity instead of a lose/lose.

Chapters

00:00:00 - Intro

00:02:14 - Are current laws sufficient?

00:09:41 - Types of AI Risk

00:23:30 - Arms Races

00:39:10 - What happens inside an AI?

00:46:39 - Rogue AI

00:52:22 - Sentient AI

01:07:36 - Risks from Centralization

01:14:45 - Open Source

01:23:02 - AI speeding up systemic risks

01:29:54 - Synthetic Data & Simulations

01:36:52 - What Dan is excited about in AI

Links

♾️ An Overview of Catastrophic Risk Paper

https://arxiv.org/pdf/2306.12001.pdf

♾️ Center for AI Safety

https://www.safe.ai/ai-risk

♾️ Representation Engineering

https://www.ai-transparency.org/

♾️ Liv's Ted talk on AI & Moloch

https://www.youtube.com/watch?v=WX_vN1QYgmE

♾️ Norbert Wiener

https://en.wikipedia.org/wiki/Norbert_Wiener

♾️ Reinforcement Learning Textbook

https://inst.eecs.berkeley.edu/~cs188/sp20/assets/files/SuttonBartoIPRLBook2ndEd.pdf

♾️ Richard Posner - Economics Engine

https://plato.stanford.edu/entries/legal-econanalysis/

♾️ More Than a Toy: Random Matrix Models Predict How Real-World Neural Representations Generalize

https://arxiv.org/abs/2203.06176

The Win-Win Podcast:

Poker champion Liv Boeree takes to the interview chair to tease apart the complexities of one of the most fundamental parts of human nature: competition. Liv is joined by top philosophers, gamers, artists, technologists, CEOs, scientists, athletes and more to understand how competition manifests in their world, and how to change seemingly win-lose games into Win-Wins.

Watch the previous episode with Boyan Slat of the Ocean Cleanup here:

https://youtu.be/QEYbLN-LC5k

Credits

♾️ Hosted by Liv Boeree

♾️ Produced & Edited by Raymond Wei

♾️ Audio Mix by Keir Schmidt

  continue reading

34 episodes

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