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A tartalmat a Steven Parton biztosítja. Az összes podcast-tartalmat, beleértve az epizódokat, grafikákat és podcast-leírásokat, közvetlenül a Steven Parton vagy a podcast platform partnere tölti fel és biztosítja. Ha úgy gondolja, hogy valaki az Ön engedélye nélkül használja fel a szerzői joggal védett művét, kövesse az itt leírt folyamatot https://hu.player.fm/legal.
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#16 - Karl Friston + Singularity: Free Energy and AI

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Manage episode 412584524 series 2964063
A tartalmat a Steven Parton biztosítja. Az összes podcast-tartalmat, beleértve az epizódokat, grafikákat és podcast-leírásokat, közvetlenül a Steven Parton vagy a podcast platform partnere tölti fel és biztosítja. Ha úgy gondolja, hogy valaki az Ön engedélye nélkül használja fel a szerzői joggal védett művét, kövesse az itt leírt folyamatot https://hu.player.fm/legal.

** This is a partnership episode originally recorded in collaboration with Singularity**

This week my guest is professor of neuroscience at University College London, Karl Friston. Viewed by many as one of the world’s most influential neuroscientists, Friston rose to prominence when he pioneered one of the key techniques that allows neuroscientists to analyze brain activity. And as if that wasn’t enough, he has since developed the Free Energy Principle, which some see as monumental to the field as Darwin’s theory of evolution was for biology and genetics.

It’s this work on the Free Energy principle that will be the bulk of our conversation in this episode, and I warn you that this is probably one of the most intellectually challenging conversations we’ve had on the show. To help you navigate this, I want to offer just a quick overview that may aid in understanding the ideas. In essence, Friston’s work roughly states that entities that exist must track information from the world around them, create an internal model of that information, and then use that model to navigate the world in a way that reduces the difference (the error) between what was actually experienced and what one’s model predicted.

While this concept may seem simple on the surface, the actual science behind it is detailed, complex, and holds immense influence for how we develop artificial intelligence.

Learn more about Friston and his work at ⁠fil.ion.ucl.ac.uk/~karl/⁠

**

Host:⁠⁠⁠⁠⁠⁠ Steven Parton⁠⁠⁠⁠⁠⁠ - ⁠⁠⁠⁠⁠⁠LinkedIn⁠⁠⁠⁠⁠⁠ /⁠⁠⁠⁠⁠⁠ Twitter⁠⁠⁠⁠⁠⁠

Music by: Amine el Filali

--- Send in a voice message: https://podcasters.spotify.com/pod/show/curiousapes/message

  continue reading

33 epizódok

Artwork
iconMegosztás
 
Manage episode 412584524 series 2964063
A tartalmat a Steven Parton biztosítja. Az összes podcast-tartalmat, beleértve az epizódokat, grafikákat és podcast-leírásokat, közvetlenül a Steven Parton vagy a podcast platform partnere tölti fel és biztosítja. Ha úgy gondolja, hogy valaki az Ön engedélye nélkül használja fel a szerzői joggal védett művét, kövesse az itt leírt folyamatot https://hu.player.fm/legal.

** This is a partnership episode originally recorded in collaboration with Singularity**

This week my guest is professor of neuroscience at University College London, Karl Friston. Viewed by many as one of the world’s most influential neuroscientists, Friston rose to prominence when he pioneered one of the key techniques that allows neuroscientists to analyze brain activity. And as if that wasn’t enough, he has since developed the Free Energy Principle, which some see as monumental to the field as Darwin’s theory of evolution was for biology and genetics.

It’s this work on the Free Energy principle that will be the bulk of our conversation in this episode, and I warn you that this is probably one of the most intellectually challenging conversations we’ve had on the show. To help you navigate this, I want to offer just a quick overview that may aid in understanding the ideas. In essence, Friston’s work roughly states that entities that exist must track information from the world around them, create an internal model of that information, and then use that model to navigate the world in a way that reduces the difference (the error) between what was actually experienced and what one’s model predicted.

While this concept may seem simple on the surface, the actual science behind it is detailed, complex, and holds immense influence for how we develop artificial intelligence.

Learn more about Friston and his work at ⁠fil.ion.ucl.ac.uk/~karl/⁠

**

Host:⁠⁠⁠⁠⁠⁠ Steven Parton⁠⁠⁠⁠⁠⁠ - ⁠⁠⁠⁠⁠⁠LinkedIn⁠⁠⁠⁠⁠⁠ /⁠⁠⁠⁠⁠⁠ Twitter⁠⁠⁠⁠⁠⁠

Music by: Amine el Filali

--- Send in a voice message: https://podcasters.spotify.com/pod/show/curiousapes/message

  continue reading

33 epizódok

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