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A tartalmat a John Willis biztosítja. Az összes podcast-tartalmat, beleértve az epizódokat, grafikákat és podcast-leírásokat, közvetlenül a John Willis 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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S4 E6 - Dr. Khai Minh Pham - Redefining Our Understanding of AI

53:29
 
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Manage episode 411966828 series 3568163
A tartalmat a John Willis biztosítja. Az összes podcast-tartalmat, beleértve az epizódokat, grafikákat és podcast-leírásokat, közvetlenül a John Willis 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.

In this episode of Profound, I talk with Dr. Khai Minh Pham, whose unique approach to artificial intelligence challenges conventional paradigms and opens new frontiers in AI research and application. Dr. Pham, with his extensive background in both medicine and artificial intelligence, shares his journey towards creating a distinctive AI framework that prioritizes knowledge over data, steering clear of the traditional data-centric methodologies that dominate the field.

Dr. Pham recounts his early realization of the limitations inherent in human cognitive processes and how this propelled him to explore AI as a means to augment human memory and decision-making capabilities.
Central to this episode is Dr. Pham's critique of the prevailing AI models that rely heavily on data processing and pattern recognition. He introduces his concept of "macro connectionist AI," a system that mimics human reasoning more closely by forming high-level knowledge representations rather than merely processing data inputs. This approach, according to Dr. Pham, not only enhances AI's problem-solving capabilities but also significantly reduces the computational resources required, challenging the current industry trend towards increasingly complex and energy-intensive AI systems.
you can find Dr. Pham's LinkedIn below:
https://www.linkedin.com/in/khai-minh-pham/

  continue reading

66 epizódok

Artwork
iconMegosztás
 
Manage episode 411966828 series 3568163
A tartalmat a John Willis biztosítja. Az összes podcast-tartalmat, beleértve az epizódokat, grafikákat és podcast-leírásokat, közvetlenül a John Willis 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.

In this episode of Profound, I talk with Dr. Khai Minh Pham, whose unique approach to artificial intelligence challenges conventional paradigms and opens new frontiers in AI research and application. Dr. Pham, with his extensive background in both medicine and artificial intelligence, shares his journey towards creating a distinctive AI framework that prioritizes knowledge over data, steering clear of the traditional data-centric methodologies that dominate the field.

Dr. Pham recounts his early realization of the limitations inherent in human cognitive processes and how this propelled him to explore AI as a means to augment human memory and decision-making capabilities.
Central to this episode is Dr. Pham's critique of the prevailing AI models that rely heavily on data processing and pattern recognition. He introduces his concept of "macro connectionist AI," a system that mimics human reasoning more closely by forming high-level knowledge representations rather than merely processing data inputs. This approach, according to Dr. Pham, not only enhances AI's problem-solving capabilities but also significantly reduces the computational resources required, challenging the current industry trend towards increasingly complex and energy-intensive AI systems.
you can find Dr. Pham's LinkedIn below:
https://www.linkedin.com/in/khai-minh-pham/

  continue reading

66 epizódok

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