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SAS Podcast Admins, Kimberly Nevala, and Strategic Advisor - SAS에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 SAS Podcast Admins, Kimberly Nevala, and Strategic Advisor - SAS 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.
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Plain Talk About Talking AI with J Mark Bishop

1:06:32
 
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Manage episode 393677195 series 3546664
SAS Podcast Admins, Kimberly Nevala, and Strategic Advisor - SAS에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 SAS Podcast Admins, Kimberly Nevala, and Strategic Advisor - SAS 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

Professor J Mark Bishop reflects on the trickiness of language, how LLMs work, why ChatGPT can’t understand, the nature of AI and emerging theories of mind.

Mark explains what large language models (LLM) do and provides a quasi-technical overview of how they work. He also exposes the complications inherent in comprehending language. Mark calls for more philosophical analysis of how systems such as GPT-3 and ChatGPT replicate human knowledge. Yet, understand nothing. Noting the astonishing outputs resulting from more or less auto-completing large blocks of text, Mark cautions against being taken in by LLM’s disarming façade.

Mark then explains the basis of the Chinese Room thought experiment and the hotly debated conclusion that computation does not lead to semantic understanding. Kimberly and Mark discuss the nature of learning through the eyes of a child and whether computational systems can ever be conscious. Mark describes the phenomenal experience of understanding (aka what it feels likes). And how non-computational theories of mind may influence AI development. Finally, Mark reflects on whether AI will be good for the few or the many.

Professor J Mark Bishop is the Professor of Cognitive Computing (Emeritus) at Goldsmith College, University of London and Scientific Advisor to FACT360.

A transcript of this episode is here.

  continue reading

54 에피소드

Artwork
icon공유
 
Manage episode 393677195 series 3546664
SAS Podcast Admins, Kimberly Nevala, and Strategic Advisor - SAS에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 SAS Podcast Admins, Kimberly Nevala, and Strategic Advisor - SAS 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

Professor J Mark Bishop reflects on the trickiness of language, how LLMs work, why ChatGPT can’t understand, the nature of AI and emerging theories of mind.

Mark explains what large language models (LLM) do and provides a quasi-technical overview of how they work. He also exposes the complications inherent in comprehending language. Mark calls for more philosophical analysis of how systems such as GPT-3 and ChatGPT replicate human knowledge. Yet, understand nothing. Noting the astonishing outputs resulting from more or less auto-completing large blocks of text, Mark cautions against being taken in by LLM’s disarming façade.

Mark then explains the basis of the Chinese Room thought experiment and the hotly debated conclusion that computation does not lead to semantic understanding. Kimberly and Mark discuss the nature of learning through the eyes of a child and whether computational systems can ever be conscious. Mark describes the phenomenal experience of understanding (aka what it feels likes). And how non-computational theories of mind may influence AI development. Finally, Mark reflects on whether AI will be good for the few or the many.

Professor J Mark Bishop is the Professor of Cognitive Computing (Emeritus) at Goldsmith College, University of London and Scientific Advisor to FACT360.

A transcript of this episode is here.

  continue reading

54 에피소드

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