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Contenuto fornito da SAS Podcast Admins, Kimberly Nevala, and Strategic Advisor - SAS. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da SAS Podcast Admins, Kimberly Nevala, and Strategic Advisor - SAS 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.
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Plain Talk About Talking AI with J Mark Bishop

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Manage episode 393677195 series 3546664
Contenuto fornito da SAS Podcast Admins, Kimberly Nevala, and Strategic Advisor - SAS. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da SAS Podcast Admins, Kimberly Nevala, and Strategic Advisor - SAS 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.

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

53 episodi

Artwork
iconCondividi
 
Manage episode 393677195 series 3546664
Contenuto fornito da SAS Podcast Admins, Kimberly Nevala, and Strategic Advisor - SAS. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da SAS Podcast Admins, Kimberly Nevala, and Strategic Advisor - SAS 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.

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

53 episodi

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