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Future of Science & Technology Q&A (March 22, 2024)

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Manage episode 433328569 series 1692780
Content provided by Wolfram Research. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Wolfram Research or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

Stephen Wolfram answers questions from his viewers about the future of science and technology as part of an unscripted livestream series, also available on YouTube here: https://wolfr.am/youtube-sw-qa

Questions include: Do you have any plans, and when can we expect to see a S. Wolfram AI chatbot with voice? - Do you think each AI iteration of the person would be similar at the start and then diverge in personality/intelligence as they continued to "live" and develop? - ​​Are you comfortable with the average quality and correctness of AI-generated answers and commentary? - ​​Due to the success of nature-inspired computing, I am really wondering if like our best bet is creating full-on human replicas, meaning similar learning experiences/processes... - I like the architecture of having many bots with like a base that confer and like upload their findings to a global knowledgebase, then disperse on like new assignments or what have you after returning. - ​​Do you think human brains compress data in a lossy way, and will future AI brains also have to use lossy compression methods to be more human like? Or would AI perfect memory be more desirable? - ​​Could an element printer theoretically work, e.g. one feeds it with carbon atoms and it prints out an arbitrary element? - ​​Can you explain the quantum LLMs idea, and what advantage exists in applying multi-computation, if any, to LLMs? - What would an AI look like that is rewarded based on questioning rather than answering? - ​​What do you think will happen when we understand prime numbers to their fullest? And when we can translate this knowledge to AI?

  continue reading

420 episodes

Artwork
iconShare
 
Manage episode 433328569 series 1692780
Content provided by Wolfram Research. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Wolfram Research or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

Stephen Wolfram answers questions from his viewers about the future of science and technology as part of an unscripted livestream series, also available on YouTube here: https://wolfr.am/youtube-sw-qa

Questions include: Do you have any plans, and when can we expect to see a S. Wolfram AI chatbot with voice? - Do you think each AI iteration of the person would be similar at the start and then diverge in personality/intelligence as they continued to "live" and develop? - ​​Are you comfortable with the average quality and correctness of AI-generated answers and commentary? - ​​Due to the success of nature-inspired computing, I am really wondering if like our best bet is creating full-on human replicas, meaning similar learning experiences/processes... - I like the architecture of having many bots with like a base that confer and like upload their findings to a global knowledgebase, then disperse on like new assignments or what have you after returning. - ​​Do you think human brains compress data in a lossy way, and will future AI brains also have to use lossy compression methods to be more human like? Or would AI perfect memory be more desirable? - ​​Could an element printer theoretically work, e.g. one feeds it with carbon atoms and it prints out an arbitrary element? - ​​Can you explain the quantum LLMs idea, and what advantage exists in applying multi-computation, if any, to LLMs? - What would an AI look like that is rewarded based on questioning rather than answering? - ​​What do you think will happen when we understand prime numbers to their fullest? And when we can translate this knowledge to AI?

  continue reading

420 episodes

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