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Business, Innovation and Managing Life (July 17, 2024)

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Manage episode 439767291 series 3303208
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 business, innovation, and managing life as part of an unscripted livestream series, also available on YouTube here: https://wolfr.am/youtube-sw-business-qa

Questions include: I loved the discussion with a robot! Based on that talk, how do you imagine a future of robots in business? (Robot coworkers, bosses, assistants, etc.) Will robots be able to effectively communicate with their human companions and vice versa? - What business ideas can you think of for useful AI applications? How can we make building your own AI for your own purposes easy and affordable (such as having a bot that helps you find weekly coupons and savings for grocery trips, or for mapping ideal travel times)? - What do you think of "robots" remotely operated by humans as a precursor to autonomous robots? A new spin on outsourced blue-collar labor? - I believe that another crucial thing is that not only should technologies adapt to people's demands, but humans should quickly adapt to technology's demands in the field. Just recall how weird the computer mouse was for us 30–40 years ago. - ​​It is very useful for us humans to understand what the AI knows when it outputs its LLM computations. - ​​Maybe some layered hybrid architecture could work with LLMs providing the base, so to speak, while the other modules do more to correct what is there, perhaps? - ​​What's the gold in AI, LLMs, etc.? Is there some simpler algorithm that can learn, instead of big neural networks? Like trying to find gold in a goldmine? - What do you make of the apparent disconnect between the heavy capital expenditure into AI infrastructure vs. the lagging revenues from applications at the present time? Are we in for a "2000 telecom/fiber"-like setback? - For full robot integration into human society, will we see robot "coffee shops" where robots will be able to go and refuel/charge? What business opportunities would working robots open up? - How was your annual summer of professoring? Kudos to all the student projects! - Will you let future robots enroll in the Summer School?

  continue reading

420 episodes

Artwork
iconShare
 
Manage episode 439767291 series 3303208
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 business, innovation, and managing life as part of an unscripted livestream series, also available on YouTube here: https://wolfr.am/youtube-sw-business-qa

Questions include: I loved the discussion with a robot! Based on that talk, how do you imagine a future of robots in business? (Robot coworkers, bosses, assistants, etc.) Will robots be able to effectively communicate with their human companions and vice versa? - What business ideas can you think of for useful AI applications? How can we make building your own AI for your own purposes easy and affordable (such as having a bot that helps you find weekly coupons and savings for grocery trips, or for mapping ideal travel times)? - What do you think of "robots" remotely operated by humans as a precursor to autonomous robots? A new spin on outsourced blue-collar labor? - I believe that another crucial thing is that not only should technologies adapt to people's demands, but humans should quickly adapt to technology's demands in the field. Just recall how weird the computer mouse was for us 30–40 years ago. - ​​It is very useful for us humans to understand what the AI knows when it outputs its LLM computations. - ​​Maybe some layered hybrid architecture could work with LLMs providing the base, so to speak, while the other modules do more to correct what is there, perhaps? - ​​What's the gold in AI, LLMs, etc.? Is there some simpler algorithm that can learn, instead of big neural networks? Like trying to find gold in a goldmine? - What do you make of the apparent disconnect between the heavy capital expenditure into AI infrastructure vs. the lagging revenues from applications at the present time? Are we in for a "2000 telecom/fiber"-like setback? - For full robot integration into human society, will we see robot "coffee shops" where robots will be able to go and refuel/charge? What business opportunities would working robots open up? - How was your annual summer of professoring? Kudos to all the student projects! - Will you let future robots enroll in the Summer School?

  continue reading

420 episodes

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