Business, Innovation, and Managing Life (May 31, 2023)
The Stephen Wolfram Podcast - Un pódcast de Wolfram Research
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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: Do you think LLMs will give everyone something akin to a personal McKinsey consultant? - How much efficiency is lost by needing to explain things to a team vs. doing a whole design alone? - With schools ending for the year, what are some ways to continue teaching kids over the summer? Did your summer schedule ever change when your kids would get out of school for summer? - What do you think about machine learning libraries vs. books? Do you think there is a current infrastructure out there for people to make libraries and sell them to users? It's interesting to think about people buying machine learning libraries for their AIs instead of books for their engineers. - What are some simple mathematical tricks and shortcuts it would be good for kids to learn? This might make a useful blog post. Things like "For powers of 10, the little number is how many zeroes come after the 1" and "It's easy to get 10%, you just have to double it to get 20% or find half to get 5%". - If you created an AI emulator of yourself, what would the first three rules of its conduct be? If you could "prompt engineer" an assistant bot for yourself, what would be the first three/most important "rules" you'd tell it to follow? - I'm a software engineer with about eight years of professional experience. I'm interested in transitioning into the field of AI/machine learning. I found it quite difficult to find careers in the marketplace that don't require 5+ years of experience in AI/machine learning. Any advice on how best to make this transition? - Will prompt engineering becoming a legitimate field of study at some point, or is this mainly a trend due to the current systems? - What does it take up front for you to fully invest in a potential idea? Must there be a full proof of concept done prior, with rigorous testing? - Isn't it inherently unwise to seek out AI help, especially in a corporate setting, as it may lead to leakage of information? - Do you find that the key to bring a productive person involves structuring your mind in such a way that you tackle problems in projects? What advice would you have for the sporadic-minded individual?