AI (2014)
blog.samaltman.com
AI (2014)
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Re: AI (2014)
#2Isn't that how LLM models are trained right now? Trying to predict the next word within a "gigantic solution space". Interesting.
Re: AI (2014)
#3Man will do nothing and machine will do everything. That's a bleak world no one is preparing for.
How is that universal basic income scheme coming along?
Re: AI (2014)
#4This is where LLM is currently going. Not really AGI since they can't think like humans, but they can do a lot of things and humans can train them on novel things.
Then human work is changed to figuring out new things and the AI solves all old things, that seems much more fun than most white collar work today.
Re: AI (2014)
#5> (I originally was going to say a computer that plays chess, but computers play chess with no intuition or instinct--they just search a gigantic solution space very quickly.) Isn't that how LLM models are trained right now? Trying to predict the next word within a "gigantic solution space". Interesting.
The reference to pong makes even less sense.
Re: AI (2014)
#6Re: AI (2014)
#7> The most positive outcome I can think of is one where computers get really good at doing, and humans get really good at thinking. If we never figure out how to make computers creative, then there will be a very natural division of labor between man and machine. Man will do nothing and machine will do everything. That's a bleak world no one is preparing for. How is that universal basic income scheme coming along?
Re: AI (2014)
#8Re: AI (2014)
#9Wait, so his keyboard has got a shift key?!
Re: AI (2014)
#10> And maybe we don't want to build machines that are concious in this sense. The most positive outcome I can think of is one where computers get really good at doing, and humans get really good at thinking. If we never figure out how to make computers creative, then there will be a very natural division of labor between man and machine. This is where LLM is currently going. Not really AGI since they can't think like…
But it's not fun to be figuring out new things all the time. Some amount of routine work is necessary to 1) exercise mastery (feels good), and 2) recover energy. This is why a lot of people find agentic coding exhausting and less fun, you're basically always having to be creative (what's the next feature?) or solve the hardest 5% of issues the LLM can't handle.