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speedywilfork t1_je059or wrote

Reply to comment by acutelychronicpanic in Microsoft Suggests OpenAI and GPT-4 are early signs of AGI. by Malachiian

>I'd love to hear your thoughts on how it can perform well on reasoning tasks its never seen before and reason about what would happen to a bundle of balloons in an image if the string was cut.

I am sure you already know all of this, but It isnt really reasoning, i knows, i knows because it learned. anything that can be learned will eventually be learned by AI, anything and everything. So all of these tasks that appear to be impressive, to me, are just expected. So far AI hasnt done anything that is unexpected. but anything that has a finite outcome, like chess, Go, poker, starcraft, you name it, AI will beat a human, it won't even be close. but it doesnt "reason" it knows all of the possible moves that can ever be played. you show it a picture and ask it what is funny about it. it know that "atypical" things are considered "funny" by humans. so you show it a picture of the Eiffel tower wearing a hat, it can easily determine what is "funny". Even though it doesn't know what "funny" even means.

on the other hand tasks that are open ended and have no finite set of outcomes, like this...

https://news.yahoo.com/soldiers-outsmart-military-robot-acting-214509025.html

AI looks really, really, dumb. because in this scenario, real reasoning is required. a 5 year old child would be able to pick out these soldiers. these are the types of experiments i am interested in, because it will help us to know where AI can reasonably be applied and where it can't.

Why can't an AI pick out these soldiers and a 5 year old can? because an AI just sees objects, a 5 year old understands intent. a 5 year old understands that a person is intending to fool them, so they discern that it is a person inside a cardboard box. There is no way to teach an AI to recognize intent. because intent is an abstraction, and AI can understand abstractions

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acutelychronicpanic t1_je0nzdb wrote

The current generation of AI does not use search to solve problems. That's not how neural networks work.

Go was considered impossible for AI to win for the reasons you suggested it is expected. There are too many possibilities for an AI to consider them all.

You misunderstand these systems fundamentally.

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speedywilfork t1_je2qkbo wrote

>The current generation of AI does not use search to solve problems. That's not how neural networks work.

I never said they used search, it depends on the AI, but many still do use search with other protocols that augment it. they don't rely entirely on search but search is still a part of the algorithm.

>Go was considered impossible for AI to win for the reasons you suggested it is expected. There are too many possibilities for an AI to consider them all.

this is completely false. the original Go algorithm was taught on random games of Go, it had millions of moves built into its dataset. then it played itself millions of times. but the neural networks simply augmented the Monte Carlo Tree Search, it likely could not have won without search.

i don't literally mean it has a database of every potential move ever. i mean it builds this as it plays. however fundamentally it literally knows every move, because at any given point it knows all of the possible moves.

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