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Representative_Pop_8 t1_j8iqgft wrote

Reply to comment by amplex1337 in Bing Chat blew ChatGPT out of the water on my bespoke "theory of mind" puzzle by Fit-Meet1359

what is your definiton of understand?

what is inside internally matters little if the results are that it understands something. The example shown by OP and many more, including my own experience clearly shows understanding of many concepts and some capacity to quickly learn from interaction with users ( without needing to reconfigure nor retain the model) though still not as smart as an educated humans.

It seems to be a common misconception , even by people that work in machine learning to say these things don't know , or can't learn or are not intelligent, based on the fact they know the low level internals and just see the perceptions or matrix or whatever and say this is just variables with data, they are seeing the tree and missing the forest. Not knowing how that matrix or whatever manages to understand things or learn new things with the right input doent mean it doesn't happen. In fact the actual experts , the makers of these AI bots know these things understand and can learn, but also don't know why , but are actively researching.

https://www.vice.com/en/article/4axjnm/scientists-made-discovery-about-how-ai-actually-works?utm_source=reddit.com

>Man is still doing the learning and curating it's knowledge base.

didn't you learn to talk by seeing your parents? didn't you go years to school? needing someone to teach you doesn't mean you don't know what you learned.

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RoyalSpecialist1777 t1_j8kwg8b wrote

I am curious how a deep learning system, while learning to perform prediction and classifation is any different than our own brains. It seems increasingly evident that while the goals used to guide training are different but the mechanisms of learning effectively the same. Of course there are differences in mechanism and complexity but what this last year is teaching us is the artificial deep learning systems work to do the same type of modeling we undergo when learning. Messy at first but definitely capable of learning and sophistication down the line. Linguists argue for genetically wired language rules but really this isn't needed - the system will figure out what it needs and create them like the good blank slates they are.

There are a lot of ChatGPT misconceptions going around. For example that it just blindly memorizes patterns. It is a deep learning system (very deep) that, if it helps with classification and prediction, ends up creating rather complex and functional models of how things work. These actually perform computation of a pretty sophisticated nature (any function can be modeled by a neural network). And this does include creativity and reasoning as the inputs flow into and through the system. Creativity as a phenomena might need a fitness function which scores creative solutions higher (be nice to model that one so the AI can score itself) and of course will take awhile to get down but not outside the capabilities of these types of systems.

Anyways, just wanted to chime in as this has been on my mind. I am still on the fence whether I believe any of this. The last point is that people criticize ChatGPT for giving incorrect answers but it is human nature to 'approximate' knowledge and thus incredibly messy. Partially why it takes so long.

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