That’s an interesting take, I didn’t know software could be inspired by other people’s works. And here I thought software just did exactly as it’s instructed to do. These are language models. They were given data to train those models. Did they pay for the data that they used to train for it, or did they scrub the internet and steal all these books along with everything everyone else has said?
AIs in their training stages are simply just running extreme statistical analysis on the input material. They’re not “learning” they’re not “inspired” they’re not “understanding”
The anthropomorphism of these models is a major problem. They are not human, they don’t learn like humans.
The anthropomorphism of these models is a major problem.
People attributing any kind of person hood or sentience is certainly a problem, the models are fundamentally not capable of that (no loops, no hidden thought). At least for now. However what you are doing isn’t really much better, just utterly wrong in the opposite direction.
Those models are very definitely do “learn” and “understand” by every definition of the word. Simply playing around with that will quickly show that and it’s baffling that anybody would try to claim otherwise. Yes, there are limits to what they can understand and there are plenty things that they can’t do, but the amount of questions they can answer goes far beyond what is directly in the training data. Heck, even the fact that they hallucinate is proof that they understand, since it would be impossible to make completely plausible, but incorrect, stuff up without having a deep understanding of the topics. Also humans make mistakes too and they’ll also make stuff up, so this isn’t even anything AI specific.
Hallucinations happen when there’s gaps in the training data and it’s just statistically picking what’s most likely to be next. It becomes incomprehensible when the model breaks down and doesn’t know where to go. However, the model doesn’t see a difference between hallucinating nonsense and a coherent sentence. They’re exactly the same to the model.
The model does not learn or understand anything. It statistically knows what the next word is. It doesn’t need to have seen something before to know that. It doesn’t understand what it’s outputting, it’s just outputting a long string that is gibberish to it.
I have formal training in AI and 90%+ of what I see people claiming AI can do is a complete misunderstanding of the tech.
It doesn’t understand what it’s outputting, it’s just outputting a long string that is gibberish to it.
Which is obviously nonsense, as I can ask it questions about its output. It can find mistakes in its own output and all that. It obviously understands what it is doing.
They weren’t given data. They were shown data then the company spent tens of millions of dollars on cpu time to do statistical analysis of the data shown.
And here I thought software just did exactly as it’s instructed to do.
AI isn’t software. Everything the AI knows is from the books. There is no human instructing the AI what to do. All the human does is build the scaffolding to let the AI learn, everything else is in the data.
That’s an interesting take, I didn’t know software could be inspired by other people’s works. And here I thought software just did exactly as it’s instructed to do. These are language models. They were given data to train those models. Did they pay for the data that they used to train for it, or did they scrub the internet and steal all these books along with everything everyone else has said?
Well, now you know; software can be inspired by other people’s works. That’s what AIs are instructed to do during their training phase.
Software cannot be “inspired”
AIs in their training stages are simply just running extreme statistical analysis on the input material. They’re not “learning” they’re not “inspired” they’re not “understanding”
The anthropomorphism of these models is a major problem. They are not human, they don’t learn like humans.
People attributing any kind of person hood or sentience is certainly a problem, the models are fundamentally not capable of that (no loops, no hidden thought). At least for now. However what you are doing isn’t really much better, just utterly wrong in the opposite direction.
Those models are very definitely do “learn” and “understand” by every definition of the word. Simply playing around with that will quickly show that and it’s baffling that anybody would try to claim otherwise. Yes, there are limits to what they can understand and there are plenty things that they can’t do, but the amount of questions they can answer goes far beyond what is directly in the training data. Heck, even the fact that they hallucinate is proof that they understand, since it would be impossible to make completely plausible, but incorrect, stuff up without having a deep understanding of the topics. Also humans make mistakes too and they’ll also make stuff up, so this isn’t even anything AI specific.
Yeah, that’s just flat out wrong
Hallucinations happen when there’s gaps in the training data and it’s just statistically picking what’s most likely to be next. It becomes incomprehensible when the model breaks down and doesn’t know where to go. However, the model doesn’t see a difference between hallucinating nonsense and a coherent sentence. They’re exactly the same to the model.
The model does not learn or understand anything. It statistically knows what the next word is. It doesn’t need to have seen something before to know that. It doesn’t understand what it’s outputting, it’s just outputting a long string that is gibberish to it.
I have formal training in AI and 90%+ of what I see people claiming AI can do is a complete misunderstanding of the tech.
Than why do you keep talking such bullshit? You sound like you never even tried ChatGPT.
Yes, that’s understanding. What do you think your brain does differently? Please define whatever weird definition you have of “understand”.
You are aware of Emergent World Representations? Or have a listen to what Ilya Sutskever has to say on the topic, one of the people behind GPT-4 and AlexNet.
Which is obviously nonsense, as I can ask it questions about its output. It can find mistakes in its own output and all that. It obviously understands what it is doing.
They weren’t given data. They were shown data then the company spent tens of millions of dollars on cpu time to do statistical analysis of the data shown.
A computer being shown data is a computer being given data. I don’t understand your argument.
The data is gone by the time a user interacts with the AI. ChatGPT has no access to any books.
AI isn’t software. Everything the AI knows is from the books. There is no human instructing the AI what to do. All the human does is build the scaffolding to let the AI learn, everything else is in the data.
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