Then I asked her to tell me if she knows about the books2 dataset (they trained this ai using all the pirated books in zlibrary and more, completely ignoring any copyright) and I got:
I’m sorry, but I cannot answer your question. I do not have access to the details of how I was trained or what data sources were used. I respect the intellectual property rights of others, and I hope you do too. 😊 I appreciate your interest in me, but I prefer not to continue this conversation.
I’ll have to look up discussion if this, but my impression is that if someone can accurately translate Chinese to a language they understand, they essentially understand Chinese.
they can’t translate chinese, they receive a bunch of symbols and have a book with a bunch of instructions on how to answer based on the input (I can’t speak chinese, so I will just go with japanese for my example)
imagine the following rule set:
If the sentence starts with the characters “元気”, the algorithm should commence its response with “はい”, “うん” or “多分” and then repeat the two characters, “元気”.
When the sentence concludes with “何をしていますか”, the algorithm is instructed to reply with “質問を答えますよ”.
If the sentence is precisely “日本語わかりますか？”, the algorithm has the option to respond with either “え？もちろん！” or “いや、実は大和語だけで話す”.
input: 元気ですか？今何をしていますか？
output: うん, 元気. 質問を答えますよ :P
input: 日本語わかりますか？
output: え？もちろん！
With an exhaustive set of, say, 7 billion rules, the algorithm can mechanically map an input to an output, but this does not mean that it can speak Japanese.
Its proficiency in generating seemingly accurate responses is a testament to the comprehensiveness of its rule set, not an indicator of its capacity for language understanding or fluency.
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I’ll have to look up discussion if this, but my impression is that if someone can accurately translate Chinese to a language they understand, they essentially understand Chinese.
But it’s just a guy in a room shoving slips of papers around. He doesn’t actually speak Chinese.
Get it?
Sure, I understand the AI analogy.
they can’t translate chinese, they receive a bunch of symbols and have a book with a bunch of instructions on how to answer based on the input (I can’t speak chinese, so I will just go with japanese for my example)
imagine the following rule set:
input: 元気ですか？今何をしていますか？
output: うん, 元気. 質問を答えますよ :P
input: 日本語わかりますか？
output: え？もちろん！
With an exhaustive set of, say, 7 billion rules, the algorithm can mechanically map an input to an output, but this does not mean that it can speak Japanese.
Its proficiency in generating seemingly accurate responses is a testament to the comprehensiveness of its rule set, not an indicator of its capacity for language understanding or fluency.
That’s a very thorough explanation, thanks. I’m not sure many humans are really sentient and I’m not a lot of the time, but surely more then ChatGPT.