Human mind or even something like Wolfram Alpha can perform reasoning.
https://www.lesswrong.com/posts/qy5dF7bQcFjSKaW58/bad-at-ari...
The provided example directly shows ability in mathematical reasoning by coming up with a novel concept and example case, it is just poor in arithmetic.
Math is not simply arithmetic abilities, you seem unable to comprehend this.
"I want it to come up with a new idea. Its first attempt was to just regurgitate the definition of the set of zero-divisors (a very basic concept), and (falsely) asserted that they formed an ideal (among other false claims about endomorphism rings)."
"I tried a few more times, and it gave a few more examples of ideas that are well-known in ring theory (with a few less-than-true modifications sometimes), insisting that they are new and original."
"This in particular is quite an interesting failure. "
"So there we have it. A new definition. One example (of a 4-cohesive ring) extracted with only mild handholding, and another example (of a 2-cohesive ideal) extracted by cherry-picking, error-forgiveness, and some more serious handholding."
"Some errors (being bad at arithmetic) will almost certainly be fixed in the fairly near future." - and this opinion is based on absolutely nothing.
However, the result often looks the same, which is neat
I don't understand this thinking that it's x because it looks like x(thinking, artistic creativity, etc.). I can prompt Google for incrementally more correct answers to a problem, does that mean there's no difference between "google" and "thought"?
Humans have the capacity to come up with new language, new ideas, and basically everything in our human world was made up by someone.
ChatPT or similar, without any training data, cannot do this. Thus they're simply imitating
Based on the current advances, in about a year we should see the first real-world interaction robot that learns from its environment (probably Tesla or OpenAI).
I'm curious (just leaving it here to see what happens in the future), what will be the excuse of Google this time.
This is again the same situation: Google has supposedly superior tech but not releasing it (or maybe it's as good as Bard...)
Anyway, I think a lot of ongoing conversations have orthogonal arguments. ChatGPT can be both impressive and generate topics broader than the average human while not giving us deeper insight into how human language works.
Art generators are the most obvious example to me. They regularly create depictions of entirely new animals that may look like a combination of known species.
People got a kick out of art AIs struggling to include words as we recognize them. How can we say what looked like gibberish to us wasn't actually part of a language the AI invented as part of the art piece, like Tolkien inventing elvish for a book?
And what do you think of the Mark Twain quote:
“ There is no such thing as a new idea. It is impossible. We simply take a lot of old ideas and put them into a sort of mental kaleidoscope. We give them a turn and they make new and curious combinations. We keep on turning and making new combinations indefinitely; but they are the same old pieces of colored glass that have been in use through all the ages.”
I’d argue ChatGPT can indeed be creative, as it can combine ideas in new ways.
If a system is so lucky that it gives you the right answer 9 times out of 10, it's perhaps not luck anymore.
In your message you say it is gibberish, but I have completely different results and get very good Base64 on super long and random strings.
I frequently use Base64 (both ways) to bypass filters in both GPT-3 and 4/Bing so I'm sure it works ;)
It sometimes make very small mistakes but overall amazing.
At this stage if it can work on random data that never appeared in the training set it's not just luck, it means it has acquired that skill and learnt how to generalise it.
Edit: ok it looks like it can now convert in base64, I'm sure it couldn't when I tested 2 months ago.
It sometimes gets some of the conversion wrong or converts a related word instead of the word you actually asked it to convert. This strongly suggests that it's the actual LLM doing the conversion (and there's no reason to believe it wouldn't be).
This behavior will likely be replicated in open source LLMs soon.