I agree with the parent post. I can get ChatGPT to solve a basic world problem but if I add a small wrinkle to it that a human would understand it fails hard. Overfitted seems apt.
Stop confusing ChatGPT with GPT-4.
Most common rookie mistake. GPT-4 is way stronger at 'solving problems' than ChatGPT. I was baiting ChatGPT with basic logical or conversion problems, I stopped doing that with GPT-4, since it would take too much effort to beat it.
Dealing with words on the level of their constituent letters is a known weakness of OpenAI’s current GPT models, due to the kind of input and output encoding they use. The encoding also makes working with numbers represented as strings of digits less straightforward than it might otherwise be.
In the same way that GPT-4 is better at these things than GPT-3.5, future GPT models will likely be even better, even if only by the sheer brute force of their larger neural networks, more compute, and additional training data.
(To see an example of the encoding, you can enter some text at https://platform.openai.com/tokenizer. The input is presented to GPT as a series of integers, one for each colored block.)
Second, You're going to have to give specific examples on what a small wrinkle is. I've seen "can't solve variation of common word problem" but that's a failure mode of people too. and if you reword the question so it doesn't bias common priors or even telling it it's making an assumption wrong, it often gets it right.
Yeah it's amazing, but it's not AGI.