This is a concern because several top researchers -- at OpenAI -- have explicitly started that they think you can get AGI by teaching the machine to act as human as possible. But that's a great way to fool ourselves. Just as a duck may fall in love with an animatronic and never realize the deciept.
It's possible they're right, but it's important that we realize how this metric can be hacked.
It is however currently completely unable to "think". It can't make a novel scientific discovery because it can't even add 2 + 2. It can give you the most common answer to "what is 2 + 2" but it's not actually pulling up the calculator app and doing the computation, it's just giving the most probabilistic answer.
And even if it could pull up a predefined list of apps to double check it's work, that still isn't AGI.
One plausible hypothesis is that fixed neural networks cannot be general intelligences, because their capabilities are permanently limited by what they currently are. A general intelligence needs the ability to learn from experience. Training and inference should not be separate activities, but our current hardware is not suited for that.
That's just a timescale issue, if its learned experience of gpt4 is being fed into the model on training gpt5, then gptx (i.e. including all of them) can be said to be a general intelligence. Alien life one may say.
Every problem is a timescale issue. Evolution has shown that.
And no you can't just feed GPT4 into GPT5 and expect it to become more intelligent. It may be more accurate since humans are telling it when conversations are wrong or not. But you will still need advancements in the algorithms themselves to take things forward.
All of which takes us back to lots and lots of research. And if there's one thing we know is that research breakthroughs aren't a guarantee.
I mean timescale as in between two points in time. Between the two points it meets the intelligence criteria you mentioned. Feeding human vetted GPT4 data into GPT5 is no different to a human receiving inputs from its interaction with the world and learning. More accurate means smarter, gradually it's intrinsic world model improves as does reasoning etc.
I agree those are the things that will advance it but taking a step back it potentially meets that criteria even if less useful day to day (given its an abstract viewpoint over time and not at the human level).