That's currently. The problem I suspect is the form of the input. With AlphaGo/Zero/MuZero, they may be thinking 'fast' but is indistinguishable or better than humans thinking 'slow'.
With AlphaGo/etc there is an internal representation/language being created directly from the board state.
In the case of ChatGPT we are using natural (or programming) language which is once removed from the 'thing' that's discussed. A good illustration of this would be if the AlphaGo folks were trying to beat Atari 2600 games from English descriptions of what's happening onscreen, written out in normal style as if being explained to a person. The machine of course can get this information at high speed so the lack of bandwidth is not the problem. We wouldn't be surprised it doesn't do as well as getting a direct view without human involvement in observation.
As an example AlphaGo was trained on high-level human games and self-play, AlphaZero only learned from self-play. The latter learns faster and plays better, without the human coloring of the data.
Btw, last I heard/read there are still some Atari 2600 games that the machine still can't beat.
DON’T TRUST ChatGPT’s CODE! [youtube / 18 min] https://www.youtube.com/watch?v=YiokTYzA6BI
"He explores the code that ChatGPT can write, and gets ChatGPT to practice Test Driven Development (TDD)."