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One thought that came to mind when the author mentioned that GPT-4 seemed to want to use A* was that maybe the problem statement was not formed in a way that wo
by akamoonknight 4y ago
One thought that came to mind when the author mentioned that GPT-4 seemed to want to use A* was that maybe the problem statement was not formed in a way that would get the best response. I'm not entirely sure if this type of back and forth would be useful, but just struck me as interesting to try.
I put the following prompt into ChatGPT (no GPT-4 access for me yet):
*A problem statement is given as follows:
An agent needs to find the best path on a 10x10 tile grid from their current location to a target location. They have a limited movement range of 5 points. Regular tiles cost 1 point to move through, water tiles cost 2 points to move through. Fire tiles cost 1 point to move through, but they should avoid pathing through them even if it means taking a longer path to their destination (provided the path is still within their limited movement range)
Please point out any parts of the problem statement that require clarification.*
Which returned the following response:
Based on the given problem statement, some potential areas that may require clarification are:
Current location and target location: It is not clear if the current location and the target location are fixed or if they change with each problem instance. If they are fixed, it should be mentioned explicitly. If they are not fixed, it should be specified how they are generated for each problem instance.
Movement range: It is not specified whether the agent's movement range is circular or square. If it is circular, it means that the agent can move to any tile that is within a distance of 5 from its current location. If it is square, it means that the agent can move to any tile that is within a range of 5 tiles in both the horizontal and vertical directions. The shape of the movement range needs to be specified.
Fire tiles: The problem statement mentions that the agent should avoid pathing through fire tiles even if it means taking a longer path to their destination, but it is not clear how the agent knows which tiles are fire tiles. It should be specified how the agent perceives and distinguishes fire tiles from regular tiles.
Tile costs: The problem statement mentions that regular tiles cost 1 point and water tiles cost 2 points, but it is not specified what happens if the agent moves diagonally. It should be specified whether diagonal moves are allowed and how much they cost.
Objective function: It is not specified how the "best path" is defined. It should be mentioned whether the objective is to find the shortest path or the path that minimizes some other cost function (e.g., total cost of the path).
- TigeriusKirk 4y agoI really like that approach of asking it what needs to be clarified. That's going straight into my GPT toolbox.
- TylerGlaiel 4y agoInteresting, not a single one of these things it asked for clarifications on are things it actually got wrong in its suggested solution
- copperx 4y agoThis is perhaps one of the most impressive responses I've read. It truly seems like there is some reasoning happening. I don't understand how this can be the output of a generative LLM.
- DaiPlusPlus 4y ago> It truly seems like there is some reasoning happening. I don't understand how this can be the output of a generative LLM Right - this seeming "cognition" is exactly what's so spooky about the whole thing. Here's what spooked me out from yesterday: https://news.ycombinator.com/item?id=35167685 https://news.ycombinator.com/item?id=35167685 - specifically how it determines the divide-by-zero error in this code: https://whatdoesthiscodedo.com/g/6a8f359 https://whatdoesthiscodedo.com/g/6a8f359 ...which demonstrates GPT as being capable of at-least C++ "constexpr"-style compile-time computation, which shouldn't even be possible if one presumes GPT is "just" a giant database storing only multidimensional word similarity scores and sequence distribution from text inference. > a generative LLM I definitely wanted to believe that GPT was "just predicting the next word" - it was somewhat comforting to think of GPT as still being far from being-human or behaving like a real brain does - but that explanation never sat well with me: it was too simplistic and dismissive, and didn't explain the behaviour I was witnessing in GPT. ...so after having read Wolfram's (surprisingly accessible) article on GPT ( https://writings.stephenwolfram.com/2023/02/what-is-chatgpt-doing-and-why-does-it-work https://writings.stephenwolfram.com/2023/02/what-is-chatgpt-... ) it made a lot of things "click" in my head - and enabled me to start to understand why and how GPT is capable of... the surprising things it does; but it also leads me to believe we're (warning: incoming cliche) barely scratching the surface of what we can do: right-away I do believe we're almost at the point where we could simply ask GPT how to adapt it into some kind of early AGI - and we've all heard of what's supposed to follow next... and it really is quite unsettling.