4 ms·
> 1 billion frames in memory... With such dataset, you have seen practically all realistic possibilities in the short-term. I mean... no? Not even close? Multi
by OskarS 2y ago
> 1 billion frames in memory... With such dataset, you have seen practically all realistic possibilities in the short-term.
I mean... no? Not even close? Multiply the number of game states with the number of inputs at any given frame gives you a number vastly bigger than 1 billion, not even comparable. Even with 20 days of play time to train no, it's entirely likely that at no point did someone stop at a certain location and look to the left from that angle. They might have done from similar angles, but the model then has to reconstruct some sense of the geometry of the level to synthesize the frame. They might also not have arrived there from the same direction, which again the model needs some smarts to understand.
I get your point, it's very overtrained on these particular levels of Doom, which means you might as well just play Doom. But this is not a hash table lookup we're talking about, it's pretty impressive work.
- rvnx 2y agoThis was the basis for the reasoning: The map 1 has 2'518 walkable map units. There are 65536 angles. 2'518*65'536=165'019'648 If you capture 165M frames, you already cover all the possibilities in terms of camera / player view, but probably the diffusion models don't even need to have all the frames (the same way that LLMs don't).
- znx_0 2y agoI think enemy and effects are probably in there
- bee_rider 2y agoDo you have to be exactly on a tile in Doom? I thought the guy walked smoothly around the map.
- cthalupa 2y ago> I thought the guy walked smoothly around the map. Correct. You are certainly not moving between the tiles as discrete units in doom.
- commodoreboxer 2y agoThere's also enemy motion, enemy attacks, shooting, and UI considerations, which make the combinatorials explode. And Doom movement isn't tile based. The map may be, but you can be in many many places on a tile.