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I made a video explaining the details of this paper if you are interested! https://youtu.be/H8F6J7mYyz0
Thanks for doing this. I stumbled upon one of your previous videos a while ago and really liked it. I'm super indebted to YouTubers like yourself that take the time to distill and explain complex topics, papers, and new research.
Thought experiment: Is my brain also generating reality without a physics engine and is filling in details that it thinks should be there? If true, what are the advantages/disadvantages of it?
If you manage to not move your eye while paying attention to the finger, you'll find that it doesn't look quite right when you put it over the blind spot.
With your finger you know it should be there, so something finger-like fills the blind spot. If instead of a finger you try with something like a black dot, you'll see it disappear completely.
Thought experiment: Is my brain also generating reality without a physics engine and is filling in details that it thinks should be there? If true, what are the advantages/disadvantages of it?
The other answers to your comment are great but I also want to point out that you can feel your brain doing that if you play some videogames for a long time. You can feel that you develop an intuition for the way the game will behave even if the in-game physics are very different from our real word, showing the plasticity of our brain. If we had a fully hardcoded physics simulator in our head we couldn't "think with…
Cut to a few hours later when they took a break and wanted a snack. So they went to their kitchen and tried to look in their real world fridge, and immediately slammed their head into the door as they tried to stick their head through it without thinking...
This research reminds me of one of their April Fool’s videos [1] with a gaming USB stick that you plug into your computer to offer various gaming enhancements. One of which is a “Ghostplay” feature where an AI program can mimic you after training on your gameplay. I remember that video because it always struck me as not being far off from reality. It’ll make the current set of online game cheats/hacks seem like child…
This research reminds me of one of their April Fool’s videos [1] with a gaming USB stick that you plug into your computer to offer various gaming enhancements. One of which is a “Ghostplay” feature where an AI program can mimic you after training on your gameplay. I remember that video because it always struck me as not being far off from reality. It’ll make the current set of online game cheats/hacks seem like child…
Something similar to what you describe is already being done. Game video is streamed to a Raspberry Pi Zero that sits between the real mouse and the Gaming PC and adjusts the mouse movements. Google for "Valorant RPi0" for videos to see this in action. Here is an excerpt from a now deleted Reddit comment where the setup is described: > "My pi is connected to my pc as a HID device with all the descriptors matching a l…
I predict methods like this will be used to create a simulation environment that approximates the real world. Reinforcement learning folks are running out of game engines win inside of. I believe the best way to transcend this coming limitation will be to take a learning based approach similar to this.
This research reminds me of one of their April Fool’s videos [1] with a gaming USB stick that you plug into your computer to offer various gaming enhancements. One of which is a “Ghostplay” feature where an AI program can mimic you after training on your gameplay. I remember that video because it always struck me as not being far off from reality. It’ll make the current set of online game cheats/hacks seem like child…
But if the AI is functionally indistinguishable from a human player (human-like and undetectable), does it even matter really? https://xkcd.com/810/ (Conversely, if they're _not_ functionally indistinguishable from a human player, then that means it's possible to write an AI or other algorithm to detect them.)
A) It's no longer practical to incorporate into real products given the hardware costs for training and inference. In NLP, large transformer based models can easily occupy a 5 thousand dollar GPU at a paltry 50-60 words per second processing pace.
B) The Research often demonstrates things that existing non-ML toolchains were already reasonable at doing with a better result, and a faster iteration time.
This demo looks like it's replicated the core mechanics of pac-man with worse graphics, 3-4 orders of magnitude higher resource consumption, and undoubtably many odd bugs hidden away from the pretty demo. It even needed the game to exist in the first place! While this is fascinating from the technical and academic perspective, it's hard to be convinced that any gains we see in the field won't be offset by increased hardware/latency costs from a product standpoint.