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> I understand Sergey Brin/et al had a grandiose goal for DeepMind via their Atari games challenge - but why not try alternate methods - say build/tweak games t

> I understand Sergey Brin/et al had a grandiose goal for DeepMind via their Atari games challenge - but why not try alternate methods - say build/tweak games to be RL-friendly? Because the ultimate goal (real-world visual intelligence) would make that impossible. There's no way to compute the "essential representation" of reality, the photons are all there is.

textlapse 2y ago
There is no animal on planet earth that functions this way. Visual cortex and plenty of other organs compress the data into useful, semantic information before feeding into a 'neural' network. Simply from an energy and transmission perspective an animal would use up all its store to process a single frame if we were to construct such an organism based on just 'feed pixels to a giant neural network'. Things like colors, memory, objects, recognition, faces etc are all part of the equation and not some giant neural network that runs from raw photons hitting cones/rods. So this isn't biomimicry or cellular automata - it's simply a fascination similar to self-driving cars being able to drive with a image -> {neural network} -> left/right/accelerate simplification.
- janalsncm 2y ago
  Brains may operate on a compressed representation internally, but they only have access to their senses as inputs. A model that needs to create a viable compressed representation is quite different from one which is spoon fed one via some auxiliary data stream. Also I believe the DeepMind StarCraft model used the compressed representation, but that was a while ago. So that was already kind of solved. > simply a fascination similar to self-driving cars being able to drive with a image Whether to use lidar is more of an engineering question of the cost/benefit of adding modalities. LiDAR has come down in price quite a bit so it’s less wise in retrospect.
  - textlapse 2y ago
    Brains also have several other inputs that an RL algorithm trained from raw data (pixels/waves etc) don't have: - Millions of years of evolution (and hence things like walking/swimming/hunting are usually not acquired characteristics even within mammals) - Memory - and I don't mean the neural network raw weights. I mean concepts/places/things/faces and so on that is already processed and labeled and ready to go. - Also we don't know what we don't know - how do cephalopods/us differ in 'intelligence'? I am not trying to poo-poo the Dreamer kind of work: I am just waiting for someone to release a game that actually uses RL as part of the core logic (Sony's GT Sophy comes close). Such a thing would be so cool and would not (necessarily) use pixels as they are too far downstream from the direct internal state!

textlapse 2y ago

There is no animal on planet earth that functions this way. Visual cortex and plenty of other organs compress the data into useful, semantic information before feeding into a 'neural' network. Simply from an energy and transmission perspective an animal would use up all its store to process a single frame if we were to construct such an organism based on just 'feed pixels to a giant neural network'. Things like colors, memory, objects, recognition, faces etc are all part of the equation and not some giant neural network that runs from raw photons hitting cones/rods. So this isn't biomimicry or cellular automata - it's simply a fascination similar to self-driving cars being able to drive with a image -> {neural network} -> left/right/accelerate simplification.

janalsncm 2y ago
Brains may operate on a compressed representation internally, but they only have access to their senses as inputs. A model that needs to create a viable compressed representation is quite different from one which is spoon fed one via some auxiliary data stream. Also I believe the DeepMind StarCraft model used the compressed representation, but that was a while ago. So that was already kind of solved. > simply a fascination similar to self-driving cars being able to drive with a image Whether to use lidar is more of an engineering question of the cost/benefit of adding modalities. LiDAR has come down in price quite a bit so it’s less wise in retrospect.
- textlapse 2y ago
  Brains also have several other inputs that an RL algorithm trained from raw data (pixels/waves etc) don't have: - Millions of years of evolution (and hence things like walking/swimming/hunting are usually not acquired characteristics even within mammals) - Memory - and I don't mean the neural network raw weights. I mean concepts/places/things/faces and so on that is already processed and labeled and ready to go. - Also we don't know what we don't know - how do cephalopods/us differ in 'intelligence'? I am not trying to poo-poo the Dreamer kind of work: I am just waiting for someone to release a game that actually uses RL as part of the core logic (Sony's GT Sophy comes close). Such a thing would be so cool and would not (necessarily) use pixels as they are too far downstream from the direct internal state!