If you ensemble a bunch of optimizations you get something that behaves like a neuron. Neurons approximate the generator of the layers of 'blurs'. - The distri

If you ensemble a bunch of optimizations you get something that behaves like a neuron. Neurons approximate the generator of the layers of 'blurs'. - The distribution. Such generators have to have separate origin to be truly orthogonal. E.g. evolutionary algorithms for rodents, particle swarm for tool use. If you have orthogonality in your evolution generator, you are not modeling evolution. To my intuition, when you are making orthogonal insertions into data with these constraints you are operating in a regime where computational complexity has exploded several times over what we are used to. Non-spoofed squirrels with screwdrivers would be extremely rare data so having an encoding scheme which allows for that would be a weird flex. Thoughts still baking...