Gradient Descent Models Are Kernel Machines (Deep Learning)

Thus a new instance and a previously seen example might be similar in an abstract (non-explicit) sense, but that similarity is still incorporated into the kernel. When Einstein invented Special Relativity he was not exactly aping another physical theory he had seen before, but at an abstract level the physical constraint (speed of light constant in all reference frames) and algebraic incorporation of this fact into a description of spacetime (Lorentz symmetry) may have been "similar" to examples he had seen already in simple geometry / algebra.