I know current learning models work a little like neurons but why not just make a sim that works exactly like how we understand neurons work
I know current learning models work a little like neurons but why not just make a sim that works exactly like how we understand neurons work
Actually, neuron-based machine learning models can handle this. The connections between the fake neurons can be modeled as a “strength”, or the probability that activating neuron A leads to activation of neuron B. Advanced learning models just change the strength of these connections. If the probability is zero, that’s a “lost” connection.
Those models don’t have physical connections between neurons, but mathematical/programmed connections. Those are easy to change.
That’s a vastly simplified model. Real neurons can’t be approximated with a couple of weights - each neuron is at least as complex as a multi-layer RNN.