But why can’t you make an AI that constantly adjusts the weights as new data becomes available? You wouldn’t have to dump 20 MW of power on it during the training period every year. Instead, just keep running it at a lower power and have it generate and learn simultaneously.
If you are thinking about adjusting the number of weights, that’s also a technique. The issue is that (afaik) it can only be trained through genetic algorithms, which take longer than backpropagation.
But why can’t you make an AI that constantly adjusts the weights as new data becomes available? You wouldn’t have to dump 20 MW of power on it during the training period every year. Instead, just keep running it at a lower power and have it generate and learn simultaneously.
Adjusting the weights is how training works.
If you are thinking about adjusting the number of weights, that’s also a technique. The issue is that (afaik) it can only be trained through genetic algorithms, which take longer than backpropagation.
(This information might be incomplete/incorrect.)