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I'd say this is outdated. Since its publication, transfer learning has really started to pick up speed. Taking a model trained in one subject, and reapplying i
by huffmsa 7y ago
I'd say this is outdated. Since its publication, transfer learning has really started to pick up speed.
Taking a model trained in one subject, and reapplying it to build out new vertical is pretty much how children learn new things.
We'll have models using models to train new models sooner rather than later.
If a program can create it's own curve functions and decide which one to use to evaluate a problem, is it that much different than a brain?
- jgalt212 7y agoIsn't transfer learning just a faster way to fit a curve by starting with a curve that's partially fit instead of a random vector. So under this interpretation, transfer learning is also "curve fitting."
- huffmsa 7y agoIt is. But progress has been made taking models fit on pretty different topics and using them for something tangentially related. And that's exactly what humans do. You don't start from zero when you learn to paint if you already know how to draw. You take another model of behavior and use it as a baseline to develop your painting behavior. The fundamental thing that you can do that the computer can't right now is decide when you need a new model, when to use an existing one and when to transfer off of something.