Re:Why train when you can optimize?
by viraptor on Saturday April 30, 2022 @01:43AM
(#31213649)
> And then your NN can't represent anything else than periodic functions
Significant parts of x+sin are close to linear. You don't need to use this activation as the result layer either. Why would we lose anything?
> If we had to build separate programs for each product requirements variations
We pretty much do? We use both extremely generic frameworks both in technical sense (.net) and organisational (sap). But we also have software written to specific requirements where needed (there's millions of very specific ways to invoice someone, companies get invoicing platforms written just for them from scratch). There's space for both approaches.
Significant parts of x+sin are close to linear. You don't need to use this activation as the result layer either. Why would we lose anything?
> If we had to build separate programs for each product requirements variations
We pretty much do? We use both extremely generic frameworks both in technical sense (.net) and organisational (sap). But we also have software written to specific requirements where needed (there's millions of very specific ways to invoice someone, companies get invoicing platforms written just for them from scratch). There's space for both approaches.