10 ms·
Either #1 You can train the model continously #2 the model stops learning #3 it has a submodel which detects you are feeding it false data. Given that peopl
by Fnoord 7y ago
Either
#1 You can train the model continously
#2 the model stops learning
#3 it has a submodel which detects you are feeding it false data.
Given that people change over time, #2 seems unlikely. The question to me is "how advanced is #3?". Another thing I wonder about is how relative are these to eaxh other. At odds?
- nerdponx 7y ago#1 is a well-established technique called "online learning", and I'd bet money that it's how many of these "industrial scale" ML algorithms are trained. #2 makes no sense from a business perspective. #3 is also well-established. This is how Google's Captchas work, for example.