Re:A group of ex-NSA and Amazon engineers are building a ‘Gi...
by ivalm on Thursday February 20, 2020 @04:05PM
(#22378609)
> The classic solution to "too little data" is use a simpler and/or less discriminating model. It's still the only one with a good track record.
Kind of, transfer learning is an important tool that people should use more.
Re:A group of ex-NSA and Amazon engineers are building a ‘Gi...
by ska on Thursday February 20, 2020 @04:22PM
(#22378768)
Transfer learning is nothing like a silver bullet. True, it has become an important work around but it's no panacea and the track record is at best mixed.
People already use it quite a lot. More importantly they misuse it a lot. I'd be less concerned with increasing the usage, and more concerned that the people using it understand the implications and trade offs.
Which is part of the reason for the high failure rate.
Good governance and data access for health data is a very hard problem. Good labeling is also hard/expensive in this space.
So there is an incentive for people wanting to do ML/AI without solving above to try any kind of shortcut they can think of. This incentive doesn't help solve any real problems.
The classic solution to "too little data" is use a simpler and/or less discriminating model. It's still the only one with a good track record.