Trivially do better than the naive thing I human would do*, sry (e.g. v.s. looking at the sun & seasons, which is what I think human trying to tell time would do to locally improve). Definitely agree can’t trivially do a great job on traditional standards. Wasn’t a carefully chosen example
The broader point was that some subskills can enable better performance at many tasks, which causes spiky performance in humans at least. I see no reason why this wouldn’t apply to nns. (e.g. part of the nn develops a model of something for one task, once it’s good enough discovers that it can use that model for very good performance on an entirely different task—likely observed as a relatively sudden, significant improvement)
[Citation Needed]
Designing an accurate mechanical clock is non-trivial[1], even assuming knowledge of gears
Understatement.
Trivially do better than the naive thing I human would do*, sry (e.g. v.s. looking at the sun & seasons, which is what I think human trying to tell time would do to locally improve). Definitely agree can’t trivially do a great job on traditional standards. Wasn’t a carefully chosen example
The broader point was that some subskills can enable better performance at many tasks, which causes spiky performance in humans at least. I see no reason why this wouldn’t apply to nns. (e.g. part of the nn develops a model of something for one task, once it’s good enough discovers that it can use that model for very good performance on an entirely different task—likely observed as a relatively sudden, significant improvement)