10-08-2024, 06:05 PM
I guess anything that trains on part of the data and works calculating results on data that was not used for the training is the start. Then it would be something that doesn't have a known functional ralation between input and output. Its hard to think of a good ''simple' suggestion with:
1] Lots of available data that can be split into training and calculation data that are not the same.
2] Something where there isn't a known functional relationship between input and output.
Without these, for AI to do something valuable, then either:
1] We just reproduce the training data during testing - a simple lookup would work just as well, or:
2] It would be easier to just use the known function.
So this tends to be stuff like image recognition etc which are hard to create simple examples for - tricky!
1] Lots of available data that can be split into training and calculation data that are not the same.
2] Something where there isn't a known functional relationship between input and output.
Without these, for AI to do something valuable, then either:
1] We just reproduce the training data during testing - a simple lookup would work just as well, or:
2] It would be easier to just use the known function.
So this tends to be stuff like image recognition etc which are hard to create simple examples for - tricky!