[platypii]

Well I guess I have some citations to read later, but intuitively I just have a hard time believing that lack of training data is the problem. There's so incredibly much data available on the internet. If that was the limiting factor, it would just be a matter of throwing more data at T to increase the amount of information in M, but that doesn't help if we haven't found the right machine learning algorithm L. And searching that space is the real challenge of AI. To search that space we either need human experts, huge amounts of computational power to brute force, or some combination thereof. We've tried human experts alone for decades, without much success, so I think it's likely that we will need some computational assistance to find the right algorithms. That's why AI people love throwing around graphs of Moore's law.

[enki]

not if the amount of training data required to learn by example is exponential or even combinatorial. we might not even be in the same ballpark. all data ever recorded on digital media might not be enough to learn even a simple intelligence without assumptions about structure.

a kind of analogous problem is: can you learn how to build a living thing purely from digitally recorded DNA samples, if you don't have access to the internal structure of any living thing? How many dna samples would you need?