| >> There is no mathematical distinction between different "tasks". Sure there is. For instance, the minimax algorithm is a mathematical model of
optimal behaviour in a specific kind of game (two-player, zero-sum, complete
information games). Performing minimax to dominate such a game is a very
clearly delimited task and that's exactly why a machine can do it in the first
place. More broadly, any "task" can be described mathematically by means of a program
for a given machine. Saying there's no mathematical distinction between
different tasks is like saying you can't write a program that does a specific
thing. >> Insects are indeed tiny. But they are highly specialized. Agreed- see my comment above. However, that on its own doesn't say much. Sure, insects have highly
specialised firmware-style programming. How did they come to have them and how
can we reproduce them? We can't hope to create such programs "by hand" so
we're currently trying to create algorithms that learn them. We're still far
from achieving it though. That neural networks and other learning algorithms can learn all sorts of
different things is true, however you have to train a new instance of an
algorithm for every different thing you want it to learn (what I call a
"task", so a new program). For each instance you need new data (and a lot of
it) another huge chunk of processing power and a long time to train. Then you
have to find a way to combine all the trained models into one ... thing that
can operate as a coherent whole. We haven't even started on the last bit. Just having the technology to create pigments is far from being the same as
creating a Mona Lisa. |