[quote="bkutt, post:1, topic:3000, full:true"]
One thing I was thinking was feeding the predictions that come out of the TM
algorithm right back into the TM's input. This would be like assuming the
predictions were 100% correct and then seeing what cells would get put in a
predictive state next if those first order predictions were 100% correct. This
could be repeated n times to get n high-order cellular activation predictions.
[/quote]
Definitely an interesting problem. The issue with predictions from predictions
is that since the TM makes multiple simultaneous predictions (it predicts
unions of possible futures) your SDRs will get denser and denser with each
timestep, resulting in less and less precise predictions. However, for any one
level of temporal abstraction, maybe that's exactly what should happen.
In the long run the theory predicts we'll do this by representing time more and
more coarsely at larger scales up the hierarchy. Then at each level you can
make predictions at that granularity that get less and less precise as you go
multiple timesteps in the future, but you can still predict out to whatever
duration you want if you pick a high enough region.
But of course the theory hasn't yet fleshed out the method of temporal
abstraction up the hierarchy ("temporal pooling"). That said, some recent
threads on the forum have some promising work in this direction.
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