There is something i don’t understand about the htm concept, that is how the Inputs are related between different columns?
In the right side of the image, we can kind of assume there is only one way for the input to travel. But in the case of htm (thousand brain concept) the inputs need to act at specific columns to get the appropriate output. How does the incoming input act at specific columns (sensory columns <-> motor columns) apart from enormous columns that were present in the neocortex?
Turning to TBT, the presentation of a full cup in every column is a bit misleading. I asked Jeff about this in one of the online gatherings and he explained that this was not correct. Ever column sees whatever is presented to it by the portion of the sensory mechanism it is attached to. The lateral connections between columns allows columns to gather consensus that the fragment that the column is seeing is in agreement with the fragments the neighboring columns are seeing to “vote” on the most likely recognition of the possible matches that are stored in that column. The lateral connections between the various sensor streams expands this voting to achieve sensor fusion and better recognition.
If you want to structure the sensory stream into sensory & voting between sub units in a single layer you will be doing some version of lateral voting.
Well, that’s my question, why would you want to structure it that way? I see excitatory lateral connections as positional encoding by key-value pairs in a transformer, the weights / number of synapses per connection are trained vertically. Doesn’t have to be backprop, this training could be Hebbian, but it’s still vertical.
Why not, Hebbian learning is local. And there are models that use apical dendrites as 5-8 layers of backprop. Unless you mean adjacent neurons, but I think those connections are inhibitory.
Likely. We learn both the sensory pattern and accompanying states as a unitary learned local state.
Then again, with a local inhibitory field (basket cells) the lateral excitatory connections are sufficient.