Hi Ed,

Yeah, well, there is opencog (cog prime??) the abstract architecture, and
opencog the actual code base. I presume that the abstract architecture can
be mapped to various nifty algos. (e.g. scatter-gather map-reduce type
broadcasting that you allude to)  although figuring out how to do this well
is not easy (we've tried).  After that, how to get that into the current
code-base is a rather different challenge.

--linas

On Thu, Aug 25, 2016 at 8:43 PM, Ed Pell <[email protected]> wrote:

> Hi Linas, I believe we are basically in agreement. But I will comment
> anyway. I agree that inference and evoking an image give the same
> functional result. Inference by step by step traversing many serial nodes
> is slow. Evoking an image by broadcasting "cat" to the whole memory system
> and potentiating the "cat" related entries followed by broadcasting "mice"
> and super potentiating (or triggering) the relevant entries. The first can
> take thousands of time steps, the second takes about two time steps. Yes,
> additional steps to deal with the several memories thrown up.
>
> I like "compute close to memory" solutions.
>
> Ed
>
> On Thursday, August 25, 2016 at 1:08:35 AM UTC-4, linas wrote:
>>
>>
>>
>> On Tue, Aug 23, 2016 at 7:05 PM, Ed Pell <[email protected]> wrote:
>>
>>> All three of my answers did not come from inference. They came from a
>>> lifetime of experience with cats, boxes, and mice. It was 90% memory bases
>>> with maybe 10% logic/inference to gue the pieces together.
>>>
>>
>> I suppose. A lot of inference/deduction is subconscious.  The word "cat"
>> evokes a huge number of mental images, in a human.  I sketched the computer
>> equivalent of this in the other email -- "evoking an image" is actually an
>> exploration of a connected graph of factoids. We can quibble about whether
>> this is knowledge or memory or inference -- there are algorithmic
>> trade-offs.
>>
>> --linas
>>
>>>
>>>
>>

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