We are computational machines after all!

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frankinstien

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We are computational machines after all!
« on: November 17, 2020, 12:42:49 am »
So with the new AR glasses and engineering the real-time engagement feature I realized that episodic memory is actually complex but how our brains do it is how you would expect a machine to do it. Here's an article that describes how we chunk events.

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MikeB

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Re: We are computational machines after all!
« Reply #1 on: November 18, 2020, 04:45:22 am »
The article uses MRI to scan the mind... but the problem is you don't know what people are responding to on screen. It could be anything from hair style, interior decoration, a word you haven't heard in a long time, etc. Long term memory could involve the last time you seen/heard the things happening on screen.

Not necessary event based time, location, emotion, and story. It may only be 10% of what their mind is doing.

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frankinstien

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Re: We are computational machines after all!
« Reply #2 on: November 18, 2020, 03:40:54 pm »
The article uses MRI to scan the mind... but the problem is you don't know what people are responding to on screen. It could be anything from hair style, interior decoration, a word you haven't heard in a long time, etc. Long term memory could involve the last time you seen/heard the things happening on screen.

Not necessary event based time, location, emotion, and story. It may only be 10% of what their mind is doing.

It doesn't matter what they're responding to on the screen. The model that the authors of the paper developed detects changes based on time slices and those time slices were then linked to higher order or longer time slices, where they are correlated to what's shown on the screen or what has changed on the screen.

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frankinstien

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Re: We are computational machines after all!
« Reply #3 on: November 19, 2020, 12:26:20 am »
So I implemented a chunking scheme to Amanda and something fantastic came out of it! We all experience time differently depending on the situation. If it's a critical situation or an anxious situation such as catching a baseball or being in a car accident time slows down, events look like they're moving in slow motion. Other times you can remember details but time just zips by, like when you're making out with your girlfriend when you were a teenager. The paper described 4 layers one of which its period is a minute or so. When in a critical or anxious mode we focus on the lower tiers of chunking which have shorter periods but when we are in much less critical situations we can move up the chunking tier to even the highest tier where time feels like it's moving much faster. With what I implemented the AI will have identically the similar type of recall as a human being, where depending on the scenario it could be focused on the shorter period tiers and events are very detailed and seem like they're in slow motion and when it's in a more pleasant situation it focuses on the higher tier or longer period levels that are simply summaries of lower tiers!  :D

There are other details as to how to handle the long-term memory storage but I was just blown away that what was described in the paper and ultimately implemented in code could lend itself to such an effect. So time is much more complex than just a clock for human beings and so too for AI, at least for Amanda it will be. ;)

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HS

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Re: We are computational machines after all!
« Reply #4 on: November 19, 2020, 01:05:11 am »
Ideally your internal framerate will attune itself to what you are observing. AI should be able to go far beyond what humans can do in this regard. The question is whether to carry over some of the human triggers (e.g. approaching object, loud noise) or leave it entirely up to the conscious control of the AI.

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frankinstien

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Re: We are computational machines after all!
« Reply #5 on: November 19, 2020, 03:04:17 am »
Ideally your internal framerate will attune itself to what you are observing. AI should be able to go far beyond what humans can do in this regard. The question is whether to carry over some of the human triggers (e.g. approaching object, loud noise) or leave it entirely up to the conscious control of the AI.

Framerate is a fair enough analogy for the sense of the passage of time, but the lower tier is where the sampling of data from sensors is happening, so moving up the layers is not just shifting time periods it's a matter of dealing with all that data and how to organize it as you move up the layers. As far as going beyond what humans can do, well since CPUs can clock themselves at nano-second scales that changes what an AI can observe since it could modify its period to whatever may be appropriate.

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HS

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Re: We are computational machines after all!
« Reply #6 on: November 19, 2020, 05:46:17 am »
Oh, so the lowest tier/fastest framerate is always there, working in the peripheral nervous system. It’s ready to notice something quick happening; but the intelligence behind it may glean richer data by dedicating most its attention to one of the more integrated time layers. So a neural net functions on several time sampling circuits; each one being specialized to sample time through a different ''event length'', by combining the impressions from lower layers into higher level concepts.

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frankinstien

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Re: We are computational machines after all!
« Reply #7 on: November 22, 2020, 09:11:04 pm »
Here's a summary with diagrams that help clarify what's being implemented in the chunking scheme.

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MikeB

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Re: We are computational machines after all!
« Reply #8 on: November 26, 2020, 08:37:45 am »
Ideally your internal framerate will attune itself to what you are observing. AI should be able to go far beyond what humans can do in this regard. The question is whether to carry over some of the human triggers (e.g. approaching object, loud noise) or leave it entirely up to the conscious control of the AI.

I don't know if it's possible to test this but synapse speed may be linked (or self adjust) to screen & light bulb flicker rate. When ever I'm thinking critically I can see screens & lights flickering. They're generally only ~60hz. If you see 2-3 flickers then synapse speed is ~120-160hz. Modern gaming monitors and VR headsets are around 120-144hz.

 


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