It’s funny reading even expert reports that wrap up with statements like “That will require us to tap into a superpower that can’t be programmed into a robot: imagination.” which are already proving false.
One only has to look at any image generation program to see AI imagination at work. Yes, it’s currently human directed but with advances in internal AI monologues we can see that AI will soon be deliberately daydreaming to find novel solutions.
More and more we are able to transfer the evolved mechanisms of brains directly to advances in machine learning. Using sleep to consolidate weights from one task before learning the next is helping with generalization across tasks.
And the reverse is true as well. Seeing and experimenting with ML models gives us insight into the daily machinations of the wet neural networks we each carry around. That led to the following question.
How much of age related cognitive decline is due to the normally beneficial process of generalization?
When your Mom goes through her sibling’s names before getting to your own, those similar concepts have been grouped together and are less differentiated. Commonality becomes generalization. Names in particular are highly specific, high resolution information that map to things like “that tall blond guy I met at that neighbor’s party”.
Perhaps you visit the Botanic Gardens. How many petals did that flower have? What was its latin name written next to it? Neither fact is as useful as the vague memory that it was purple with a yellow center and pretty, so the petal count and latin name may not even make it to long term memory. As time passes the specific high resolution information about each flower on the trip is consolidated into mosaics of areas you passed through, that flower is now just a purple dot. “Yes, it was beautiful, lots in bloom. You should stop by.” Eventually the whole trip is mostly a dot in the timeline of memory, “Yes, I’ve been to the botanic gardens many times”. You probably remember where it’s located, the general layout, some highlights of visits, and have some very general emotional impressions of how you feel about the place.
All of which is a useful process. Knowing the exact petal counts of thousands of flowers is fairly useless compared “it’s pretty there in June and makes me feel relaxed”. The process of learning is powered by that consolidation. All these things are flowers whether they have 3, 5, or 10 petals.
What expectations then should we have of memory? The more one lives, the greater the surface area grows of subjects we expect to know and remember. Are most memories stored with 5 or 10 years of detail before being compacted into more general knowledge or erased to make room for more? The existence of Highly Superior Autobiographic Memory indicates there could be space for all the detail but that forgetting or at least generalizing is useful for getting through life.
It is theorized that memory storage is similar to holographic storage. A scratch across the surface of digital holographic storage will introduce noise rather than destroying specific information; reducing the fidelity and detail. Whether due to cell death or age related decrease in neuron performance, we expect similar effects on our memory as we age.
With two mechanisms, generalization and aging, that have similar results, how do we tell the difference? Your mom eventually retrieves your name but that may not be the case for more obscure information. If aging is the predominant force, perhaps in our knowledge driven economy we should focus more on understanding the cellular mechanisms and developing treatments. If generalization is stronger we could adapt in other ways: changing our cultural expectations of memory or spending time reviewing memories to curate the level of specificity vs generalization we want in areas of our memory.
In an age where we’re able to store more knowledge and detailed photographic memories outside of our brain perhaps generalization is ok and we should remember the bare minimum.