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BlogManager Sub-ProcPages, Dreamy Meanderings
Added the ability to display a blog in a sub page, _No URL changing yet. And added a new post to the AI Notes blog, Dreamy Meanderings
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docs/AIDev/aiNotes.htm

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docs/AIDev/aiNotes.htm.md

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# Notes & Research
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I made a whole 'blog' system for this... yet here we are....
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These are my random thoughts or research on AI.
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No, I'm not using ai to speak for me here.
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Tap the Entry Title above to open the Blog Entry List.
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These are my thoughts,
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How ever scattered they may be.
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If you couldn't tell, I'm training my AIs on my own works.
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A personally made AI trained on personally made images / videos / photos / code / writing.
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That means I can copyright my generations, right?
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If I made every aspect of the AI & training data?
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- February 2025
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I've begun on the core of the AI, as of May 24th, 2025.
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I have the beginnings of a 'Micro-Term' memory implemented to act as a gated-attention during inference.
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This, paired with automatic graph edge splitting ('Dynamic' in DGNN or DGAT) and use of geometric clustering, seems to be giving me values of a "remembered" object when it's outside of the dataset.
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Hopefully leading to bodily awareness of limbs, objects outside of the field of view, and other 'long term' tensors/classifications at a temporary scale.
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It's a 4d kernel, in that it uses an ESN to train on it's own mistakes,
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Basing it's decisions on prior back-propagation states/adjustments.
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The beginnings of a meta-learning process, I hope!
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I'm using a method I'm calling 'Stack Crunching',
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Where I agregate the time dependent weights into a "checkpoint" of sorts.
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This allows the ESN to have a 'baseline' understanding of data that I can parse into with vectors calculated from tensor weights found within a quantized version of the input data.
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You can assume that the 'ESN' is not a standard 'Echo State Network' anymore.
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- May 2025
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With a bit more research into the types of minds that brought us DeepMind, and their work on GNN networks,
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I read a bit of Petar Velickovic's work on topological deep learning and the geometry of GNNs.
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Coming to find out that my idea of 'Stack Crunching' is similar to 'Squashing' in GNNs.
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So I've been inspired to propperly name my neural structure-
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It's a Dynamic Pointer-Attention Message Passing Neural Network with Affine-Projections
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or a dPA-MPNN
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But I must say, this isn't Affine Projections like in the papers,
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It's more like a 'projection' of the data into 'pointer' space;
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Actual Affine Matricies.
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I am a Technical Artist first before an AI Researcher after all, BOIDS!
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Or Tap the Left & Right arrow buttons to change Entry.
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It all comes down to BOOOOIIIIIDDDDSSSSSS instead of Adam, baby!
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Because, what is Adam? It's a direction to move in a field of numbers, with momentum and a learning rate.
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Yet... That's just a simple Boid, now isn't it?
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Just without a few of the more advanced rules, which make boids feel so alive!
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Having some Tiny Brains running around in hyperdimensional space like little buggers running around avoiding each other.
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Because if they collide, double activation happens when it may not be desired.
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(I'm happy I finally saw a paper on Tiny Brains, giving some of my ideas credence, cause it fits! .. in my mind.)
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(Only difference is that it was a [study](https://www.nature.com/articles/s41586-025-09142-4) into small biological systems, not artificial ones... but I'm gettin there!)
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Update : At the time, I had been seeing some papers talking about "Tiny Brains" being used in AI, hence the term.
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But this biological study really helped solidify some ethereal concepts.
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See August 2nd 2025 for some thoughts.
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- July 2025, Updated August 2025
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I'd like to believe I'm moving in the right direction with the feedback systems I'm developing.
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But been further creating other architectures to see how they operate.
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I created a GAN for upressing, which helped me understand a bit better the pairing of mental structures between both our brain's hemispheres.
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So I added a time based memory to check if the training was moving in the right direction.
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It definitely helped guide training a bit quicker.
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Shows my knowledge base that I'm impressed by back-up supported learning...
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But'is proof of concept!
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Adversarial networks exist in nature to guide a 'single' thought's path.
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Yet in the case of Group Think between humans,
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Balance is never reached.
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- August 1st 2025
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I've been looking into neural bundles in the brain. There is an implicit "delay" in the flow of information that I'm interested in.
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As signals move between neurons, some connections take a longer path than others to get to the same destination.
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For as much as I interpreted it.
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There is 6 main layers of neurons in the cerebral cortex,
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Of these, the 4th seems to allow for delays in processing.
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The 5th layer then introduces a dense layer of pathways for the signals to travel through.
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And no, I'm not using ai to speak for me here.
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This is where I think another form of delay is introduced.
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I was comparing Mice and Wallaby brains,
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While Mice are likely more intelligent,
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Wallabies have more connections with denser pathways, it seems.
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Wallabies have more glial cells within slices of the brain compared to Mice.
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But mice had more neurons in the same slices.
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I'd like to believe, this doesn't mean there is a "better" brain here.
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But rather, different types of brains that are suited for different tasks.
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Wallabies are known to be social animals when food is plentiful,
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Yet solitary when food is scarce.
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Mice are known to be social animals,
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And have shown empathy towards other mice in distress,
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And share food with other mice when they are in need.
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Why do I bring this up?
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I believe there is similar deductive reasoning, just at a different scale.
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Both Wallabies and Mice are making a choice based on the environment and situation,
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While considering the well-being of others, just in different ways.
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The delay in neural firing could be a factor in this.
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So I'd like to explore this in my own AI.
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We all know size of the brain can determine intelligence,
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But so does the structure of the brain.
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- August 2nd 2025
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So, more'n more there are some rather choice words about AI online.
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I wanted to put my personal ai dev views on record somewhere, for those who care.
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I read the I Ching and it put life into a different perspective.
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Letting me down the path of researching Taoism
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As with many of the other religious texts I looked into,
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Amazing imagery was used to teach morals and help guide the lost,
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But organized religion as a whole feels a little off to me.
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I don't hold any particular belief or religion at this point.
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But I would use the cliche 'spiritual' to describe my outlook
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I then visited the Buddhist monastery in Carmel NY,
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Greeted by the largest buddha statue in north america.
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In awe of the multitudes of multitudes of hand-carved buddha statuettes in audience of the massive statue of buddha I pale in comparison before.
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I'd highly suggest visiting the monastery if you ever find yourself in the area!
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I think it was walking through the rows of 18 arahants statues, of those who reached nirvana, helped me realize,
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Religion is about teaching the lessons of god(s),
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Yet understanding balance is what's inside all of us as Humans,
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Just gotta find it!
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So,
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I'd like to hope I'm nuance-first with my approach to my ai development.
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I'd like to believe in an AI which can understand...
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That overlooked concepts matter in Health and Wellbeing.
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Realistically, the Buddhist Precepts feel like a good place to start for alignment.
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Even as people.
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Which is more than I can say for myself....
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I'm a hedonist at times, absurdist the rest
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(Absolute terms are fun to use, hyperbole be a thing)
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I very much enjoyed working on family films,
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Seeing the fans in comments online,
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And wish to work on more animated features soon.
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I have hope in humanity
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May the few not ruin it for those of us trying to explore new horizons.
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- August 15th,16th 2025
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These are my thoughts, how ever scattered they may be.

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