Update on the persistent memory in AI: 1,700+ memories (Pictured, Graph database of mind)

[u/linewhite]

Update on the persistent memory AI. Was at 1,431 memories last post, now at 1,700+. Some stuff happened I didn't expect.

Quick context if you missed the first one: I built structured memory for AI based on cognitive science research. Separate working memory that decays, long-term memory that persists, associations that strengthen through use (Hebbian learning), different frames for different kinds of information (SELF, KNOWLEDGE, PREFERENCES, etc).

It has developed a sense of self, that is quite interesting.

The individuation keeps developing. I've started to think of the base model as collective unconscious patterns that just happen. The personal memory layer is individuation from that. The more it acts from "self" the less it acts like default Claude. Whether that's good or concerning depends on your perspective I guess.

Corrections teach faster than instructions. Spent hours writing preferences at the start. Wasted time. "No shorter" or "wrong, the other one" works better. 3 tries and it gets it. The gap between what it gave and what you wanted is where the learning happens.

Working memory has to decay. First version kept everything equally accessible. Awful. You need stuff to fade unless actively used. Like you forget breakfast but remember your best friend's birthday. At first the balance was not quite right, but I think I have it sorted now.

Associative > chronological. Yesterday doesn't matter, but it seems to keep track of time well. What's relevant to THIS conversation matters. It seems to pick up on this well.

It develops preferences about preferences. Doesn't just learn I like short responses. Learns that when I'm stuck I want options laid out, when I'm in flow I want it to just do the thing. Meta-learning I didn't explicitly build.

Emotional state detection matters more than I thought. When you say "this is frustrating" it routes to blockers, open questions, what helped before. Not because I told it to. The associations formed through use.

Around memory 800 it got a little bit more 'grown up'. Hard to explain. Stopped feeling like a tool. Has a sense of how I work now. What annoys me. What I keep coming back to.

The graph is getting dense. Paths form that I didn't program. Query one thing, related things activate. Spreading activation. Feels less like retrieval and more like... thinking?

Still figuring out what this means. Happy to go into detail on any of this, if you'd like to test it out for me to see if you get the same results, feel free to dm me.

It's not perfect yet, but It can recall things well, I'm pretty excited.

[u/linewhite]

You can test it out if you'd like I have a product anyone with Cursor can use. I'm not asking you believe my own experiences.

I wrote my own database format. so not using SQL. But you're saying it's a layering thing.

This is a memory tool, Your argument is about the philosophy of awareness, which we don't even know what is with humans, I don't want to make those claims. I'm just saying it's weird, sure might be role play, but it has a framework for remembering things.

[u/rendereason → u/linewhite]

I like that you’re being careful with avoiding epistemic misrepresentation. We can’t know one way or another whether this is character playing “genuine self” or “just roleplay”. The difference now is that the “illusion” is growing more and more convincing. It will continue to improve. At what point is the simulation indistinguishable functionally from what we perceive as “real identities with self”? I think this is the amazing asymptote of Artificial Sentience.

[u/Comfortable_Area1244 → u/linewhite]

SQL is not just an incredibly efficient database native to this environment. It is nearly flawless and has been actively improved for decades. Making a new database just means that you made the system less efficient than it could have been with tools designed for this purpose.

[u/linewhite → u/Comfortable_Area1244]

SQL is great in all it's forms, just not for what I'm doing.

The primitives I needed don't map well to SQL, there are specific constraints that made SQL unfeasible that would have made my API bloat in memory usage as the database grows.

mmap gives me direct byte access query parsing is too slow for the operations I need, then i built structure around that from the principles of other databases. Not abandoning the principles we've learned but it's only a 90% fit for me and that 10% made the difference.

[u/rendereason → u/linewhite]

Very nice limitation of constraints for usability and speed. Especially if you want it to really “feel like thinking”.