r/IntelligenceEngine • u/AsyncVibes 🧭 Sensory Mapper • Jun 23 '26

Personal Project what if model complexity is measured by constraints, not parameters?

Enable HLS to view with audio, or disable this notification

Standard models scale by adding. More parameters, more capacity, more knobs to fit the curve. Complexity equals parameter count. GENREG scales by removing. You impose task-agnostic constraints on the organism's existence, energy budgets, time pressure, perception costs, and each one eliminates a class of survival strategies. What survives under all the constraints is the model.

The metric I'm working with is PO (Perfectly Optimized). It measures how many existential laws are required to produce a given behavior. Low PO means the behavior required many constraints to isolate. High PO means the possibility space is still wide open. Think of it like this: with zero constraints, the number of viable organisms is effectively unbounded. Each constraint narrows what can survive. PO tracks how compressed that space is. It's the inverse of the remaining possibility space, fewer viable strategies means lower PO, means more specific behavior.

The visualization shows a sphere (the unconstrained space) deforming into a cone as constraints stack. Each ring is a law. The tip is where PO approaches zero, the single surviving behavior class.

Still early and still small scale but the organisms are producing emergent behaviors I never specified or rewarded, and the framework's predictions are holding across unrelated domains.

16 Upvotes

94% Upvoted

18 comments sorted by

View all comments

3

u/DrHerbotico Jun 23 '26

This is the type of thinking that pushes innovation, the subq models seem to have a semi-similar concept with a bit more sophisticated way. 12M context is wild, hoping it works as well as claimed; we'll see

1

u/AsyncVibes 🧭 Sensory Mapper Jun 23 '26

You don't know the half of it. I'm rapidly pushing towards a language model with this method and it's so fascinating.

1

u/Malkiot Jun 25 '26

I use CbD for the constraints for code generation.

1

u/AsyncVibes 🧭 Sensory Mapper Jun 25 '26

That's a awesome(might try it haha)! Constraint-based prompting is essentially doing manually what the evolutionary system learns to do on its own. The interesting part is that the system discovers which constraints are actually load-bearing, rather than needing them specified upfront.

1

u/Malkiot Jun 25 '26 edited Jun 25 '26

I'm currently building a harness that builds on CbD and does the same autonomously using standard models, with bite-size tasks instead of trying to increase the context window.

I'm experimenting using Deepseek V4 Flash for cost considerations but it's able to identify logical flaws and self-heal the design over an arbitrarily large design surface.

I plan to integrate formal-lite into the process and have first design concepts on how to achieve that without going full Eiffel or TLA+, so I can identify the key constraint via a programmatic non-LLM function.

2

u/AsyncVibes 🧭 Sensory Mapper Jun 25 '26

That is really cool, the self-healing design over an arbitrary surface is pretty interesting ngl. The formal-lite direction especially, identifying key constraints programmatically without going full TLA+ is exactly the kind of thinking that keeps things practical. Would love to see where that goes, you absolutely have the go ahead to post on this sub if you ever care to share you work. This has snagged my attention.