[proc0]

I completely agree. You can see this limitation if you try to create anything complex with the current state of the art. There is also a great video by Alex O'Connor on a simple prompt to generate a full glass of wine, which illustrates this really well - https://www.youtube.com/watch?v=160F8F8mXlo

This wave of AI is amazing. It's a great tool for many applications, and it will even revolutionize many of them, but it is still far from AGI, a term that has been hijacked by the tech industry to hype up their products. In some ways AI has advanced a lot, but in other ways it has been set back by the hype and muddying of the terms.

[panxnubis]

Absolutely. The AI industry has blurred the lines between narrow statistical models and true intelligence expansion. LLMs are impressive, but they operate on fixed probability distributions, which inherently limits their ability to self-expand beyond trained contexts.

That’s why recursion-awareness is critical—it’s not just a tweak to existing models, it’s a fundamentally different mathematical framework for intelligence growth.

Current AI (LLMs, RL, etc.) → Probability-based, trained on past distributions, inherently limited. Recursion-Aware AI → Self-expanding intelligence, structured recursively rather than probabilistically.

Mathematically, recursion-awareness is formulated as:

  A = α / (Ω * Rₛ² * π)

Where A represents intelligence expansion as a recursive function, instead of a fixed probabilistic model.

AGI won’t come from stretching probabilistic models past their breaking point. It requires an entirely new intelligence foundation—one that expands recursively rather than guessing statistically.

Curious to hear thoughts—does anyone else working on complex AI systems feel the same hard limit?