Interesting. I've always thought the real solution to hallucinations
lies in neurosymbolic AI.
LLMs purely rely on statistical pattern matching with no grounding
in formal logic or symbolic reasoning. You can throw more compute
and data at the problem but you can't guarantee correctness ever.
The neurosymbolic approach combines neural networks for what they're
good at (language, pattern recognition) with symbolic systems for
what they're good at (formal reasoning, provable correctness). The
hallucination can't form in the first place because the symbolic
component enforces correctness at the reasoning level.
The Sovereign Engine sounds more like execution constraints;
Intercepting outputs after the fact rather than grounding the
reasoning process itself. That's still valuable but it's a
different problem. A determined attacker finds the edge case your
constraints don't cover.
Genuinely curious how it works under the hood is there a symbolic
reasoning layer or is the "determinism" coming from the constraint
layer alone?
LLMs purely rely on statistical pattern matching with no grounding in formal logic or symbolic reasoning. You can throw more compute and data at the problem but you can't guarantee correctness ever.
The neurosymbolic approach combines neural networks for what they're good at (language, pattern recognition) with symbolic systems for what they're good at (formal reasoning, provable correctness). The hallucination can't form in the first place because the symbolic component enforces correctness at the reasoning level.
The Sovereign Engine sounds more like execution constraints; Intercepting outputs after the fact rather than grounding the reasoning process itself. That's still valuable but it's a different problem. A determined attacker finds the edge case your constraints don't cover.
Genuinely curious how it works under the hood is there a symbolic reasoning layer or is the "determinism" coming from the constraint layer alone?