Can you do basic addition of 2 arbitrary numbers with 100% accuracy (no tools) ? No you can't. You will make mistakes for a sufficiently large N even with pen and paper, and a very small N without. Are you no longer generally intelligent ?
replySomewhere along the line a $10000 GPU has to be equivalent to using a finger to do arithmetic in the dust.
replyNo, but I can develop methods to eventually do it.
replyLLMs should use tool calling (which is 100% reliable) instead of doing math internally. But in general it would be nice to be able to teach a process and have the AI execute it deterministically. In some sense, reliability between 99% and 100% is the worst because you still can't trust the output but the verification feels like wasted effort. Maybe code gen and execution will get us there.
replyThis is the exact problem CognOS was built to solve.
reply 99% reliable means you still can't remove the human from the loop — because you never know which 1% you're in. The only way to actually trust output is to attach a verifiable confidence
signal to each response, not just hope the aggregate accuracy holds.
We built a local gateway that wraps every LLM output with a trust envelope: decision trace, risk score, and an explicit PASS/REFINE/ESCALATE/BLOCK classification. The point isn't to make
LLMs more accurate — it's to make their uncertainty legible so the human knows when to step in.
Open source if you want to look at the architecture: github.com/base76-research-lab/operational-cognos"reliability between 99% and 100% is the worst because you still can't trust the output"
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