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n4r9 3 hours ago

The concern for me about LLMs confabulating is not that humans don't do it. It's that the massive scale at which LLMs will inevitably be deployed makes even the smallest confabulation extremely risky.

NiloCK 2 hours ago | parent [-]

I don't understand this. Many small errors distributed across a large deployment sounds a lot like normal mode of error prone humans / cogs / whatevers distributed over a wide deployment.

xmprt 2 hours ago | parent | next [-]

There's a difference between 1000 diverse humans with varied traits making errors that should cancel out because of the law of large numbers vs 10 AI with the same training data making errors that would likely correlate and compound upon each other.

GolfPopper 2 hours ago | parent | prev | next [-]

I have yet to see a comparison of human vs. LLM confabulation errors at scale.

"Many small errors" makes a presumption about LLM confabulation/hallucination that seems unwarranted. Pre-LLM humans (and our computers) have managed vast nuclear arsenals, bioweapons research, and ubiquitous global transport - as a few examples - without any catastrophic mistakes, so far. What can we reasonably expect as a likely worst case scenario if LLMs replacing all the relevant expertise and execution?

krainboltgreene an hour ago | parent | prev [-]

Your project vue-skuilder has 6 github action steps devoted to checking the work you do before it's allowed to go out. You do not trust yourself to get things right 100% of the time.

I am watching people trust LLM-based analysis and actions 100% of the time without checking.