How do people reading on a place like HN still not understand what LLMs are... this is terrifying that this is even a post, and makes you wonder how many startups are having LLMs do deterministic tasks probabilistically and have no idea they're getting nonsense?
To me, the surprise is the other way around: why does a probabilistic process result in such a deterministic result? Not just for ChatGPT, but also for others (see my other comment)?
can't argue with that logic. But jokes aside, if even a consensus of multiple AIs can be this biased, I wonder how many actually important topics are mistakenly treated as settled truth because different AIs aggree on that but it's actually simply because of statistical biases in the training data.
How do people reading on a place like HN still not understand what LLMs are... this is terrifying that this is even a post, and makes you wonder how many startups are having LLMs do deterministic tasks probabilistically and have no idea they're getting nonsense?
To me, the surprise is the other way around: why does a probabilistic process result in such a deterministic result? Not just for ChatGPT, but also for others (see my other comment)?
Got 17 too, with Opus 5, Sonnet 5, GPT5.6 Terra, and Deepsek v4 pro. So it must be the right answer.
can't argue with that logic. But jokes aside, if even a consensus of multiple AIs can be this biased, I wonder how many actually important topics are mistakenly treated as settled truth because different AIs aggree on that but it's actually simply because of statistical biases in the training data.
Lumo, Proton's AI randomly picked 17.
how does it come that every major LLMs seems to have this behavior? same training data?
How do you train on random numbers ?
Just tried this and it picked 17