this post was submitted on 27 Jul 2025
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Large language models aren’t designed to be knowledge machines - they’re designed to generate natural-sounding language, nothing more. The fact that they ever get things right is just a byproduct of their training data containing a lot of correct information. These systems aren’t generally intelligent, and people need to stop treating them as if they are. Complaining that an LLM gives out wrong information isn’t a failure of the model itself - it’s a mismatch of expectations.
Neither are our brains.
“Brains are survival engines, not truth detectors. If self-deception promotes fitness, the brain lies. Stops noticing—irrelevant things. Truth never matters. Only fitness. By now you don’t experience the world as it exists at all. You experience a simulation built from assumptions. Shortcuts. Lies. Whole species is agnosiac by default.”
― Peter Watts, Blindsight (fiction)
Starting to think we're really not much smarter. "But LLMs tell us what we want to hear!" Been on FaceBook lately, or lemmy?
If nothing else, LLMs have woke me to how stupid humans are vs. the machines.
There are plenty of similarities in the output of both the human brain and LLMs, but overall they’re very different. Unlike LLMs, the human brain is generally intelligent - it can adapt to a huge variety of cognitive tasks. LLMs, on the other hand, can only do one thing: generate language. It’s tempting to anthropomorphize systems like ChatGPT because of how competent they seem, but there’s no actual thinking going on. It’s just generating language based on patterns and probabilities.