[zer00eyz]

> You're implying that all reality is cultural,

Let's look at two examples of cultural reality:

Fan death in South Korea. Where people believe that a fan running while you sleep can kill you.

The book "Pure, White and Deadly". Where we discredited the author and his findings and spent decades blaming fat, while packing on the pounds with high fructose corn syrup.

An LLM isn't going to find some intrinsic truth, that we are ignoring, in its data set. An LLM isn't going to find issues in the reproducibility / replication crisis. I have not seen one discredit a scientific paper with its own findings.

To be clear LLM's can be amazing tools, but garbage in garbage out still applies.

[sigmoid10]

You are describing the state of LLMs from 2 years ago. Which basically means they were just pre-trained on the internet and then fine tuned to follow a particular instruction format. Current models still use this as a first step, but are then trained a lot using reinforcement learning, which has given them much better skills at reasoning and logic than human tainted data ever could. See how Grok 4 for example still eagerly dismisses all those right wing hoaxes, despite being massively tuned to favour right wingers by its creators carefully selecting pre-training data.

[otabdeveloper4]

You have some sort of very confused idea of what reinforcement learning is. (Which is probably why you're being downvoted.)

[sigmoid10]

I suggest you reed something like the DeepSeek R1 paper, because you and everybody else here seems to have no clue how it works (which is not surprising tbh).