And if your LLM is giving you 100 different answers, then it has been configured to do so. Because instead, it could be configured to never vary at all. It could be 100% reproducible if so desired.
No, it will generate a new hallucination that might be a logical stepwise progression from the question you asked to the answer you gave, but it is not due to any actual internal reasoning being done by the LLM
You don't know either "for sure", but you don't know that the external world exists "for sure" either. It's an insight-free observation, and shouldn't be the focus of anyone's decision-making.
We're not talking about an LLM that is trying to do the job of a human, here
We're talking about an LLM that is trying to give authoritative answers to any question typed into the Google search bar
It's already well past the scale that humans could handle
Talking about human shortcomings when discussing LLMs is a red herring at best, or some kind of deliberate goalpost shifting at worst
Anyone who doubts the usefulness of even these nascent LLMs is fooling themselves. The proof is in the pudding, they already do a great job, even with all their obvious limitations.
Because we interact with computers (which includes LLMs) differently than we do with humans and we hold them to higher standards
Ironically, Google played a large part in this, delivering high quality results to us with ease for many years. At one point Google was the standard for finding high quality information
To the extent that anyone avoids employing these technologies, they will be at a disadvantage to those who do; because these tools just work. Already. Today.
There isn't even room for debate on that issue. Again, the proof is in the pudding. These systems are already successfully, usefully, and correctly answering millions of questions a day. They have failure modes where they produce substandard or even flat out incorrect answers too. They're far from perfect, but they're still incredible tools, even without waiting for the improvements that are sure to come.
An LLM does not have such real world limitations. It will hallucinate nonstop and then create layers of gaslighting explanations to its hallucinations. The problem is that you absolutely must be a domain expert at the LLM’s topic or always go find the facts elsewhere to verify (then why use an LLM?).
So a company like Google using an LLM, is not providing information, it’s doing the opposite. It is making it more difficult and time consuming to find information. But it is then hiding their responsibility behind the model. “We didn’t present bad info, our model did, we’re sorry it told you to turn your recipe into poison…models amirite?”
A human doing that could likely face some consequences.
The human might lie, but they generally don't.
An LLM is always confabulating when it explains how it reached a conclusion, because that information was discarded as soon as it picked a word.
The limitations are not in the same ballpark.
A human can explain their reasoning step by step, if the original reasoning was a System 2, formal, step-by-step process in the first place; otherwise, they're just making shit up after the fact, which feels right, but may or may not be correct (see also the previous paragraph).
Note that it's very rare anyone has an interaction with a human that uses this mode of reasoning - it's unnecessary except in special circumstances, usually math-heavy.
There is no basis for claiming to know that people don't usually make up explanations like this other than when e.g. breaking the process apart and writing it down step by step during. But even then individual decisions are "suspect".
The fact that one human brain is composed in two half brains that each seem to be able to function fairly independently when separated doesn't seem like it changes that much
If this were true textbooks could not work. Given a question, we don't consult random humans but experts of their field. If I have a question on algorithms, I might check a text by Knuth, I wouldn't randomly ask on the street.
> It could be 100% reproducible if so desired.
Reproducible does not mean better. For harder questions, it's often best to generate multiple answers at a higher temperature than to greedily pick the highest probability tokens.