Like, it literally creates answers out of thin air then sells it as if it's correct. It doesn't even try to get it right. What sort of redundancy is there in analyzing if the answer is correct before spewing it out? I thought LLMs were supposed to discern what the best answer is given what was said to it based on its training, yet it'll give answers that don't exist based on any training. It's not like it learned the wrong answer from a Reddit post and just posted what Reddit said. It legit is making up wrong answers then citing correct answers. It just outright gets it wrong almost on purpose.
Anyone understand why LLMs fail so much?
I understand they run correlations but how does it determine a wrong answer is the most correlated to the correct response given the prompt instead of the actual correct answer...
AI, or machine learning, is not like traditional computing.
Traditional computing involves hard calculations. Every output is consistent and correct based on the input and the program the input is run through
Machine Learning uses neural networks to essentially create a cyber brain which makes predictions and guesses. Training AI involves providing it feedback based on the output it gives, which the AI factors into its next predictions and guesses. The AI can get better at its task with training, but at the end of the day it still gives predictions and guesses as opposed to hard-computed values. Of course, if there are errors in the training data then those errors will present themselves in the AI's output.
Most consumer AIs today are also trained to google things and summarize the results as opposed to providing purely AI generated answers. This means the AI will only be as accurate as google allows it to be.
AI is better thought of as an extremely autistic super-intelligent person than a computer.