Eerke Boiten, Professor of Cyber Security at De Montfort University Leicester, explains his belief that current AI should not be used for serious applications.
An LLM cannot think like you and I. it’s not able to solve entirely new problems. And it doesn’t have a concept of the world - it paints hands without knowing what a hand does.
It is a system which learns the rules of something by means of reinforcement learning to tune the coefficients of its heap of linear equations. It is better than a human in its area. I guess it can be good for tedious, repetitive tasks. Nevertheless it is just a huge coefficient matrix.
But it can only reproduce what is in the training data - you need lots of already solved examples in the training data. It doesn’t work for entirely new problems.
(that’s also the reason, why LLMs don’t give good answers to questions about specialized niche topics. When there are just one or two studies, there just isn’t enough training data for the LLM.)
Right? I see comments all the time about it just being glorified pattern recognition. Well…thats what humans do as well. We recognize patterns and then predict the most likely outcome.
How? You’re focusing on one thing a human does and using it to point to how human like LLMs are, while ignoring everything else humans do. You’re missing the forest for the trees.
The same could be said about every human being…
An LLM cannot think like you and I. it’s not able to solve entirely new problems. And it doesn’t have a concept of the world - it paints hands without knowing what a hand does.
It is a system which learns the rules of something by means of reinforcement learning to tune the coefficients of its heap of linear equations. It is better than a human in its area. I guess it can be good for tedious, repetitive tasks. Nevertheless it is just a huge coefficient matrix.
But it can only reproduce what is in the training data - you need lots of already solved examples in the training data. It doesn’t work for entirely new problems.
(that’s also the reason, why LLMs don’t give good answers to questions about specialized niche topics. When there are just one or two studies, there just isn’t enough training data for the LLM.)
This was already disproven a year ago.
They replaced the training data with an evaluator. (which rates the LLMs output for training?) Interesting, thanks.
Edit: this reminds me of the self evolving (virtual) robot problem, a robot which is rated by an external moderator and improves over time. I.e.: https://www.sciencedirect.com/science/article/pii/S0925231221003982
Right? I see comments all the time about it just being glorified pattern recognition. Well…thats what humans do as well. We recognize patterns and then predict the most likely outcome.
That is one part of many that a human brain does. This is like trying to say the color red is a rainbow, because the rainbow has red in it.
Can you expand on that?
How? You’re focusing on one thing a human does and using it to point to how human like LLMs are, while ignoring everything else humans do. You’re missing the forest for the trees.