57
Does current AI represent a dead end?
(www.bcs.org)
you are viewing a single comment's thread
view the rest of the comments
view the rest of the comments
this post was submitted on 27 Dec 2024
57 points (86.1% liked)
Technology
60130 readers
2704 users here now
This is a most excellent place for technology news and articles.
Our Rules
- Follow the lemmy.world rules.
- Only tech related content.
- Be excellent to each another!
- Mod approved content bots can post up to 10 articles per day.
- Threads asking for personal tech support may be deleted.
- Politics threads may be removed.
- No memes allowed as posts, OK to post as comments.
- Only approved bots from the list below, to ask if your bot can be added please contact us.
- Check for duplicates before posting, duplicates may be removed
Approved Bots
founded 2 years ago
MODERATORS
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.
I didn't say that at all. What I said was LLMs solve problems just like a human does. Pattern recognition. Then I asked you to provide an example of one thing a human does that doesnt boil down to pattern recognition. The words we speak and type are patterns. The decisions we make are based on patterns we learned in the past. Thats really all I meant by it.
LLMs don’t solve problems. That’s the point being made here. Many other algorithms do indeed solve issues, but those are very niche, as the alogos were explicitly designed for those situations.
While yes, humans excel at pattern recognition, sometimes to the point of it being a problem, there are many things we do that have nothing to do with patterns beyond the fact that they are tangentially involved. Emotions for instance don’t inherently follow patterns. They can, but they aren’t directly tied. Exploration also doesn’t come from pattern recognition.
If you need examples of why people flat out say LLMs aren’t solving problems, look at the recent “how many r’s in strawberry” which has admittedly been “fixed” in many models.
At the end of the day LLMs take in historical data and use it to predict what comes next. Just like humans do. But I guess we can disagree and leave it at that.