Eerke Boiten, Professor of Cyber Security at De Montfort University Leicester, explains his belief that current AI should not be used for serious applications.
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.
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.