A very good point. For anyone not familiar with anterograde amnesia, the classical case is patient H.M. (https://en.wikipedia.org/wiki/Henry_Molaison), whose condition was researched by Brenda Milner.
> Near the end of his life, Molaison regularly filled in crossword puzzles.[16] He was able to fill in answers to clues that referred to pre-1953 knowledge. As for post-1953 information, he was able to modify old memories with new informations. For instance, he could add a memory about Jonas Salk by modifying his memory of polio.[2]
The nature of memory is so cool, the idea that there are completely different systems governing the creation of wholesale "new" memories and the modification of existing concepts is fascinating to me because those things really do "feel" different in a qualitative sense, but having evidence that you're physically doing something different in those cases is really cool.
I thought maybe people would be curious to read about how we came to understand the condition and the history behind it, as well as any associated information. Forgive me for such a deep transgression as this assumption.
All that needed to be conveyed was that there are humans who cannot create new memories. That is enough to pose the philosophical question about these models having intelligence. Anything more is just adding an anecdote that isn't necessary.
lol, as if pointing at a wikipedia article (without any relevant discussion of the contents therein) is some kind of conversational excellence.
Or perhaps you were referring to the impact of the two in that the "sledgehammer" of "they can't make new memories" is a lot more effective than the tiny scalpel of "if you do a wikipedia search this is a single one of the relevant articles"
The extra information is that he is the canonical case which defined our clinical understanding of the condition. Not just a "single relevant article."
I pulled it up because I was familiar with this fact.
Nobody else in the thread is making an argument that relies on the distinction.
"Intelligence" is used most commonly to refer to a class or collection of cognitive abilities. I don't think there is a consensus on an exact collection or specific class that the word covers, even if you consider specific scientific domains.
LLMs have honestly been a fun way to explore that. They obviously have a "kind" of intelligence, namely pattern recall. Wrap them in an agent and you get another kind: pattern composition. Those kinds of intelligences have been applied to mathematics for decades, but LLMs have allowed use to apply them to a semantic text domain.
I wonder if you could wrap image diffusion models in an agent set up the same way and get some new ability as well.
The problem I see regarding LLMs is they are the extreme edge of what humans have created. They are trained on the outputs of intelligence and thought and its representation in language is this like parallel stream to intelligence that has pointers back to the underlying machine and semantics. The fact that LLMs are able to take that output and reverse engineer something that mimics the underlying machine that created that output is fascinating. But you can still see this machinery for what it is.
LLMs falls apart on really simple reasoning tasks because when there is no statistical mapping to a problem in its network it has to generate a massive amount of tokens to maybe find the right statistical match to this new concept. It is so slow. It is not something you or I would recognize as a process of logical reasoning. It is more like statistically brute forcing reason by way of its statistical echo.
So, I guess pattern recall is the right words. Or statistical pattern matching. Recall works if you view a trained model as memories, which is how I often model what they store in my own mind. So, it is... something. Maybe intelligence. Maybe just a really convincing simulation of the outputs of intelligence. Is there a difference? Fundamentally I think so.
