It's a statement that /feels/ true, because we can all look "inside" our heads and "see" memories and facts. But we may as well be re-constructing facts on the fly, just as re-construct reality itself to sense it.
The brain definitely stores things, and retrieval and processing are key to the behaviour that comes out the other end, but whether it's "memory" like what this article tries to define, I'm not sure. The article makes it a point to talk about instances where /lack/ of a memory is a sign of the brain doing something different from an LLM, but the brain is pretty happy to "make up" a "memory", from all of my reading and understanding.
Humans can generally differentiate between when they know something or not, and I'd agree with the article that this is because we tend to remember how we know things, and also have different levels of confidence according to source. Personal experience trumps watching someone else, which trumps hearing or being taught it from a reliable source, which trumps having read something on Twitter or some grafitti on a bathroom stall. To the LLM all text is just statistics, and it has no personal experience to lean to to self-check and say "hmm, I can't recall ever learning that - I'm drawing blanks".
Frankly it's silly to compare LLMs (Transformers) and brains. An LLM was only every meant to be a linguistics model, not a brain or cognitive architecture. I think people get confused because if spits out human text and so people anthropomorphize it and start thinking it's got some human-like capabilities under the hood when it is in fact - surprise surprise - just a pass-thru stack of Transformer layers. A language model.
See https://gwern.net/doc/cs/algorithm/information/compression/1... from 1999.
Answering questions in the Turing test (What are roses?) seems to require the same type of real-world knowledge that people use in predicting characters in a stream of natural language text (Roses are ___?), or equivalently, estimating L(x) [the probability of x when written by a human] for compression.
it does not store things in the way records of any sort do, but it does have a some store and recall mechanism that works.
To be fair, LLMs do this too - I just got ChatGPT to recite Ode to Autumn.
Did they not recently transfer memory of how to solve a maze from one mouse to another, giving credibility to what can store information?
Searching, I only find the RNA transfers done in 60s, which ran into some problems. I thought a recent study did transfer proteins.
It’s nice to know that this sort of appreciation is becoming more common. Somewhere between tech accelerationism and protestant resistance are those willing to re-interrogate human nature in anticipation of what lies ahead.
A different blog post from this month detailing an experience with ChatGPT that netted a similar reflection: https://zettelkasten.de/posts/the-scam-called-you-dont-have-...
Muromec•2h ago
I guess it merged two tokens why learning the text.
Amazingly it also knows about difference between two constants, but referrs to the wrong one in both calculations and in hallucinating the quote.
It's tedious to always check for stuff like this.
Then I asked a different LLM and it turned out that actually the constant is monkey patched for specific contexts and both me and the first lying machine were wrong