LLMs are still missing a part of working memory. Part of working memory is being able to attend to small amounts of information and then understand and parse all the pieces of that information. When LLMs use their "working memory" they just analyze different probabilities of tokens and there is no prioritization or understanding of the information in the way humans have it.
If there is no training data or data in the context that leads it to the correct result then it can't do it, whereas a human seems to be able to generalize and abstract a goal and then repeat an action or thought process in a 'recursive' manner to reach the result. AFAIK LLMs don't do this.
Just as an example to illustrate. I recently asked an LLM to organize a bunch of artists albums into whether they were released by a major label or an independent label, and for the most part it did a good job. But there were albums that it classified as independendent that weren't. I presume because it either didn't run into the right data when searching or it misunderstood the data it did find. A human would not do this because if a human had a list of all major labels, it could instantly detect whether an album was or wasn't indie, because it doesn't do any complicated parsing or token probabilities that LLMs do, it just recognizes a pattern (either an album is indie or it is not, a human brain needs simply one piece of information to decide this), an LLM is not that simple.
In a way human brains are simpler than LLMs. The algorithms it runs mentally can detect a piece of information and then see most / all of the consequences of that information whereas an LLM thrawls through megabytes of text and does a token probability distribution and so on without any simplicity.
IMO consciousness is different from working memory, at least to a certain degree. The inner mind (working memory) is different from consciousness from sensory stimuli. You can stand outside and take in the environment and have a relatively quiet inner mind. When you think about math or philosophy a different type of conscious experience arises than sensory stimuli experience. That doesn't mean consciousness is completely isolated from working memory but there is some distinction there I can't describe fully.
Edit: I also think as someone else said, we already know the intermediate layers can contain a lot of adjacent words related to the topic without explicitly outputting those words. These could just be related embedding intermediate vectors that activate but aren't outputted.
Just some speculation, but, I think humans have on the one hand a lot of degrees of freedom in behaviors and thoughts they can do, but at the same time all that freedom is reigned in by our biological needs, like preserving the integrity of our body, but also preserve the integrity of our minds. But this extends further to preserving our surroundings (for our safety, a changing environment brings uncertainty), but also of people we care about and even entire societies that we have. And preserving our future selves through prediction of future environments.
So all that is to say, I'm not sure it is even theoretically possible to create a single algorithm to do open ended search and evaluation. Biology has billions of years of evolution and accumulation, whereas a simple algorithm in a computer, even if smart and connected to the real world, has no such accumulation.
I think humans hit the perfect sweet spot where we have the simplicity of the self preservation instinct, but we have the complexity of the cortex and lots of degrees of freedom because of it, plus on top of that we have a lot of accumulated degrees of freedom in the society and technology and knowledge that have we, which has been built up for thousands of years, all of which we can't just create an algorithm to encapsulate without going through the actual evolution.
And just to make it explicit - a large percentage of what humans think derives from an instinct to preserve the self, the mind, the future and the environment, even if it is very abstract at times. Not absolutely all, but I think a good chunk. And the complexity and degrees of freedom comes from that we have so many neurons in the brain, and a complex body with hands and whatever else that allows a lot of behaviors, as well as a complex environment that is constantly challenging us.
I just want to add that the "recursive" part of recursive self improvement is by no means a given, even if an AI can improve itself.
Recursive self improvement is by its nature a step wise behavior not a continuous one, I would argue. Why? Because you can imagine an AI improve itself by simply fixing random bugs and fixing things using techniques that are in its training, and doing refactoring and so on, all without any real change in capability.
These are not recursive improvements. Recursive improvements usually need conceptual breakthroughs. It is possible to get conceptual breakthroughs with LLMs I believe, maybe it can improve something by tying together ideas from disparate disciplines for example, but I have at least for time being, limited success getting that to work in a way that is creatively new and surprising. Not sure how to get it to feel as creative as the best humans can be.
Personally I'm not a fan of the emergence story, for a number of reasons.
First is, it doesn't really make sense for consciousness to have emerged gradually through natural selection. When we and animals are conscious, the whole brain is coordinated and works to for example turn off consciousness when we sleep. And as someone else mentioned, animals with much fewer numbers seem to have a similar consciousness to us.
If consciousness really evolved gradually, you would expect to see for example dogs or gorillas having less of it, but if they has less of it, why does it function the same way? Like for example animals can be scared, happy, anxious etc, they can experience the full range of emotions and thoughts, so their conscious experience seems just as rich as ours. What I mean by this is, if you can be "less conscious", then what does that mean _exactly_? Is it that you have less content in consciousness, or is it that you feel more like you are asleep? Or something else? We don't have any examples in animals of "less conscious", I would argue.
This makes me think that rather than having emerged gradually, evolution found a mechanism by which consciousness exists, and then some animals have that mechanism and others don't. I think that if it is a mechanism, then this mechanism is located in one part of the brain, not many parts functioning together (though one possibility is that this mechanism coordinates brain activity in such a way to enable consciousness).
I proposed in another comment that consciousness and self-awareness are at least close cousins, and perhaps the same phenomenon. If that's true, then that's an axis upon which you might create comparative measures. Yes, hamsters are conscious, but they don't have a sense of self to the same degree that gorillas do. If you posit capacity for language as another emergent property of sufficiently-complex networks, then you have another measure.
LLMs, then, are particularly unintuitive to us, because they've got to the language part first, long before they've reached even hamster-level self-awareness. They're not, however, biological networks, so there's no reason these properties need arise in the same order, or indeed in the same ways.
I'm not entirely convinced by that second paragraph, but I think the logic holds together.
I'm not sure consciousness and self-awareness are the same thing. First is we can be conscious when we sleep/during REM sleep, where it's arguable we are not self-aware. And if not that, we can even do it when awake, for example when we think about a movie, or a philosophical problem, we can have conscious thoughts that are not related to the self. This leads me to believe consciousness is separate from self-awareness. Self-awareness is _one thing_, among many, that the brain can think about and be conscious of.
Sure, but capacity for self-awareness? I'd guess that hamsters dream, and that their subconscious processes (eg, desires for food and sleep and sex), and maybe even emotions, run much like ours. It's just that humans, with more complex neural networks, have more layers added on top. It's similar to how the brain-stems of everything from lizards on "up" function similarly, but humans have more-developed pre-frontal cortexes and so forth. (Don't hold me to those details, please, I'm not a neuro-anatomist! You can see where I'm going with that, though, right?)
Well in that case I'm not sure where you're going. I agree that hamsters probably have a similar consciousness to ours, which is kind of the point I was trying to make.
I think that consciousness comes before self-awareness, even though self-awareness is kind of a vague term. Self-awareness can either be an abstract knowledge that you are an organism and a discrete entity in the world (world knowledge/self knowledge), or it can be more basic and be a form of conscious experience, but as my point was, I think conscious experience is broader and does not necessarily need to be about self-awareness.
I think we agree on all of those points. I'd posit, however, that whatever "it" is, and however you define it, humans are further up the scale than other animals. That's partly why I mentioned language use; it could be the step function that allows further development. Like, sophisticated-enough communication with other conscious entities is the factor that unleashes recursive improvement. This is all highly speculative.
I find that this happens when you enter folders that have media files like audio files, video files and so on. One way to fix it is to enter one such folder, then remove all columns (like file name, date modified - those columns) and remove all the columns that are media metadata columns. Things like track length, artist, contributing artist or whatever else, then click in the File explorer menu on the 3 dots icon (**) and select View tab, then click 'Apply to folders'. This will apply the column and view settings that you just applied to all such folders.
Now all folders with media files open immediately. Also if you want no wait for video files folders, right click in the folder and select 'View -> Details or View -> List or some other option where it doesn't create thumbnails and it'll load even quicker.
> remove all columns (like file name, date modified - those columns) and remove all the columns that are media metadata columns [...] click in the File explorer menu on the 3 dots icon (*) and select View tab, then click 'Apply to folders' [...] click in the folder and select 'View -> Details or View -> List or some other option
I'm sorry, this is very funny to me in the context of the person upthread arguing about how great "agentic OSes" are. Some people seem to believe that we're living in the future, but I'm pretty sure we're still stuck in Windows '95.
It's not just media files. I'm forced to use Windows 11 on my work PC, and I had to disable the new shell extensions to make the file explorer usable again. It's noticeably faster without the new UI.
Looking up media details is of course one of the main reasons. Thank you for sharing this information. However, all the folders are already configured as general folders and this one specifically has a bunch of PDF files.
When such basic tasks are failing spectacularly, nobody can have any confidence that complex things can be achieved reliably. Instead of spying on their users and trying to squeeze more and more money from them, they should first focus on making a great product and work on making it better, not researching ways to enshitify things.
I feel like I kind of borked the last paragraph so I want to clarify something.
The point is basically that since these repeating patterns are different every time, they are not emergent. They don't really "exist" except as matter repeating itself in a similar way. Emergence implies there is some kind of different qualitative difference between the emergent level and the lower level but I would argue there isn't.
Even though I think it's true that it's lossy, I think there is more going on in an LLM neural net. Namely that when it uses tokens to produce output, you essentially split the text into millions or billions of chunks, each with probability of those chunks. So in essence the LLM can do a form of pattern recognition where the patterns are the chunks and it also enables basic operations on those chunks.
That's why I think you can work iteratively on code and change parts of the code while keeping others, because the code gets chunked and "probabilitized'. It can also do semantic processing and understanding where it can apply knowledge about one topic (like 'swimming') to another topic (like a 'swimming spaceship', it then generates text about what a swimming spaceship would be which is not in the dataset). It chunks it into patterns of probability and then combines them based on probability. I do think this is a lossy process though which sucks.
Maybe it's looked down upon to complain about downvotes but I have to say I'm a little disappointed that there is a downvote with no accompanying post to explain that vote, especially to a post that is factually correct and nothing obviously wrong with it.
If there is no training data or data in the context that leads it to the correct result then it can't do it, whereas a human seems to be able to generalize and abstract a goal and then repeat an action or thought process in a 'recursive' manner to reach the result. AFAIK LLMs don't do this.
Just as an example to illustrate. I recently asked an LLM to organize a bunch of artists albums into whether they were released by a major label or an independent label, and for the most part it did a good job. But there were albums that it classified as independendent that weren't. I presume because it either didn't run into the right data when searching or it misunderstood the data it did find. A human would not do this because if a human had a list of all major labels, it could instantly detect whether an album was or wasn't indie, because it doesn't do any complicated parsing or token probabilities that LLMs do, it just recognizes a pattern (either an album is indie or it is not, a human brain needs simply one piece of information to decide this), an LLM is not that simple.
In a way human brains are simpler than LLMs. The algorithms it runs mentally can detect a piece of information and then see most / all of the consequences of that information whereas an LLM thrawls through megabytes of text and does a token probability distribution and so on without any simplicity.