Comment by noduerme
1 day ago
In what way is that different from any other model of reality that you'd use to winnow a dataset into an answer to a question? The only major difference I see is that beyond a certain number of transformations, people are willing to treat it as some sort of miracle, and too tired to figure out why it came up with the answer it came up with. It's almost like people desperately want to give up their agency and creativity to black boxes, whether those weights produce answers that are right or wrong. Factor in that psychology and it looks a lot less like we have invented something useful, and a lot more like we as a species are choosing to quit life en masse.
> The only major difference I see is that beyond a certain number of transformations, people are willing to treat it as some sort of miracle, and too tired to figure out why it came up with the answer it came up with.
It’s funny, because I thought you were talking about humans here when you wrote this. We know some things about how our bodies encode information that is sent to the brain, and we know some things about how neurons receive information and act on it, but after that we get too tired and give up on how the brain works and treat it like a miracle.
It’s like we desperately want to believe our consciousness is not just electrical impulses in our brain, and we want to ascribe agency and uniqueness to the physical processes going on in our head.
There's definitely a sizable contingent of people who desperately want to believe consciousness is just electrical impulses in our brain. Because "what else could it be"? The fact is that we just don't know, and "abiding in the not-knowing" is for many the most uncomfortable thing ever. Especially for the curious- and rational-minded people this forum tends to attract. I'm one of them, too.
It is basically reductionism, or in the extreme atomism, and (as I understand it) it has largely fallen out of fashion both in the philosophy of science and in the philosophy of mind, since it heyday in the 1970s. And I don’t see it coming back into fashion any time soon.
I can definitely see why reductionism would appeal to an educated public. We learn about the periodic table; we are able to break sentences down to words, down to letters; to break an executable down to binary code, to machine instruction, to electrical currents flowing through semiconductors. Why shouldn’t we be able to do the same with conscious thoughts? It is certainly an appealing thought process.
As I understand it, reductionism started to fall out of favor because of the rise of quantum mechanics and chaos theory, where we have a lot of weird phenomena which cannot be explained by reducing the particles down to the sub-sub atomic (or rather they are better explained by describing the interactions directly).
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> but after that we get too tired and give up on how the brain works and treat it like a miracle.
I disagree. We know very well how neurons work, and we have a pretty good idea of how neural activity translates to behavior. In other words, we have a pretty good idea on how the brain works. We stop at consciousness because as of yet it is in the realm of philosophy, not science. We don‘t know what consciousness is or even whether or not it is useful for science and we are simply waiting for the philosophers guides us out of that situation.
Note that both cognitive psychology and behavioral psychology has done fine without tackling consciousness. When neuropsychology emerged in the 1980s it complemented both these fields perfectly. The situation is the opposite with the philosophy of mind which grew significantly around the same time.
There have been some attempts to describe consciousness as an emerging phenomena out of neural activity, but so far all of these attempts have failed, or at least failed to turn consciousness into a useful term in psychology (the way gravity is a useful term in physics). I think it is equally likely that these attempts have failed because consciousness may simply not be a useful term in psychology, that is as likely as it is that we simply don‘t understand it well enough.
Saying we have a good idea of how the brain works massively overstates the case...
We know how neurons fire. We do not know how a brain turns that into thought, meaning, intention, experience and on and on. That is not "pretty well understanding the brain", it's understanding some components and hand waving the thing we actually care about.
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> beyond a certain number of transformations, people are willing to treat it as some sort of miracle, and too tired to figure out why it came up with the answer it came up with
It’s less about being too tired and more about being realistic about the limits of understanding.
Consider mass and energy flows in planet-scale systems: At some point we call these “weather” and change the tools with which we study them, but we never stopped trying to understand the phenomenon.
When we attempt to recreate those complex, planetary atmospheric phenomena in a box, we're doing so in order to measure and study them.
Making random turbulence in a box until it resembles the outside world, and calling it weather and extrapolating some predictive meaning from the result, is the total antithesis of what you're describing about why we come up with simplified models for impossibly complex systems. The purpose of [mathematical] models that are built thoughtfully is to explain why complex systems are the way they are, with data and algorithms, however imperfectly. [Whereas] The purpose of LLM models is to give the illusion of answering questions while never answering why the answer was given. The difference is the difference between a scientist and a tarot card reader, an equation and an oracle.
People have a well known tendency to gravitate toward the shamanistic, oracular, and superstitous. Listen, I ran a casino for 6 years, I know. The impossibility of knowing how 80 layers of matrix multiplication led to a particular answer is in itself a psychological factor in choosing whether to accept the answer or to question it. People tend to err on the side of the over, in sports betting terms... or on the lazy side in general... and they will make whatever excuses they need to after the fact to justify their decisions. So now we have a machine that can act like an oracle and which you can also blame, but the blame goes into a void because this machine is stateless and is only a reflection of information, not an intentional refinery of data.
Sit next to a bank of slot machines for an hour and listen to the absolutely ridiculous shit most people will come up with to explain how they "know" if a machine is going to pay out soon, and then tell me if you think it's a good idea to give them an LLM in their pocket to answer their questions in whatever way they frame them.
> The purpose of [mathematical] models that are built thoughtfully is to explain why complex systems are the way they are, with data and algorithms, however imperfectly.
Nope. The main purpose of the whole endeavor is usually to predict the behavior of a complex system, because that's actually what we care about. If we can predict it, we can adapt to it, and eventually use it to our advantage.
Explaining why a complex system is the way it is, is merely nice-to-have. Models are opinions. All of them are wrong, but some are useful, and we rank them by how useful they are. The models and explanations are important because, beyond their elegance and convenience, it's also the case that more accurate models give you better predictions across larger domains, meaning we get better at getting something useful out of the complex system.
People get fixated on modern theoretical science, with bottom-up mathematical explanations traced through seas of empirical data, with whole magical rituals of peer review and double-blind studies and statistical significance around them. But they forget that the core of empirical science is literally throwing shit at a wall to see what sticks. That is the guiding principle, everything else is just making the process more efficient.
Understanding complex natural systems (or even engineered ones that got too complex) always starts with tests - tests on the real thing, then on approximate models that we poke and prod and bash into shape until they start acting similarly to the real thing. It's through the poking and bashing, and how they affect our proxy model, that we glean insights into nature of the simulated phenomena, and eventually formulate general theories - but more importantly, the models give us useful predictions from the start, before we have any theories explaining why.
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> The purpose of LLM models is to give the illusion of answering questions while never answering why the answer was given.
This is just your own idiosyncratic and biased belief. You're not describing anything objective about LLMs, you're describing your personal attitude to them. This colors your understanding in a way that can't really be reasoned with until you let go of the artificial constraints you're imposing on your own understanding.
> Sit next to a bank of slot machines for an hour and listen to the absolutely ridiculous shit most people will come up with to explain how they "know" if a machine is going to pay out soon, and then tell me if you think it's a good idea to give them an LLM in their pocket to answer their questions in whatever way they frame them.
If the LLM in their pocket has a more robust world model than they themselves and is e.g. able to refute their irrational convictions, it actually seems like a very good idea. (Big if, of course.)
If you're going to make something smarter than a person, you got to be convinced that you're only going to be able to understand it on the single training step level and then inductively trust that the rest of it works. We do empirical testing of course with evals, but there's sort of an art to figuring out what is theoretically going to improve eval performance. Trying to fit the meaning of all those weights in your little human brain and working back from there isn't going to work for more than a little slice of the dataset at a time because that's all we can fit in our understanding.
Agency?
What are you talking about?
I want freedom.
I want freedom to do what i want and not sitting in front of a computer and coding for some company.
Please AI lets burn down knowledge work and labor work. Lets create so much stress to our society that we start rethinking what works mean.
Lets redefine work into discovering the world again. Let people do old handcraft jobs, let them do more sports, let them read more, let them write and make more. Let them enjoy nature.
Work has never been about "discovering the world". There have been a handful of privileged folks who had the time to "discover the world". Work has traditionally been "let's find enough food for my family". If you want to think of a future of abundance then perhaps we can discover the world.
We already live in a world of abundance.
No one has to work on a field for their food.
Its a capitalism problem we have, not a resource one.
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> Lets redefine work into discovering the world again. Let people do old handcraft jobs, let them do more sports, let them read more, let them write and make more. Let them enjoy nature.
Why leave something so important up to what AI does or doesn't do?
Because capitalism doesn't allow for that.
Only a fundamental change to our society will allow this for the masses when pressure to the rich skyerockets
"I want freedom to do what i want and not sitting in front of a computer and coding for some company."
"Please AI lets burn down knowledge work and labor work"
"Let people do old handcraft jobs."
So many presuppositions about what people want to do.
As a child I spent a lot of time programming and doing "knowledge work" because it's fun - I don't enjoy "old hand-crafted jobs". Sure, let's definitely destroy capitalism in it's current state I suppose. But I find people like you who hate knowledge-work/coding and think everyone else must feel the same and only do it for the money a bit out-of-touch.
right, these knowledge work and coding jobs are, by my lights, about the best possible job. From my perspective we've invented a machine that does the fun parts while leaving me the less fun parts (review, various hard-to-claude janitorial tasks, etc).
I might like woodworking as a hobby (for example), but I sure as heck don't want to be a carpenter or to depend on my ability to hand craft enough widgets people like to survive
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I differenciate between things you have to do (work) and things you want to do. Work means someone else is telling you your priorities.
If you want to write code and think, you would be welcome in my utopian vision.
But when i write code, its business shit. And its business shit someoneelse already solved a few times.
This seems to be a little naive about how humans consume the benefits we create in society.
"Let people do old handcraft jobs, let them do more sports, let them read more, let them write and make more. Let them enjoy nature."
Very nice thoughts. You know we all could do this today without "burning it down"? Get in your pod, eat your slop, and watch your screen is where this is headed.
"I want freedom to do what i want and not sitting in front of a computer and coding for some company."
You get that it's you creating the misery here? Then stop? Don't do it. Go start a farm or whatever you think will solve your problems. At some point this all boils down to "chop wood and fetch water" so if the modern way of doing that is so terrible then stop. Go fetch water the old fashioned way and be free.
Have you heard of property tax? We have that here.
I also do not earn currently a farm, im planing to buy one, i'm still 100k short though.
Its not me creating the misery, its our capitalistic system.
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The solution we've come up with is move all the unpleasant work stuff to China where people don't complain about doing it because they already have communism, and therefore everything is of course effortlessly perfect there.
>It's almost like people desperately want to give up their agency and creativity
Don't make me think!
Also don't make me take responsibility. (This seems to be the actual function of every organization.)