subjectivationx
subjectivationx on Hacker News
Lawyers are exactly the counter example and how stupid this meme is.
If I was convicted of a crime and had access to Claude in jail, of course I would use profoundly more "law research". You wouldn't hire more lawyers though, you would do the law research yourself because you would be empowered to do law research in ways you wouldn't have been able to do previously and an order of magnitude cheaper than a human lawyer.
Food/farming is really the best example of the stupidity of this meme though. As if the increase in farming automation leads to more farmers as opposed to an increase in the consumption/quality/diversity/output of food.
The meme is a category error as it relates to the output vs the paid for human activity.
The price has doubled but it takes 10-15 years on average just for the permitting of a new mine in the US.
Offshore drilling for oil is a 7-8 year project.
People in software I think can't but help to have a Laissez-faire bias because software is so Laissez-faire. Most other businesses are highly regulated.
A “machine” is precisely what eliminates complexity by design. "People are complex machines" already has no meaning and then adding just and really doesn't make the statement more meaningful it makes it even more confused and meaningless.
The older I get the more obvious it becomes the idea of a "thinking machine" is a meaningless absurdity.
What we really think we want is a type of synthetic biological thinking organism that somehow still inherits the useful properties of a machine. If we say it that way though the absurdity is obvious and no one alive reading this will ever witness anything like that. Then we wouldn't be able to pretend we live at some special time in history that gets to see the birth of this new organism.
Most people have had no exposure to even the most basic ideas of language philosophy.
The idea all these people go to school for years and don't even have to take a 1 semester class on the main philosophical ideas of the 20th century is insane.
It is like saying the airplane understands how to fly.
"You disagree? Well lets see you fly! You are saying the airplane doesn't understand how to fly and you can't even fly yourself?"
This would be confusing the fact humans built the flying machine and the flying machine doesn't understand anything.
If you raised a baby inside a windowless solitary confinement cell for 20 years and then one day show them the sunrise on a video monitor, they still don't understand the meaning of a sunrise.
Trying to extract the meaning of a sunrise by a machine from the syntax of a sunrise data corpus is just totally absurd.
You could extract some statistical regularity from the pixel data of the sunrise video monitor or sunrise data corpus. That model may provide some useful results that can then be used in the lived world.
Pretending the model understands a sunrise though is just nonsense.
Showing the sunrise statistical model has some use in the lived world as proof the model understands a sunrise I would say borders on intellectual fraud considering a human doing the same thing wouldn't understand a sunrise either.
I don't agree with information-theoretic models in this context but we come to the same conclusion.
Loss only makes sense if there was a fixed “original” but there is not. The information-theoretic model creates a solvable engineering problem. We just aren't solving the right problem then with LLMs.
I think it is more than that. The path forward with a use theory of meaning is even less clear.
The driving example is actually a great example of the use theory of meaning and not the information-theoretic.
The meaning of “driving” emerges from this lived activity, not from abstract definitions. You don't encode an abstract meaning of driving that is then transmitted on a noisy channel of language.
The meaning of driving emerges from the physical act of driving. If you only ever mount a camera on the headrest and operate the steering wheel and pedals remotely from a distance you still don't "understand" the meaning of "driving".
Whatever data stream you want to come up with, trying to extract the meaning of "driving" from that data stream makes no sense.
Trying to extract the "meaning" of driving from driving language game syntax with language models is just complete nonsense. There is no meaning to be found even if scaled in the limit.
I have Libre Calc installed because I am on mint at home and even if it could do everything excel could do, I don't know how to do things the same way. Neither do most people. The personal experience and network effect is insurmountable for other software.
At this point, I need a nice gpu on a linux machine and a mac mini. It is a dream setup. I think I booted windows once on my most recent laptop because I messed up booting from the thumb drive to blow it away.
Reaper runs incredible on linux for DAW software but you always run into something that is not available with creative software. Then it is really nice keeping the mac only for creative pursuits.
I am using language models as much as anyone and they work but they don't work the way the marketing and popular delusion behind them is pretending they work.
The best book on LLMs and agentic AI is Extraordinary Popular Delusions and the Madness of Crowds by Charles Mackay.
There is even a small amount of hierarchy at our 15 person Thanksgiving family dinner.
Before the internet, you weren't going to get famous without being an actor, musician, artist, author, etc.
Sam Walton was not famous the way Elon or Jeff Bezos are famous.
I would think there is less because music just isn't as important as it use to be and there are just so many other creative outlets now. The hard thing to account for though is electronic music. You would have had to spend quite a bit of money in the 90s just to make a track and now you can do it basically for free.
If it was 1990, I would be in a band because there wasn't much else to do. Being in a band then was like having a podcast now.
The music industry was never this static thing either. There isn't much before 1950. It is hard now to imagine how huge folk music was in the 70s. MTV was such a big deal in my youth but that only had a 25 year run of being relevant if that.
I don't think there is a real alternative to streaming or the power law distributions that are going to come with that.
That I think is the entire mistake of this bubble. We confused what we do have with some kind of science fiction fantasy and then have worked backwards from the science fiction fantasy as if it is inevitable.
If anything, the lack of use cases is what is most interesting with LLMs. Then again, "AI" can do anything. Probabilistic language models? Kind of limited.
The poseur part is that it doesn't matter if you know what is in the book or not. That is actually the interesting part of the book to me but also why it is largely an exercise in futility.
I would assume someone who says it is their favorite book just has not read that many non-fiction books.