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Please write your blog posts yourself. I don't want to have to parse through this stupid claude output to get to your point. Literally just posting the prompt would be better than this.
The top comment only based off of one sentence which to me doesn't seem AI. And the author is saying in comments here that it's not AI.
I am genuinely curious as I'd like to update my brain on how to detect AI slop if that's the case here.
https://www.pangram.com/history/c0a9cde2-7a5c-4588-83a3-0269...
Obviously there’s a rise in pure AI writing but I find these sort of services that “analyze” content more harmful than good.
I'm old enough to see this process in action; I used to be young and in possession of esoteric knowledge that made me infinitely in demand and now most of the things that young people have esoteric knowledge about is things that I don't particularly care about, and I'm left with a lot of finely honed skills to solve problems that have mostly been abstracted away.
I do not understand the need to argue that monkeys are better than screwdrivers at screwing. Just let the monkey be the best version of a monkey.
So now instead of improving the tools of biology so we can actually understand it deeply - we increase complexity of IT so we have to rely on muddy, side-effecty tools of biology to try to infer some of the properties of the systems we made. That's depressing.
Determinism is way undervalued.
Non-determinism combined with bugginess?
That's a terrible combination. It is impossible to gradient-descent your way into a working prompt.
Probably not many here know the processes needed to turn sand into silicon and the expertise needed for hand grinding fancy lenses used in lithography. But we do know those things are needed and the approximate philosophical concepts behind these needs.
I think the danger comes when or if we fully automate a lot of the low level infrastructure tasks to the point where future generations do not even have the conceptual framework for how the tech they use is created
This is out the door for AI generated systems. Unless extreme care is taken there is is no consistency in these new-found codebases. New paradigms are introduced left and right, because in the eye of the LLM, and the prompter, they worked.
It didn't matter that the same pattern was repeated 37 times in a slightly different manner.
So your knowledge now is no longer portable.
It used to be that you could look at code, and ask why? And usually (not always) the answer was something like: 'I tried x, y, and z, and those didn't work', either by past experience or current experimentation. (we could argue if the current experimentation should be documented).
But for LLMs they put in something complex for no other reason than that it does what is requested. Reading a string from a valid source byte by byte until you hit \0 is valid, and it'll work. But if you take a step back at, read the API docs of what you're consuming, and then consider: if the API says X, why am I testing whether that's correct?
Issac Newton/Bernard of Chartres said we stand on the shoulders of giants and that allows us to see further afield but it also loses the detail of the ground beneath us - modern folks will no longer have the broad expertise that someone struggling through building a computer from transistors would gain through overcoming that[1], but we should learn about it academically to garner the bits of knowledge that remain salient. It is incredibly useful when experts in these highly specific fields have the communication skills and knowledge to share what is relevant to others without overwhelming them[2] with detail.
1. Real modern consumer grade computers are far too complex to understand fully without dedicating your life (or a significant portion of it) solely to that. It is more pragmatic to allow specialization and small realm expertise instead.
2. Of course, if you want to geek out and learn the minutiae that's awesome - but we can only geek so much in our limited time here.
I'd say it's generally true that the majority of jobs of an era deal with a similar level of abstraction, and that's why most people stay on it. However, I frame this as being born with technical debt, and it's my obligation as an engineer to understand what the previous generations have built, and where it makes sense for me to work, directionally.
But yea this glosses over a bit trial-and-error designs and, so to speak, "genetic optimization" kinds of designs where we just try random stuff and say "Hey, this works. Not sure why, but it works.".
There's a lot of places in history where engineering far outpaced the science required to explain it.
Not saying engineering is required to build or improve a product; it is not.
"try this" is not engineering.
I'm fairly certain I know how it works. Being a physicist helps with the even-lower-level-details if you want to start talking about transistor doping, or electrical circuit theory, for example
What? Definitely not. I went to university and my first two years were subjects where I had to understand really deep levels of abstractions. I had to build logic gates, I had to work with hardware, wires, etc. I didnt see the point back then (I never used any of that professionally). The same about algorithms, databases, and a lot of things. But now I find it valuable and thankful that my professors (and whoever designed the career) considered important topics that I had to lear.
Did I end up an expert at those layers? Of course not, but I know the basics and I know enough that if I need to I know where to start learning more. Just like I wasn't a C++ or hard realtime expert after university either, but now a decade and a half later I am pretty good at those (and a bunch of other skills that ended up relevant to my line of work).
Basically, none of the layers are "magic" to me. Even if I don't know the details of it, I know the general principle and I know I could learn more if I need it.
(I think you naturally end up an expert at the layer(s) you work in, and the knowledge tapers off as you go down (or up) the stack. For example, I know a fair bit about how the CPU works (cache coherency, pipeline stalls etc), I can passably read x86 assembly, etc. Because they affect the layer I work at (hard realtime systems C++ and now also Rust). I know far less about web dev than hardware.)
Did I do all physics or all electronic circuit design or all software stacks? Definitely not. But I spent 3 years learning (and building) about lots of stuff.
The first two years were shared with Electrical Engineering. The second two years started to specialize towards Computer Engineering topics.
* Physics and chemistry.
* Circuits.
* Transistors.
* Logic gates.
* FPGAs.
* Assembly.
* Compilers.
* CPU and hardware design.
* Operating systems.
* Networking layers.
* Programming languages.
* Computer graphics.
Did I master all of the above - absolutely not. I loved some of them, struggled with others. Generally the cut-off for how my brain works is logic gates, I was never strong at the levels below that.
But we did cover them, and I could honestly say I had at least a rough understanding and mental map of everything that happens inside a computer from the point where it's plugged into an outlet, to the point where pixels show up on the screen.
i had to make logic gates and so on, but i wouldnt say i really learnt it, even if back in highschool i learned all the different things a 555 timer can do
Please get used to this sort of depressive, absurd and out of touch tone from HNers, it’s literally all they do now. Don’t bother calling people here hackers anymore, they have checked out emotionally and spiritually.
so even if you're right, checking out emotionally and spiritually just means more life lived. That ain't some kind of bad thing.
life is good sometimes. hard sometimes. and it's long sometimes, so give people a break.
We really dont understand how AI is working, even the earliest "genetic algorithms" could be incomprehensible, but computer systems in general, they're not really that complicated.. its like an audio mixing desk..it looks insanely complicated until you realise it's just the same few knobs repeated many times for many channels. High level languages, compilers, assembly, machine code, nand, mosfets. A single person really can understand it all.
Exactly, I'm over 50 and I remember all the complaints about script kiddies who looked at windows bat files as opposed to all the 'real programmers' who knew C and Assembly and used VIM and linux (which is still going strong)
(ie https://www.explainxkcd.com/wiki/index.php/378:_Real_Program...)
but now also as an AI engineer we have to learn how harnesses, sys prompts, various models, tokens LLMs etc all work so a new abstraction is born..
layers changes, nerds and ultra-specialist nerds will remain
nostaliga is always for the last layer- the one you remembered from your teens and 20s.
As someone who's been exclusively using Vim for my development (and can definitely integrate it with AI workflows), that's just an insanely silly opinion. But I guess it shows how the next generation thinks about these tools that they've heard of but never actually bothered to learn.
But I also see that the people who can create the absolute most and the good things and the working things and the maintainable things nowadays are the people that have gained a tool, but not lost the knowledge of the medium we are using it on because we are tied to this old world so perfectly put under the spotlight in this blog post.
Now everything is a means to a commercial end. Tinkering for fun and knowledge just isn't profitable. And it matters less and less what each our stance is on money and capital if the people that optimize for money and capital gobble up all the money and capital. Of all that's going on, the wealth gap is what's most troubling to me, closely followed because it's closely related is "post truth". I think post-truth is roughly caused by the fact that people are happy to believe what they want to believe toward some commercialized and/or idealogical end. You're much more likely to hate and blame your neighbor when you look around and you're the one not doing too well.
There's absolutely nothing wrong with doing that - I'm just not sure the 'ethos' of tinkering has anything to do with trying to make money and is usually reserved for describing someone playing about with something for their own enjoyment/fun with no desire to make money.
Now, of course some people did find that their tinkerings were able to make them money, but I think at its base it's a term I'd tend to say implies doing something for fun/for themselves, rather than doing it for profit?
In my experience there's still plenty of people out there tinkering just for their own personal satisfaction, but of course there's almost certain a whole load more people out there 'tinkering' to try make a profit.
To be clear, I'm seeing this as an observed phenomenon, not that everyone made up their mind that they hate tinkering and love money. I just think it's getting really really hard to exist in the world as a normal person when the entire human collective is getting pumped commercialized hyper-media from all angles at all times now 100X'd by genAI bots. It's really exhausting and so you either opt-in to the game, monetize your now AI side-hustle to pay the rent, or opt-out and live in the woods. and get packages delivered by Amazon. heh.
Processing error.
Programming languages, UNIX, debuggers aren’t going anywhere. There is more to computing than what your boss demands and what is hyped on tech forums.
In fact I believe the indie/handmade scene will grow substantial if not boom, even if just as a hobby for most. Showing what you have made with your blood sweat and tears will elicit more praise and delight when you could have just asked a machine to do it all along.
We could do this forever.
ETA: Or, to put it in car terms, we were all forced to take cabs (except for the people who were interested in driving, who became cab drivers) because car crashes happen or my sand eating neighbour couldn't tell which pedal was the brakes
I appreciate the tactile joy of interacting with simple systems like those, but most times I just want to get where I'm going. Freeing my attention from those tasks allows me to pay more attention to the (inattentive) drivers around me, and try my best to not die.
Eventually a computer will handle driving for most of us, and we can lament about all the things we've lost there too. If you zoom out, most of us don't have an in-depth understanding of how an entire city works (power, garbage, sewage, maintenance, public services, politics, etc), and couldn't coordinate the various activities to keep it running if we had to. We live in towers of abstraction.
I'm all for just getting to where I need to go by using the appropriate tool, like a reliable car. But no not if it means foregoing the liberty of other options.
We have never before seen every single profession disrupted to this degree, not even the introduction of the personal computer introduced such a dramatic shift
"The difficulty was the knowledge. You came to know that machine the way you come to know anything that pushes back. The resistance was the whole medium. You only ever know the things that you can lose to."
We who grew up in this era formed a hands-on engineer's knowledge of these systems, built from experience and practice, learning these layers of abstraction as the bleeding edge developed. Many these days have entered into a world where there are easy answers abound, they just might not be right, and one has to gauge how much they care about correctness.
I've been staring at 0x10c, carwars and battletech and there's a sense that I could build a sort of programming / engineering Zach like
For a while I've been meaning to set up some Wireguard connections among some of my systems. Being as busy as I am with work and family, I've relinquished that to Tailscale for now.
Sure, I could have sat down and jumped through the hoops to get everything set up and working across my various hosts, including network routes, firewall rules, key pairs, systemd units, and so forth. But the "cheap and easy" alternative was right there and worked (except when it forces re-authentication).
With LLM agents, I was able to effortlessly analyze my existing network and produce tailored scripts to do precisely what I wanted. All I had to do was review the scripts for potential security issues and what not. Looking at the script, there are 3 or 4 specific tweaks that needed to be made to my network routing rules given my network topology. I could have read a few man pages and iterated on the script by hand to eventually get there after maybe an hour or two of futzing.
The availability and effectiveness of the agents is simply too tempting for me. I'm not sure what this means about my skillset, or if that even matters any more. I am fairly confident that, so long as my brain still works well enough, I'll always be able to RTFM and figure things like this out myself. At this rate I wonder whether my kids will have the same ability. And I also wonder how much that will matter.
Regardless, I'm still helping them figure things out the "old way" without over-reliance on LLMs. One thing I'm fairly certain about is that failure to develop problem-solving skills can only put them in a worse position in life, no matter how capable AI becomes.
I've done at least a little of the latter, and it's amazing how underrated it is as an educational tool - especially for the solo individual.
Every technology has ways it can be used, and ways it wants to be used. This one wants to be used in a way that produces outcomes we won't like.
Making the jump from 300 baud to 2400 felt like magic!
> When I was young I fixed my parents’ computer and now that I’m older I fix computers for my kids. Are we the only generation that knows how computers work?
https://x.com/ryancbriggs/status/1847391612428517844
https://xcancel.com/ryancbriggs/status/1847391612428517844
We raised a generation of people on consumption-based computing devices, which means they don't develop the skills necessary to produce things using computers. Of course, we can teach these skills, but to do that, we must first acknowledge it's a skill which needs to be taught.
Whatever dictates if people are capable of creative work with computers, year of birth does not seem to be it.
> It was a Minecraft convention. We had the game set up with a keyboard, and a controller. By the 2nd day we realized, none of the kids could use a keyboard. So on the 2nd day we set up two controllers instead.
> Then I noticed something else. We counted it. 50% of the kids would come up to the console, push the controller out of the way, and try to touch the screen.
I mean, she was right, it turned out to be a touch screen, but really who does something like that?
I went on to study CS and teach undergrad courses and what I noticed, this started already maybe a decade ago, is that CS students who we handed bootable linux usbs couldn't figure out how to set their system up. And not just that, they just kept emailing us with statements like "it didn't work, what do I do?". It's not just lack of knowledge but complete helplessness when something doesn't work in 2 minutes. That's the biggest problem with this reliance on ChatGPT or whatever.
I think the young generation is in an even worse position. Not only do they not know how computers work, they don't even have the basic DIY problem solving attitude our parents have.
Is the premise here correct? I'm not sure that I'm convinced that a 1990s computer user who knew how to edit autoexec.bat or insert a floppy to boot their computer "knew how it worked" in a meaningful sense.
The stack of abstractions is deeper now, and all indications suggest it's not going to stop deepening. But I think the abstractions were already quite deep by the 1990s.
(I think the classic error here is a demographic one: computer nerds always poke through abstractions, because they do it for fun. I don't think that's going to stop, anymore than web browsers stopped people from writing kernels. If anything, we write more low-level code than ever, because access to the prerequisite knowledge is less gatekept than before.)
The most vocal demographic on HN right now is not the nerds. The entrepreneurs and grifters are desperate to find footing somewhere. They continue to double down on the alleged impact of "AI" and are now asking that their followers remember the moments they are most nostalgic for, assume everyone else was doing what they were back then (fumbling and confused), and ignore all the rest of history.
I disagree. If you ask a model for a manual and it regurgitates that manual from its training data, it’s over-fitted. It will regurgitate something that looks like a training manual. Or whatever fits your query about training manuals.
You still have to push back on them sometimes when you spot an error. And you can only spot them if you already know what you’re looking for and should expect. Otherwise you have to ignore the output and just get the links which… could be outdated or made up as well. You’ll never know until you verify the results.
And this degrades with compression and time.
There’s no royal road. I agree that trying and getting frustrated and having to take the effort to understand something pays off in spades. I just think it’s still worth it and vastly under appreciated in this era of “everything fast, now.”
IMO the fact that something's become very mainstream doesn't necessarily mean it's been watered down for everybody. There will always be people with various levels of curiosity and enthusiasm.
The rest of that isn't part of how a computer works.
Should we petition to rename this site to "Stone Age News" or something then?
Maybe I'm wrong but I always thought figuring out how things work was pretty core to the Hacker mentality.
You: I think it’s good to understand some things.
This guy: If you don’t understand everything then you might as well not understand anything!
Guys like this are a corporation’s wet dream. Total intellectual dependence.
Beautiful writing.
Most of the people I dealt with for the decade following that (i.e. pre-LLM) had little clue how any part of computers worked, and I don't intend that to be particularly pejorative, it's just that it's been somewhat easy to carve out a niche doing something to do with programming while having little understanding of the small or big picture.. all heuristics and applying working patterns.. for a few decades.
You can still understand whatever you want, today, with added tools. It's just a choice to turn your brain on or off. I think LLMs are perfectly fine as a learning tool to interrogate a subject, do comparatives, and then formalize your understanding by reading the sources. At a macro level brain rot is real, but it cuts across all generations and it started long before LLMs.
The thing is, if there’s a way to do something easier people will generally just do that. All the nostalgia of the olden days has as a component that there were no alternatives as the example in the article highlights.
We can try to preserve the hard way to things that gets improved, but the hard way will only ever be niche if it doesn’t become extinct entirely. There is no going back.
The bigger issue with brain rot is attention spans. Social media has ruined attention spans.
Then again, maybe there's light at the end of the tunnel. Even though AI boosters kind of annoy me, I do appreciate that they're tinkering and hacking and working to understand the technology on some level. I think there's always going to be some small number of people that are like this, in the same way there are still people that look at disassembly and understand CPU caches.
Obviously this person doesn't have enough experience with the current crop of AIs. This is the exact reason why we should be concerned in the first place. Someone has to design and build the next version of everything, and AI isn't qualified to do the job, and might never be.
>What is dying is acquaintance. The plain, unglamorous intimacy of having fought a particular machine, and lost, and gone back, and finally felt the thing give.
This is true. But then again, who among us had to get up in the middle of the night, and trudge out to an outhouse? Who had to shovel a bit more coal into the furnace? Who had to pump water, and heat it on the stove? Who had to split wood, and stack it for the winter?
There are many, many things we're no longer acquainted with, and that's sad, but still ok. What's not ok is losing the competence required to maintaining the infrastructure and supply chain supporting society and civilization.
> knew a beige computer in 1995 that wouldn’t run a game until I had rearranged its bits by hand. More dependent than ever
If you look at previous article from this author, it says how Mac is amazing and how Linux sucks. Kids like that in 1990ties would buy expensive consoles, and would not deal with hack PC's to get free games.
Many people today are still dealing with cheap shitty hardware, 7 years old Android phones and sketchy ROMs... Just because there is no other option!
https://unix.foo/posts/it-will-never-be-the-year-of-the-linu...
As someone who played plenty of computer games as a teen in the 90s I assure you that I did not know how it worked. I learned how it worked later when I got a CS degree at university. Following the instructions from the booklet that came with the game may have helped me to get it working, but there was minimal understanding.
1: This is why I prefer console games. I just want to have fun without fighting with the machine.
2: There are plenty of people who appreciate old techniques and methods; and keep them alive. Think of going to a museum and seeing someone demonstrate an old craft or reenact how a craftsman did their job. For example, in my town there is an old, water-powered corn mill that still runs and sells corn meal.
I worry more about whether people care and consider it a problem when nobody knows.
Also, if you don't think the difficulty is the knowledge, I'm sorry but I must disagree. There has been more than one government or corporation or large institution that has tried to destroy history and knowledge in the past.
I think it's fair to say that knowledge is also at risk.
I think this is a universal feeling that accompanies any technological innovation. My phrasing is that new technology unbundles the thing people want from the craft that was formerly required to get it; any craft requires someone to learn and achieve through struggle.
I have no idea how an electrical transformer works (well, other than the bare theory I learned in physics courses), or how power gets from the power company to my house, or how the circuits in my home are setup. I plug something in, and it works, and occasionally I throw a breaker if something is malfunctioning. There's no resistance there (pun not intended), and there shouldn't be. People got killed trying to wire their own homes.
I used to read about phone phreaks from the 1970s that could do black magic to get free long-distance phone calls. When I grew up in the 80s, that was basically gone. You picked up the phone, got a dial-tone, and called. And now it's really gone, with everyone having an encrypted cell phone connection over 5G, and your IMEI and IMSI being phoned home to every tower you connect to.
It's the nature of technology and capitalism. As the technology matures, it gets hidden away to become increasingly invisible to the end user, so you just do what you want to do with it. And then the engineering resources get spent on new problems.
people will hack enterprise pbx systems. The stream just flowed somewhere else.
The change from punch cards to magnetic storage certainly made it so you didn't have to "know how it works" for every single bit.
The change from machine code to a language like Fortran brought about such an abstraction that a Fortran dev didn't "know how it works" at that same level anymore.
At this point, the layers of abstractions between using a React component and something being rendered is immense. React VDOM, the real DOM, browser render engine (which sits on abstractions like ANGLE, skia, etc), calls OS APIs, which call driver APIs, and the lowest level of anything it is still C/C++ that is compiled (abstracted) to something closer to what the hardware expects.
I won't bore you with the ChatGPT output details, but it estimated at least 35 meaningful layers of abstraction between a React component and being rendered to the screen. LLMs seem to be the latest level of abstraction to make it so we "know how it works" less than before.
In particular, I think every developer has experienced the need to jump "down the stack" to debug or understand something (even if not all the way down). Certainly, I think any senior developer should be at least conversant in the first few levels below wherever they "live". But this seemingly ends up looking fundamentally different in the interaction mode of an LLM, because you'd just ask it to jump down the stack for you
Just like there were web devs that only knew jQuery but not any actual JS. Game devs that know only Unreal Engine or Unity but nothing about DirectX, OpenGL, or Vulkan. C/C++ devs that know nothing about LLVM IR or the actual bits their compiler generates. It can also be a poor understanding of the layers in the abstractions above you too.
I find a lot of value in being able to understand levels beneath the layer I'm mostly working in. There are things, even/especially with LLMs, that I can grasp because of my deeper understanding.
But there have been plenty in our field that have only known their level of the abstraction for quite a long time. Every time there is something introduced that lowers the barrier to entry to making things, there is a version of this "but they don't know how it really works..."
> ...having fought a particular machine, and lost, and gone back, and finally felt the thing give
mayhaps this is because our computing paradigms are stuck in the 70's
You can know how your entire farm’s water system works. But a city?
Somewhere in between those extremes, you just have to let go.
Oh come on! Of course I wondered how a light switch work, and I then learnt. I remember taking apart broken electronics as a kid, and that later morphed into also trying to repair things. Including the computer (both hardware and software wise). I remember ending up reinstalling the OS so many times as a kid on the computer I had access to when I broke it in various ways past what I was able to fix.
Sure, not everyone will have that drive to understand how the world around them works under the hood. But for engineers and scientists I would expect a far higher percentage to have that sort of personality.
It doesn't matter if it isn't "pushing back", just that I don't understand it is enough to catch my interest and a reason to go poking at the thing.
The collective knowledge of people will likely ebb. Things will be different and individuals will have to adapt.
There are also still courses you can take to learn practical skills, I for example took a short blacksmithing course a few years ago. A lot of fun and way harder than it looks (at least if you want to get good at it, my goal was just to give it a try and have fun, and 5 evenings was enough for that).
I dunno. I suspect it'll be slightly different in the OSS world[1]. There will be some folks who can climb down there and fix it, but since that skill is no longer valued (as in, being able to do that isn't valued by most users now, much less in some hypothetical future). And they will be expected to do that, now, without thanks. And when they say "I'm too old for this shit...you can go pound sand" because this was one unpaid insult too many, users will shrug their shoulders and load windows or buy a mac because those companies are paying & tasking people to keep things running. And by inches oss ceases to be a thing.
[1] Yes, I know there are many oss devs who get paid for their work. Many critical contributors do not.
I'm not sure things are very different now.
I find the current expectations around consumer "apps" to be totally infantile in comparison, where everything is now a single-purpose "app" that does exactly one thing when you push a button, and if you want something even a tiny bit different.. you can't, and that even basic things like files and settings are no longer accessible.
There's nothing new about this particular progression - we've been through it in dozens of technologies already.
So you learned. You opened files like autoexec.bat and you read them."
Ehh I dunno about that. I rarely, if ever, had to mess with any of that junk after Windows 3... I also didn't have to deal with any IRQ issues. So seems like it was already mostly abstracted in the "1990s" lol
That said I did run into my fair share of other problems, and that early era of personal computing and my access to machines is the only reason I work in computing/tech today. If my childhood wasn't full of tinkering with these fascinating machines, and I only ever had an iPhone or iPad, I likely would have turned out much different.
I do remember having to look lots of things up and figuring out why some things wouldnt work. Then getting into building our own computers (because it was cheaper) and figuring out how to get halflife mods working...
And of course IRQ diddling was still necessary to configure sound, network, and game controller hardware throughout the DOS era of gaming, which lasted well into the Windows 9x era.
Good luck coming up with a new language and getting enough content out there that LLMs will be fluent with it.
If true, I think that's a shame. There's plenty of innovation still to be done.
It certainly does worry me, though. As does the increasing amount of materials and manuals that seem to be written assuming the LLMs will be the (only? primary?) audience
They eventually decided to keep their head in the sand and pretend like their restriction was useful.
The issue was a complete lack of knowledge of how the system actually worked one layer down.
That's wrong, and that's exactly why the loss of knowledge is such a problem. LLMs do not, and cannot, actually know a single thing. They are a statistical model, not knowledge. When they give out wrong information (and they always will, by their very nature), you need someone with actual knowledge to be able to recognize the BS and correct it. But we are losing the knowledge, and unless things change we will be no better off than the people in dystopian sci-fi stories who pray to the machine god because nobody knows how it actually works.
Sounds like absolutely horrifying dystopia.
Maybe AGI is impossible with current model as it simply can not reliably improve itself... Enough errors in any part of loop will stop the progression.
1. GPT proved Erdős Unit Distance Conjecture entirely on its own
2. GPT-5.4 Pro Solves Erdős Problem #1196 (April 2026)
In fact there's a whole benchmark that's measuring this: https://epoch.ai/frontiermath
> But we are losing the knowledge
No we aren't and this is spreading FUD. Things have always been like this. Its called specialisation and this is how society progresses. I don't know how the supply chain worked to get the food to my table. That's why its so cheap!
There's no arguing down that we have a greater amount of information about old hardware and software easily available now compared to back then, and there are many more enthusiasts as well.
This kind of cognitive dissonance has been going on in other disciplines, like music, since their inception. Guess what? There's thousands of highly talented young people on social media covering it all.
What people are actually upset about is that there isn't new "old stuff" and they can't make money off what can now be thoroughly understood by anyone.
Don't get me wrong, AI is a total shitshow and we're entering another winter, but there's also no reason to be jealous of what is making money right now.
There have always been layers of abstraction. I've been around for a while, and when I was a kid, the two choices I remember seeing were assembly code and simple semantic languages like BASIC.
Assembly seemed like too cryptic for me to really even follow and I never really did learn it, but at the time I remember people would say that assembly was easy and basically plain English compared to machine code.
As recently as fifteen or twenty years ago, I would occasionally check in and think of how unbelievably far away we had gotten from how the computer actually works. Like, you can just write "open window" and a window opens. Amazing.
Of course, those people writing machine code didn't need to really understand what P and N were in a transistor, let alone how an integrated circuit pulls it all together. And I'm not sure how much those guys knew about silicon dioxide.
The more complex things get and the more layers of abstraction there are, the more impossible it gets to really master things all the way down to first principles.
So what? People can carve out whatever chunk of the stack they want to really understand if they want to focus their lives on it. And for everyone else who's just trying to accomplish some other goal with computers as the tool, they will naturally use the highest level of abstraction and the simplest one for them to use, which is exactly what they should do.
Please don't fucking tell people that AI is competent. It is not and it cannot ever be because it is not alive.
[1] - https://www.youtube.com/watch?v=5WWyKQThSKg