llmssuck

I have no idea how and why GenAI would be useful in your profession. I'm sure a lot of money is moved there (not sure about the profits though), but it's not clear to me how software itself is budging that needle. I suppose better algorithms and better understanding of geology will do it, but software itself seems just subservient to that goal.

I guess what I'm saying is that "domain knowledge" is taking software development for a ride here. The software is just the vehicle, the science is the engine here and I can see why companies like OpenAI start going for the low-hanging fruits first instead.

Your specific company might be profitable, but does automating "mineral exploration" give you leverage over quite literally all other domains? My guess is not. For "CRUD" it is a resounding yes, it provides gigantic leverage. Once you automate basic software development you enter a new world. 10 billion, 10 trillion, all bets are off. You automate the creation of the next iteration of automation and on we go. Let's hope it takes a while for this take off. I can't see ourselves being ready for it.

My guess is it'll take a decade or so for real AI science to start taking off though - if that soon - so you're probably fine for now.

No career is safe for what's coming though. I think I'll just hang around the computer boys. The dress code is much more forgiving.

Stuff it's not directly trained on is going to be flaky and sucky. It was like that with programming at first too and it still is sometimes. It's hard to imagine this won't improve with better more focused training. They focus on improving "CRUD" for obvious reasons. The specialization era hasn't begun yet.

Your domain, while I'm sure it is very interesting and complex, if it proves economically interesting will be cracked as well.

I also remember doing this. Chats, first parts of books, title pages and all, just to give it a chance of saying something in the ballpark of what I was looking for. I remember very vividly that chats or books by Linus Torvalds would be more technically accurate that say Lincoln. It's obvious of course, but I found it really enlightening. It could code a bit actually, not great, but well enough to push me into an existential crisis. I started doing a master to re-educate myself because I could see "interesting" times coming.

I actually emailed OpenAI back then saying they should be careful because this is much greater than the public or even they themselves think. They actually replied! They thought it was cool, but very limited and I shouldn't be too impressed. Good times.

Interesting, so you would say that your experience is .. illusory? In what medium exactly? Illusion requires a substrate of some kind. "Awareness"? What's that?

Neurons are themselves things we experience (indirectly). Once seen through a microscope or known about in some fashion the only way they "exist" is by you having the experience of knowing them. It's not the other way around. One thing is more fundamental here. What is this experience? What are the atoms of this? "Atomic particles"? How would you even approach an answer if your building blocks are themselves part of what needs to be explained?

The hard problem cannot even be touched if you start out like this.

Why is this using Unity? That's insane? How do we know this is not malware?

"no vibe coding" is different from "no ai". I'm not sure where the authors are going with this. No autocomplete? What level of autocomplete? No "deep learning"?

Interesting example for sure. Walking the woods seems more complex, but I still think there is a real difference between "this character Xenia in a TV show acts an actor inside a TV show inside this current one and she likes to eat brownies with yellow cream on top" versus "I see trees with many leaves".

TikTok I have no knowledge of, but for sure seeing something like "Arab dude wearing suspicious looking outfit playing unknown instrument that I now have a name for playing a tune I did not know the name of but I do now says weird cultural thing that is highly specific to his or her locale but it kind of makes sense because of clues inside the video" is still very high-load compared to "I see a bird there that I do not care about in any way shape or form but I do remember it is blue".

Just to offer a counter-example, using AI makes programming bearable again for me. Most of programming comes down to a short - edit: not quit so short but you may understand the figure of speech.. - list of things which are repeated ad infinitum in myriad variations.

I don't have to slog through yet _another_ way to sort, split, combine a list, open a file, show a UI component, handle events, logging, make data flow through some type of "database", serialize and deserialize endless things, implement yet another protocol in $whateverishotnow, managing authn, authz, the list is endless.

The interesting part of programming, for me, is deciding on and capturing the domain in a tight, surprisingly simple yet powerful architecture. This is hard - for me - and actually has very little to do with "programming" per se, meaning it has nothing to do with wrangling syntax/low-level semantics of whatever platform I'm on and fighting package managers to name just two highly depressing parts of my job. I don't like typing code. I am doing it my entire life and I still don't like it.

I like coming up with invariants and ways of guarding them. To find simple decompositions that turn a hairy, ungodly blob of a problem into a manageable almost trivial network of not-so-complicated things. The not-so-complicated things themselves.. I don't care in the slightest about them. Opening files, managing database connections, forms, the mechanics of i18n, typing the word "class", you name it. I find it exceedingly boring.

Perhaps I am more of the architect type, but I find managing a bunch of AIs and making sure they don't stray from My Path is easy on the mind. Programming works on my level of abstraction finally.

I understand your point, but a slightly more positive reading might be that the quantity of information consumed, while perhaps unable to be precisely quantified, can be related to the type of content being perceived.

Staring at wall produces little information in and of itself, perhaps through reflection, but staring at a TV produces a load of information, most of which is useless like names of characters, their favorite dresses, what food is being eaten where, etc. You can learn a lot by just passively observing even "dumb" TV especially if it contains foreign content or skills like cooking or sports. Again, not saying all of it is relevant to your life, but that's a different issue.

Just want to add this is my experience as well. Just solid coworkers. Of course they mess up sometimes, but easier to fix up than with humans and their politic and egos. I find I can actually reason for once instead of always fighting and deferring to whomever has The Biggest Opinion and not rarely just the loudest voice.

I think many people here work at nice, large places with reasonable and knowledgeable colleagues that are cooperative and mostly rational and try to do the right thing. In my experience that is not a common or widespread thing. Of course I only have small to medium business experience, but that's still a pretty good chunk of the economy. LLMs are an absurd, ridiculous win in those kinds of environments.

I know it's unpopular to say (here), but I see it all the time. Myself I sometimes cannot recognize what I wrote and what the agent wrote. It's just that I often have a physical memory of typing it, but that's it. (I also saw a lot of garbage, to be fair.)

There is quite a bit of skill to it, however. You cannot just take an AI from blank to "good code" without doing work. Yes, it takes work and quite a bit of it. By this I mean you have to write a good code style guide and a proper explanation of your architectural style(s), your preferences, your goals, plenty of examples, etc. Proper thought has to be put into this.

If you come across bad code, you need to investigate not castigate: why did this happen? How can we prevent this in the future? Those sort of processes need to become second nature. They actually should be already, because it's not that much different from managing a bunch of humans.

Humans come with lots of implicit knowledge and you also select them to match your company's style when you're hiring them. When they sit down at their keyboards you (and society) has already guided them towards a desirable path. (And even then they often still misfire.)

AI agents operate different. Their range of expression is completely alien to us. We cannot be both von Neumanns and complete morons. LLMs have no problem there. It takes a good while to get used to that.

I suppose the complexity of the domain is the main driver of the difficulty level. Perhaps that's the intuition that I'm trying to pin down: programming itself, the typing of words for the compiler, the act of converting pure thought into code, seems mechanical at best. But if you include the act of abstraction itself, then I concede it changes the equation. I don't find it to be all that clear what is and isn't programming to be honest.

Especially once you get to describe your abstractions in plain (or slightly technical) English instead of code I find it hard to say "programming" is being performed, but in many ways the case could be made that it remained the same and only the shape of the artifacts is different now.

Fair enough, but I think that never really worked all that well. What I mean is that the term "programming" would then essentially cover anything and everything that can be put into an algorithm of some sort. Neutrino detection, user management dashboards, CRUD APIs, basically everything is programming.

It would explain a lot of misunderstanding between "programmers" though.

We might have different concepts of "hard", but if I were a construction worker I think I would agree. Hell, I'm a developer and I agree. Figuring out what to do definitely is the hard part. The rest is work and can be sweaty, but it's not hard as if it's full of impenetrable math or requiring undiscovered physics. It's just time-consuming and in the case of construction work physically tiring.

It might be that I have been doing this for too long and no longer see it.

it was an extremely hard engineering problem

But that is not programming then? Doing voice recognition in the 90s, missile guidance systems, you name it, those are hard things, but it's not the "programming" that's hard. It's the figuring out how to do it. The algorithms, the strategy, etc.

I might be misunderstanding, but I cannot see how programming itself can be challenging in any way. It's not trivial per se or quickly over, but I fail to see how it can be anything but mechanical in and of itself. This feels like "writing" as in grammar and typing is the hard part of writing a book.