Being able to look something up real quick isn’t the same as knowing something, is it, especially in the specific absence of some reinforcement mechanism to retain it?
I just mean that I’ve been able to casually look things up once in a moment of curiosity on the internet since the 90s. This did not lead to memorising all those interesting facts, much less understanding them, and I’m not sure what the mechanism is that would lead to that sort of knowledge acquisition. If anything I’ve probably learned less because I know I can just look something up I’d have otherwise needed to learn. And in any case, actually learning hasn’t resulted in a collection of random otherwise unrelated facts I can remember, but understanding systems and relationships.
The knowledge I have learned has indeed come from what might arguably be described as, maybe not as painstaking, but certainly something with intention and effort.
To me it sounds like you’re describing learning to write by having ChatGPT write essays for you. You don’t actually know how to identify birds, you know how to ask your phone to do it for you. Though I can understand the illusion this may cause you to feel. I get the same when I watch high level chess players play, and then am reminded what I can actually do my next game.
For me, the primary mechanism for learning is doing projects.
And, doing projects in domains I'm unfamiliar with (and those I am) is massively sped up by AI.
I learn to do these projects with AI - it's different than learning to do it without AI, and I don't learn some steps I otherwise would, because AI can do those.
But, I start and finish and use and polish so many more projects in so many more domains, with AI, than I could without.
And, starting and finishing projects is the point for me, not learning obscure stuff that doesn't help there, so, I don't feel like I've missed out on much. You might look down on it, but, if I have AI and you don't, I will bet on me to finish a project before you, better than you, in almost any field where we have similar levels of experience.
IDK about frontier-pushing-pursuits, though. I've written algorithms by hand that I doubt AI ever would have, in its current state... but, then, at least a few of those I'd given up on, for lack of time, and when AI came along, I was able to go back and have it finish them. But, for me, the work wasn't the goal, or even my own accomplishment therein - I just wanted the result. If your motivations differ, you might not find AI as fucking awesome as I do.
Sure, you can be much more productive writing essays for example if you have AI write them. Homework of course is much faster and easier if ChatGPT does it for you. All of these things were possible even pre-AI by paying someone else to do things for you (though in some cases it would be considered cheating, but if we set that aside). You’ll definitely blow anyone out of the water who studies or writes for themselves. I also totally get that the productivity gains are so attractive you don’t mind not learning some or all of it. But we are talking about knowing and learning things. Or at least that’s what I thought the thread was about.
"If I should really WANT to answer the foolish question you have just asked, or any of the other questions you have been asking me, let me remind you that I have a row of electric push-buttons on my desk, and by pushing the right button, I can summon to my aid men who can answer ANY question I desire to ask concerning the business to which I am devoting most of my efforts. Now, will you kindly tell me, WHY I should clutter up my mind with general knowledge, for the purpose of being able to answer questions, when I have men about me who can supply any knowledge I require?"
- Henry Ford
This is roughly my point. The moment the AI was able to do things for me, those things which it could do became trivia. I never had a taste for trivia. I still fill my days with learning and knowledge... the things I must learn and know to do my work and run my business well. I am growing faster with AI than I could without - it's allowed me to expand my purview while narrowing my focus. No less learning, just a different shape of it.
So, to me, the argument that "AI doesn't help you learn" completely misses the point. AI can help you learn, if you use it to and apply yourself, but also, AI can allow you to accomplish without filling your mind with "general knowledge" - not the high value stuff that is your business, but the low level stuff that was incidental.
I can easily build you a system that will guess the price of a stock tomorrow wrong at least 90% of the time. Even 100% wrong if you'd like. How would you use that to make fewer errors in some other system?
What’s binary choice we are discussing here and what’s the opposite that you’d do? Approve every claim that was denied by the AI, and vice versa? Or what’s the binary choice related to stock prices you’re referring to?
I agree, that most real world problems, are not binary choices. But in this case actually yes, just do the opposite.
For that reason error rates above 50% don't make any sense. Building a system, that is reliably wrong, is as hard as building one that is reliable correct, because the systems are the same, just with the output inverted.
The worst you can get with a system is 50%, at which point you can just flip a coin, because that is just pure random. Any deviation from that is going to be an improvement.
I always thought insurance claims were more complex, some things may be wholly or partially covered on a line by line basis, and there should be justification provided. In certain cases they go to mediation or even court. It doesn’t seem binary to me but maybe it works differently where you are.
This exactly. The conservative MO has been to accuse everyone else of doing exactly what conservatives do in the shadows, and once everyone believes non-conservatives are corrupt in a certain manner, conservatives goes mask off.
Then their supporters shrug their shoulders and say, "Meh, it's okay because everyone else does it." Except that everyone does NOT do these things. It's just the lie campaign took hold.
Donald Trump belongs in jail for January 6th (among other things) and it's not ok. But pearl-clutching only about Donald Trump doing it is dumb and doesn't solve the problem.
We should oppose corruption and graft everywhere at all times (within our systems), and prior Republican and Democratic administrations (never mind Congress) have done the exact types of things that Trump is doing now. It happens at local levels too, not just at the federal level. If you want to play team sport when it comes to corruption you're simply part of the problem.
I'm responding to someone who accused every politician of engaging in the same level of corruption as Trump. What is your basis for accusing Biden or Obama of even 1/100th of this amount? The Viktor Shokin conspiracy theory? Or the Hunter Biden Burisma story?
That's true, and it's also one of those factoids that everybody already knows but certain people can't help themselves from bringing up every time it's even tenuously relevant.
The fact that it was the top comment only shows that people agreed or liked it, not that it was actually valuable, accurate, or useful. Popularity and value aren't the same thing, correlation is not causation, etc, etc...
Being a programmer has always meant dealing with abstraction layers and climbing up the abstraction ladder.
You are simply learning a new language, whose syntax happens to look like English (or whatever language you speak), but with new, undiscovered, and constantly changing design patterns and best practices.
If you outsource everything to a llm, I just don’t think you get very good results right now. Language models aren’t great at remembering all the little design decisions that are needed in medium to large projects. The code ends up riddled with semi-conflicting design choices, which have been slammed together and maintained by context inertia. For a lot of projects this is more than fine - sometimes higher quality work simply isn’t worth my time. But for a lot of projects, you will pay for that slop later.
But I think there is a useful middle ground. If you carefully review all the decisions an llm makes, I think you can often be more productive than just programming everything by hand. But it’s a very different way to do engineering. I think I learn more this way than if I program by hand - if only because I’m touching more code. My mind roves around the design space a lot more. I don’t lock in as much as when I’m programming each piece individually.
If you work with an llm like this, your engineering skill matters more than ever.
But solving hard problems and developing systems intuition was. If you're trying to tell me that people working on code bases predominantly written by AI are still solving hard problems themselves, or understand the systems the AI is building, I think they're lying to themselves.
I work on a codebase with a lot of math and I've both learned and implemented a bunch of things that were beyond my level before I could iterate on it with AI. Same for binary reverse engineering. On the other fixing tedious bugs by hand and typing the code in is not something I miss at all.
I'm also dependent on a bunch of advanced libraries and compilers I didn't write. I could reimplement them if I took years to do it but it would be a total waste of time.
>I'm also dependent on a bunch of advanced libraries and compilers I didn't write.
Two different kinds of dependence here: one is taking advantage of a pre-existing tool to perform some set of tasks. The other is there to outsource your thinking over concepts you are not able to reason about yourself.
I'm also outsourcing computational geometry to CGAL and CPU optimizations to GCC, so what? I can still reason about them.
For example for a problem I had recently Claude pointed out (after some prodding for me) that the determinant of the Jacobian of a function I'm interested in is a polynomial in polar coordinates, so I used a fancy root finding library (which I also didn't write) to solve it efficiently.
I have a blazor app in poduction, Codex made errors which it could not fix and it required me reading documentation. I won't argue that it didn't make my life simpler, tasks which would take me days are done in hours, sometimes without touching code.
Yea, i still deal with a ton of code in AI heavy workflows. If anything the frustrating part is absorbing the code quickly enough. AI (Claude for me) writes in cryptic text and the code flows can often be non-obvious.
I need (and am exploring) custom review tooling to improve this AI->Human code flow. Reviewing PRs were always the hardest part for me in programming. They were often full of the developers decisions and you have to rediscover those as you're reading code for it to make sense[1]. However i find this even more difficult to discover these decisions from AI.
However unlike human PRs we can ask more of AI. Rarely have i had a developer put on a presentation for a PR - but AI could right? AI could produce a guided walkthrough of the code. Not sure if it will help of course, but my thought is we're all stuck in the old "PR review flow" but instead of PRs it's AI - and the volume of them is far greater than anything prior. So i expect we need to tweak how we review, how we get information from LLMs.
[1]: I'm speaking generally, and about larger PRs. Not some small func where you can easily see what it does. Business logic and complex code can be difficult to decipher in PRs, imo.
From what I’ve seen they get to the level of understanding of systems way faster than we did because they iterate and experiment with this from day one. We had to spend years understanding code syntax, and other minutia.
Also, you need a different kind of toolset/skillset to grok a system that was vibe coded all the way - different failure scenarios. Older devs tend to just say “see, I told you, it’s just spaghetti underneath, you need to clean it up”, and the newer gen learns to work with that spaghetti.
Smart people are handsome, charming, and always make the right decisions even on things they don’t know about. And if they ever are deceived, well I guess they were no true smart person.
Really widely reported in normie news and on reddit, hallucinations and sycophancy. Stand by that whether you’re a petroleum engineer or a bartender, if you’re clever you were probably either well informed or curious enough not to blindly trust the plagiarism machines.
