Those young engineers, in 10 years, won't be able to fix what the LLM gave them,because they have not learned anything about programming.
They have all learned how to.micromanage an LLM instead.
Those young engineers, in 10 years, won't be able to fix what the LLM gave them,because they have not learned anything about programming.
They have all learned how to.micromanage an LLM instead.
I have heard a version of this plenty of times, and it was never correct. In the early 90s it was the "electronics" people that were saying "I come from an electronics background, these young'uns will look at a computer and don't know what to do if it breaks". Well, bob, we did, the whole field moved to color coded anti-stupid design, and we figured it out.
Then I heard it about IDEs. Oh, you young people are so spoiled with your IDEs and whatnot, real men code in a text editor.
Then it was about frameworks. BBbbut what if your framework breaks, what do you do then, if you don't know the underlying whatever?
... same old, same old.
Every single finance person uses a calculator. How effective do you think a person in any aspect of finance would be if they had never learned what multiplication is? Would they perform their job adequately if they don't know that `X * Y` is `X repeated Y times`?
IOW, if you gave a finance person (accountant, asset manager, whatever) a non-deterministic calculator for multiplication, would you trust the person's output if they never learned what multiplication is?
This is the situation I am asking about; we aren't talking about whether deterministically automating something that the user already knows how to do is valuable, we're talking about whether non-deterministically generating something that the user is unable to do themselves, even if given all the time in the world, is valuable.
All those examples you give are examples of deterministic automation that the user could inspect for accuracy. I'm asking about a near-future where people managing your money have never learned multiplication because "Multiplication has been abstracted away to a tool that gets it right 90% of the time"
Yup, my mom used to say "you need to be able to do it without a calculator, because in life you won't always have a calculator with you"... Well, guess what mom :)
But on a serious note, what I'm trying to say (perhaps poorly worded) is that this is a typical thing older generations say about younger ones. They'll be lost without x and y. They won't be able to do x because they haven't learned about y. They need to go through the tough stuff we went through, otherwise they'll be spoiled brats.
And that's always been wrong, on many levels. The younger generations always made it work. Just like we did. And just like the ones before us did.
There's this thing that parents often do, trying to prepare their children for the things they think will be relevant, from the parent's perspective. And that often backfires, because uhhh the times are achanging. Or something. You get what I'm trying to say. It's a fallacy to presuppose that you know what's coming, or that somehow an entire generation won't figure things out if they have a shortcut to x and y. They'll be fine. We're talking about millions / billions of people eventually. They'll figure it out.
People who "take the time to really understand the code" will rapidly be outcompeted by people who don't. You don't like that, I don't like that, but guess what: nobody cares.
I suppose we'll get over it, eventually, just like last time.
And I don't think there's anything to get over about them. They are useful but people elevate their significance too much over what they actually are.
As for "autocorrect," let us know when your "autocorrect" takes gold at the International Math Olympiad, with or without steroids.
I might offload multiplying some numbers to a calculator, but Kids These Days™ are trying to offload executive function, like "what should I do next" or "is there anything I've forgotten".
IMO the dichotomy should not be deterministic/stochastic, but proved/unproved reliable. gcc has been shown reliable, for instance, so I don't need to know whether it was built by deterministic (clever engineers) or stochastic (typewriting monkeys) processes. I'm certain the former are more efficient, but this is ultimately not what makes the tool valuable.
As a bit of an artificial example, there's stochastic processes that can be proved to converge to a desired result (say, a stochastic gradient descent, or Monte-Carlo integration), in the same way that deterministic methods can (say a classic gradient descent or quadrature rules).
In practical cases, the only proof that matters is empirical. I write (deterministic) mathematical algorithms for a living, yet they very rarely come out correct on first iteration. The fact there is a mathematical proof that a certain algorithm yields certain results lets me arrive at a working program much faster than if I left it to typewriting monkeys, but it is ultimately not what guarantees a valid program. I could just as well, given enough time, let a random text file generator write the programs, and do the same testing I do currently, it would just be very inefficient (an understatement).
...and today, Nvidia ships self-immolating graphics cards because nobody wanted to figure out how to design a safe electric connector.
> Oh, you young people are so spoiled with your IDEs and whatnot, real men code in a text editor.
...and today, a lot of so-called programmers are trapped in AbstractHellFactorySingletonFactories that they cannot and never will understand, because generations of code monkeys have abused IDE assistance to dig themselves deeper into their hole.
And as a user, you'll know, because the software they write is garbage and never works reliably.
> Then it was about frameworks. BBbbut what if your framework breaks, what do you do then, if you don't know the underlying whatever?
Going by software like Teams, or Slack: They just ignore it, because consumers can't fight back against the the enshittification of increasingly useless software nobody understands.
Developers throwing huge amounts of money (in cloud resources) at performance problems that would’ve been prevented if they had some understanding of how their tech stack actually worked.