this sounds a lot like the "when you're an adult, you won't always have a calculator in your pocket" line we all heard in elementary school. and of course, we all know now how wrong that was.
in life, chatGPT exists. and tools like it are only going to become more widespread. we are going to have the answers in front of us. knowing the things an LLM knows is not a useful skill anymore.
Also, knowing what kind of things exist and what questions to ask is half the battle. If you haven't stored anything in your head on the grounds that you can outsource knowing things and thinking about them to ChatGPT, you're not going to be able to prompt it efficiently either. It's much harder to sanity check numbers and formulas given to you by others (or ChatGPT) if you can't do any quick mental math. Having original ideas that don't yet exist in LLM datasets also requires storing a lot of concepts and making new connections between them.
I suppose all this is moot if you expect AGI to be available to everyone in the near future, but if it turns out to be decades or more away unfortunately human mental effort will still be required in the meantime.
Tools like calculators, ChatGTP, Google, and chainsaws are often force magnifiers for experts, and a danger for beginners.
If you have an idea of what you are trying to do at a deep level then they are great, but beginners don't, they usually just use them as a shortcut to avoid needing any real understanding of the space, and just get "the answer".
Although in some ways youre right. There will need to be changes in the skills we value, just churning out words, or calculating large sums and interating obscure trig functions will lose value.
Current research being your opinion?
Because literally every expert I personally know to be competent says that they're essentially garbage producers and don't use them beyond occasionally checking if they've improved. And no, they haven't.
The only way to get decent code from them is to be so specific that you'd be able to produce the same code in a fraction of the time you need to add all the context necessary for the LLM to figure it out.
It's like coding with a junior. Thay can produce great code too. It's just gonna take a lot of handholding if complexity skyrocks.
The only place llms got a foot hold is with generating stock art that's mostly soulless marketing material. This "industry" is going to crash so hard in the next 3 years
But for junior devs, it's often the blind leading the blind.
That said, I don't actually use ChatGTP much. I'm just pretty sure I should in some areas.
Generating test data, adding documentation template for functions (which tbh is less useful when you specify types everywhere, even inferred types) and recently, after reading a HN comment, 'rubber ducking'. Which is great, because almost each time I need the rubber duck technique was for real obvious and easy issues I overcomplicated (last was induced by a naming change), and ChatGPT is quite good at that.
But if you want a sketch solution quickly, know the requirements, and can fix the silly mistakes it's a useful tool. Especially if you are doing something where you are rusty, or are used to a slightly different framework or language.
They are like a super fast but slightly clueless junior, who can hammer out mostly correct boilerplate. Not someone you want unsupervised or training a junior, but usefully in some ways.
And yes, boilerplate has disadvantages, but it has its place.
You’re not using it to be better than yourself though in your domain of expertise though.
For example if I need a very specific bash script, I can describe it to ChatGPT and get a good result far faster than I can learn the appropriate bash.
Or if I need a summary of all the config options for some package.
You can also use it to speed up your own learning. But this all depends on you being able to check the out put.
How wrong was it ? I find myself having to do head math every time I playing video games.
Just knowing that your combo can finish an opponent can switches your situation from very passive to very aggressive. Also some jungle / gank timing require clock math.
I think most serious / pro players memorize the numbers already. But casual players like me still have do head math.
I also use things I learned from calculus and physics. Like when driving. No, not solving integrals all the time but it does teach you to focus on rates of change
teaching kids problem solving and how to be productive is important. maybe that means knowing how to solve certain mathematical equations, maybe that means knowing how to use tools like ChatGPT. focusing on the math just for the sake of passing tests because that's what we've got good tests for isn't super helpful to anybody.
I write tests for my code and when they fail I know I have to change something. If you're finishing a math test and not passing, then you don't have the skills to solve the problems in said test.
Tests are only useless when you ace them.
[0] https://gwern.net/doc/psychology/spaced-repetition/2006-roed...
but the big hangup is that "stochastically correct/incorrect" part. Can't count on it, still need skillz. Maybe when straberry/q* drops things will change in this regard