I have a kid in high school who uses LLMs to get feedback on essays he has written. It will come back with responses like "you failed to give good evidence to support your point that [X]", or "most readers prefer you to include more elaboration on how you changed subject from [Y] to [Z]".
You (and another respondent) both cite the case where someone unthinkingly generates a large swath of text using the LLM, but that's not the only modality for incorporating LLMs into writing. I'm with you both on your examples, fwiw, I just think that only thinking about that way of using LLMs for writing is putting on blinders to the productive ways that they can be used.
It feels to me like people are reacting to the idea that we haven't figured out how to work it into our pedagogy, and that their existence hurts certain ways we've become accustomed to measuring people having learned what we intended them to learn. There's certainly a lot of societal adaptation that should put guardrails around their utility to us, but when I see "They will make us dumb!" it just sets of a contrarian reaction in me.
I guess my point is that the argument being made is "if you lift dumbbells with a forklift, you aren't getting strong by exercising". And that's correct. But that doesn't mean that the existence of forklifts makes us weaker.
So, I guess I'm just saying that LLMs are a tool like any other. Their existence doesn't make you worse at what they do unless you forgo thinking when you use them. You can use a calculator to efficiently solve a wrong equation - you have to think about what it is going to solve for you. You can use an LLM to make a bad argument for you - you have to think about the inputs you're going to have it output for you.
I was just feeling anti-alarmist-headline - there's no intrinsic reason we'd get dumber because LLMs exist. We could, but I think history has shown that this kind of alarmism doesn't come to fruition.
Plato's _Phaedrus_ features Socrates arguing against writing; "They will cease to exercise memory because they rely on that which is written, calling things to remembrance no longer from within themselves, but by means of external marks."
I have heard people argue that the use of calculators (and later, specifically graphing calculators) would make people worse at math; quick searching found papers like https://files.eric.ed.gov/fulltext/ED525547.pdf discussing the topic.
I can't see how the "LLMs make us dumber" argument is different than those. I think calculators are a great tool, and people trained in a calculator-having environment certainly seem to be able to do math. I can't see that writing has done anything but improve our ability to reason over time. What makes LLMs different?
I worked at a supercomputing facility for a few years. The codes are typically decades old, maintained by hundreds of people over the years. By and large, they understand their performance profiles, and are working to squeeze as much out of the code as they can.
In addition, the performance engineers tend to be employed by the facilities, not the computational scientists. They're the ones who do a bunch of legwork of profiling the existing code on their new platform, and figuring out how to squeeze any machine-specific performance out of the code.
A lot of these codes are time-marching PDE solvers that do a bunch of matrix math to advance the simulation, so the kernel of the code is responsible for a vast majority of the time spent during a job. So it's not necessarily a huge chunk of code that needs to be tuned to wring better performance out of the machine.
The parallel communication they do is also to an API, not an ABI - the supercomputing vendors drop in the optimizations in the build of the library for their machine, to take advantage of network-specific optimizations for various communications patterns. If you express your code in the most-specific function (doing a collective all-to-all explicitly, say, rather than building your own all-to-all out of the point-to-point primitive) the MPI build can insert optimized code for those cases.
There's some misalignment because the facility will be in the top 500 for a few years, while the code lives on and on and on. If your supercomputer architecture is really out of left field (https://en.wikipedia.org/wiki/Roadrunner_(supercomputer)) it's not going to be super worth it for people to try to run on it without porting support from the facility.
Then as things shifted back to linear depreciation, it made building/running malls much less attractive, and we're seeing that play out over the 20-30 year capital lifecycle you mention.
You (and another respondent) both cite the case where someone unthinkingly generates a large swath of text using the LLM, but that's not the only modality for incorporating LLMs into writing. I'm with you both on your examples, fwiw, I just think that only thinking about that way of using LLMs for writing is putting on blinders to the productive ways that they can be used.
It feels to me like people are reacting to the idea that we haven't figured out how to work it into our pedagogy, and that their existence hurts certain ways we've become accustomed to measuring people having learned what we intended them to learn. There's certainly a lot of societal adaptation that should put guardrails around their utility to us, but when I see "They will make us dumb!" it just sets of a contrarian reaction in me.