I have always found this quote annoying. There are many ways to solve problems, but when you constrain yourself to solving them mechanistically, that is what makes computer science computer science. Virtually every theoretical CS paper implicitly presupposes a specific model of computation. Sometimes they even say it explicitly.

Sure, computer science is not about a specific computer. But it is definitely about computers.

> I have always found this quote annoying

"Mission accomplished." -(fake) E.W. Dikjstra

My strong impression/suspicion is that Dijkstra had a great sense of humor and also enjoyed irritating people; it's puzzling when people take things like his comments on programming languages as serious rather than tongue-in-cheek, but I suspect he would have been amused.

I learned today that apparently Dijkstra won the Dijkstra prize in 2002. (I'm not sure what the qualifications are, but if I were to choose then it would be awarded to the most brilliant, and irritating, computer scientist who has made a groundbreaking contribution to a particular field.)

Respectfully I disagree. I believe what Dijkstra is getting at is that the specifics of modern computers aren’t “relevant” at all. Ultimately it’s the science of information and whats computable. Be that a modern day silicon processor at X gigahertz, a pen and paper, or a universe sized computer, that’s irrelevant for the science itself.

We don’t actually disagree. Note that Dijkstra did not say “modern computer.” He said “computer.” Computer science is in a major way about what “is computable.”

> There are many ways to solve problems, but when you constrain yourself to solving them mechanistically, that is what makes computer science computer science.

How would one solve a computational problem non-mechanistically? Even if executed with pen and paper, or sticks scribbling on sand, any algorithm is still mechanistic.

Non-algorithmically, using intuition, like a (non-programmer) human.

But is it a computational problem then?

Try doing a calculus problem. E.g., integration. Even if you do it on paper, your approach is probably wildly different than a computer integration algorithm. An algorithm that does it symbolically, ala Mathematica, is a pretty difficult thing to write for an arbitrary mathematical expression. People solve those problems largely through intuition, with a sprinkling of procedures that they remember.

> People solve those problems largely through intuition, with a sprinkling of procedures that they remember.

Without making the claim that LLMs have intuition (and certainly not inspiration), what you describe sounds analogous to an LLM with function calling.

Yes Edsger, but they don't go around calling themselves "Telescope Scientists" now do they?