DISCLAIMER TO STUDENTS AND POTENTIAL COLLABORATORS

Please read the following before deciding to work or collaborate with me. I have been asked these questions several times, both in professional settings (during recruitment, promotion, and funding discussions) and in personal settings (at family gatherings, etc.).

Why do I do mathematics, matrix computations, and numerical analysis?

The only answer I have been able to give myself—and others—that I find convincing is: because it is fun. I enjoy the process.

Is it useful?

Perhaps. But usefulness is not my primary motivation. In fact, I find the word “useful” somewhat denigrating when applied to intellectual activity—or, for that matter, to any human activity. At a sufficiently high level, one could even ask: what is the use of human existence? I am reminded of the following Feynman’s quote: “Physics is like sex: sure, it may give some practical results, but that’s not why we do it.”

For now, other people seem to find what I do useful. That’s fine. But even if tomorrow everyone decided that it was completely useless, I would probably continue doing it, because I find the process of thinking, discovering, computing, and understanding fascinating.

It is much the same reason I play over-the-board tournament chess. Almost everyone in my close circle—except my son, who hasn’t yet been corrupted by society—seems to regard chess as the most useless activity imaginable. I don’t. I find it stimulating, challenging, and deeply rewarding. In fact, I think of these as art forms and find the experience almost spiritual.

Perhaps that makes me selfish, self-centred, or even a hedonist. Honestly, I don’t particularly care. There are things I do because they produce something useful for someone else, and there are things I do simply because the activity itself is worth doing. Mathematics, numerical linear algebra, computing, and chess belong largely to the latter category.

But aren’t mathematics, linear algebra, and computing useful for AI, ML, and data science?

Yes. At least that’s what everyone keeps telling us—and, in this case, it happens to be true. These subjects have become extraordinarily useful in AI, ML, and data science.

But that is not why I pursue them.

Their usefulness is a consequence of my pursuit, not its justification.

I don’t do mathematics because AI needs linear algebra. I do linear algebra because I find linear algebra beautiful and fascinating. If AI disappeared tomorrow, I would still want to understand matrices, algorithms, approximation, numerical stability, and computation.

Perhaps that’s the distinction I am trying to make: I value the activity intrinsically; society happens to value some of its consequences instrumentally.

And I am perfectly happy with that arrangement.