Submission statement: I came across this article earlier today and it hit home on a lot of things that have been swirling in my head lately on the current direction of scientific computing methods. I work in R&D in this space, and would be curious to hear the perspectives of others on the methods surveyed in this paper.
Seems underwhelming to me. A bunch of useful ideas from computer science coupled together with mostly physics applications. The paper itself includes plenty of references, which demonstrate why their manifest is unnecessary.
I don’t get, nor appreciate the low-effort dismissal.
In the world of traditional science and engineering that I come from, these kinds of methods are relatively unknown, let alone used to any real benefit. A document like this aggregates and distills the relevant methods, references, and beneficial applications in one place, which is helpful to decision makers and R&D leads who would otherwise not have known where to look or what to look at.
It can be useful, but the way they frame it is not clear to me. It is an overview and reference, which is indeed very important, but it is not the new paradigm they make it sound like.
Btw, really not a low effort. I have invested time on this. If you can explain how this is more than a survey, please share.
It’s certainly true that much of this stuff has been around a while to those familiar, and I didn’t attempt to frame this article as anything beyond a survey in my original statement. The title is what it is. I’m most interested in hearing perspectives from people who are actually using these methods to do real work, and to hear where the cutting edge actually is these days.
That said, a review like this is still significant to people who are starting out in this field or otherwise not previously familiar, and this is the most recent distillation I’ve seen that is written at a level accessible to a broader science and engineering audience.
