Understanding the soul of music and creativity at a mathematical is something that not that many people are trying to do. But there is an entire world of technology that underpins modern music and sound that is built soundly on math, like digital recording digital signal processing, synthesis, physical modeling, and plenty of other stuff, and this seems to be what the book's focus is.
Sure, there have been plenty of attempts to distill music to a mathematical essence. Certainly the ancient Greeks tried this, and traditional counterpoint resembles math in a number of ways. But at the end of the day, mathematical descriptions of math and music theory more generally are more useful as descriptive tools to help give language to what people are doing musically and to understand why we perceive some things as sounding better than others.
Starting with numbers can be good in some respects, like understanding the circle of fifths or how scales are built out of intervals, how chord progressions and harmony work and how to reharmonize, all of which can be augmented with a solid conceptual understanding. But at the end of the day, your ear and creative spirit are your primary asset when it comes to creating good music. This is why computer-generated music has been so bad up until AI took over. Great for building arpeggiators or backing tracks, but good luck creating a beautiful melody in a purely numerical rule-based system.
It's important to note that Microsoft's choice of Go for tsgo was because it would be easier to port the existing TypeScript codebase due to the structural similarity of TypeScript and Go. If writing from scratch, they likely would not have chosen Go.
Which is not to say that Go can't do well in tooling. Only that Go was not necessarily their first choice.
At the same time, the author refers to things like "decades" of muscle memory and finishing "all of college." I wonder if there's just an error somewhere?!
This is key. The yen is still weak, so framing it in terms of today's value in USD is going to make it seem much more affordable than it actually is for the average Japanese person.
I was in a similar spot, but knip offers more information that ts-prune, and ts-prune may trip on some newer TS syntax. I've been happy using knip so far.
> of course, I pretty much expect the NYT to fuck that up, but oh well, that always happens over time
They have a number of free games that don't require any kind of account or registration. I am optimistic that they won't introduce any unsavory elements to it and turn off the playerbase it's amassed.
"Deciding for yourself" doesn't mean jumping to conspiratorial conclusions based on an ambiguous, off-the-cuff remark from 1992, though. And just looking at the comments on that video you can see what sort of agenda these people are bringing to their judgments.
Great idea. One issue that I'm seeing with English/Japanese in particular is that while there is a significant overlap of names that are orthographically similar, the pronunciation varies considerably to the extent that the same pronunciation would not be intelligible as a name in both languages.
For example the name Marie is on there, which in English would be "ma-REE" while in Japanese it would be like "ma-ree-ay"
I imagine anyone using this tool would have enough knowledge of both languages to cull those results, though, so not really a problem in practice. Just an observation.
This might be a reference to the mythology that has developed around cultures and languages that don't count above a certain low number, as in a counting system that goes 'one, two, many.'
"Extremely deep" is an understatement. It's long, deep and plodding enough as to be completely inaccessible to any but the most dedicated, and you have to be willing to spend hundreds, if not thousands of hours by the time it's over, going through it.
I love and appreciate what he's trying to do, but it's overkill.
Sure, there have been plenty of attempts to distill music to a mathematical essence. Certainly the ancient Greeks tried this, and traditional counterpoint resembles math in a number of ways. But at the end of the day, mathematical descriptions of math and music theory more generally are more useful as descriptive tools to help give language to what people are doing musically and to understand why we perceive some things as sounding better than others.
Starting with numbers can be good in some respects, like understanding the circle of fifths or how scales are built out of intervals, how chord progressions and harmony work and how to reharmonize, all of which can be augmented with a solid conceptual understanding. But at the end of the day, your ear and creative spirit are your primary asset when it comes to creating good music. This is why computer-generated music has been so bad up until AI took over. Great for building arpeggiators or backing tracks, but good luck creating a beautiful melody in a purely numerical rule-based system.