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.
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.