These aren't resources for getting started. They're more like encyclopedias for learning about DSP and tech once you've established the fundamentals of music and sequencing.

If a beginner wants practical knowledge for making records with electronic instruments I'd give them a DAW, teach them to record and sequence, teach them basic music theory, and then point them to something like Ableton's synthesis tutorials that will teach them about oscillators, envelopes, filters, LFOs, and basic sample manipulation.

That's 80% of the necessary skills right there.

All this being said, I think that's a process of convenience and a historical path not a absolute constraint. We have some more flexible means of communicating with the machines today. And I strongly encourage someone to work on a new UI for computer music. "Jazz trio piano, upright bass, and drums. start drummer laid-back, piano blowing over the changes, then piano on top."

It's like Escher; he didn't have any clue that his intricate work would excite mathematicians and crystallographers.

Mandatory reference to GEB

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.

As another commenter below has said, "mathematics might be a useful way to understand music", but it's not how compelling music is made.

Mathematics are fundamental to scales and the harmonic series, and knowing about them will help you refine certain choices, but it's not going to help you write a dramatic melody or an emotionally resonant chord progression, or play an energizing rhythm, even if there are mathematical explanations sometimes.

Good music comes from being a good listener, having a strong sense of what's possible, where it could go, and then delivering something surprising. Telling a story with your melody and supporting the arc of that gesture with harmony that accentuates or contrasts it.

Again, there's a mathematical explanation for harmony and dissonance, but players aren't thinking that granular. They're operating at a higher level of abstraction one, two, or three levels above that: They're thinking about telling a story, evoking an emotion, and exciting an audience in the moment.

As a software developer I see that LLMs are better at the "craft" of making software.

Software developers training are overwhelmingly analytical.

Musicians will experience the same. That the quality of Ai generated music is superior. But it will come more as a chock for the reasons you explain.

Think of it this way: if you first saw the word "HELLO". You could deconstruct that and remember that there are 11 lines and 1 circle but that's not how you learn to read or write. You learn letters, which are collections of lines. So you learn the concept of "H" and it having a sound and that it is 3 lines. You then learn to put them together and how you can sound out something thats's written and with varying degree (depending on language) take something said and write it down.

Music theory is like that. Sheet music may be a bunch of circles and lines on a sheet but really it's describing keys and usually a chord-progression. Some sheet music will explicitly just list the chords at the top like A, Em, Asus4, etc.

The 12 notes are constructed from harmonics, specifically 2:1 and 3:2. This part is maths. But the frequencies are adjusted slightly in a system called "equal temperament" where the ratio of 2 adjacent notes is the 12th root of 2.

From there you generally play a subset of those notes (often 7). That's called a scale (eg major or minor scale). The chords in that scale can then be identified by a Roman numeral within a key. So the I chord in the C major scale is a C. The IV chord is the F. Depending on the starting note of the scale you'll get sharps (#) and flats (♭) to denote that they are a different pitch. An easy way to remember this is that the white keys represent those whole and half steps with just the white keys (starting from C). As an aside, so does the A minor scale.

Why do I say all this? Because a huge amount of modern music is simply a I-IV-V chord progression within whatever scale you're using. So if you know a little theory, you can choose a key and a chord progression that will inherently sound nice together. There's more to it of course but understanding what a key is, what chords are and what a chord progression is is a pretty good start.

As an instruction, I think clearly not, the fact that lots of musicians aren't mathematical at all but create great music seems to prove it to me.

But it is interesting to think about musicians who do seem to think about music this way. Bach is definitely a good example where the system of counterpoint is very complex. I'm not sure if she'd describe herself in these terns, but I've always got the impression Laurie Speigel thinks about music a little like that too. Then there's stuff like Coltrane's Giant Steps, where the whole piece is based around a sort of music theory "trick".

So maybe not generally, but there's definitely some awesome music out of that kind of relationship.

And not once have I ever felt that these so-called intersections were anything other than contrived.

Of course we can interface with music from a mathematical perspective, but that doesn't mean that we should or that there's anything particularly illuminating to gleen from doing so.

Beyond the very basic math (honestly even that's perhaps too strong a word -- just because something is expressed in numbers doesn't make it _math_) of time signatures and some harmonic concepts up to maybe some of Slonimsky's work, doing so is IMO a fool's errand that exists only to fill space on a TEDx stage.

It's like telling someone they can paint a masterpiece because they understand Fe4[Fe(CN)6]3 makes an aesthetically pleasant blue pigment.

> An algorave (from an algorithm and rave) is an event where people dance to music generated from algorithms, often using live coding techniques. Alex McLean of Slub and Nick Collins coined the word "algorave" in 2011, and the first event under such a name was organised in London, England. It has since become a movement, with algoraves taking place around the world.

[0] https://en.wikipedia.org/wiki/Algorave

My first thought seeing this post was, I need to find more literature like this, fine-tune a model with that + Logic Pro documentation, then give it an MCP to control Logic Pro and see if it can be my music production assistant.

I work professionally with music, including using ableton. I do create but don't sell/adverise, I'm strictly 'backstage'. I love everything about creating music, less so for reading about music (reviews, critiques, dissecting) though there are occasional exceptions. Are you putting your creativity online publicly?