One-Man Orchestra From MIDI to AI
By the time I was in my mid-teens, I had already become deeply fascinated by classical music—especially orchestral music.
At the same time, I carried several rather unrealistic dreams.
I wanted to conduct an orchestra.
I wanted to compose a “masterpiece” for orchestra.
And above all, I wanted to actually hear the music I had written performed with real sound.
Honestly, I suspect many classical music fans have had similar dreams at some point.
Especially the first one.
You know—that thing where you put on a record or CD and start waving your arms like a conductor in front of the speakers. I’m fairly sure this has long been recognized as one of the defining behavioral traits of hardcore classical music nerds.
Come to think of it, my father—who was born in the early Showa era—used to do exactly the same thing.
That impulse runs deep.
And to be fair, I completely understand it now. There is something about orchestral music that makes people want to physically enter the music itself. Perhaps that is part of the strange magic of music.
Of course, the realistic path toward any of those dreams would have been professional musical training.
But by your mid-teens, most people already begin to understand roughly where they stand.
To become a conductor, you practically need to be a kind of superhuman. And for many artistic fields—music, sports, fine arts—starting serious training too late can become a major obstacle. By the time ordinary kids realize what they truly love, it is often already “too late” in a professional sense.
But that is simply part of life.
Looking back now, even the years I spent doing nothing particularly productive still had meaning for me in their own way.
Still, youthful longing does not disappear so easily.
After graduating and entering working life, while still carrying those unresolved dreams somewhere inside me, I came across a magazine article that immediately caught my attention.
It described a machine capable of creating and playing music made up of multiple instrumental parts.
Today, I assume it was probably an early hardware sequencer developed by a Japanese manufacturer.
I asked friends and music stores about it, but apparently the technology still wasn’t advanced enough for what I imagined. Looking back, it was probably something very primitive—perhaps an expanded drum machine capable of sequencing four to eight parts.
I remember thinking:
“Well… there goes my orchestra dream.”
So I gave up for a while.
But during those years, music technology evolved at astonishing speed.
A few years later, when I looked again, fully capable instruments had suddenly appeared on the market.
The moment I found out, I rushed to a music store and spent nearly all the money I had on one.
I still remember it vividly:
a Korg 01/W FD.
An 8-track sequencer built into a multitimbral digital synthesizer.
For me, it was revolutionary.
It had a keyboard, so checking sounds was easy. Inputting notes was simple. You could compose, experiment, or simply play for fun. Even now, many people still regard it as a legendary instrument.
This was probably the early 1990s.
Compared to modern technology, the sound quality was primitive, of course.
But to me, it was my first “one-man orchestra.”
I became completely absorbed in it.
The limitations were enormous, but I still managed to compose several pieces. The actual data is long gone now, yet strangely enough, I can still remember many of the melodies and harmonies quite clearly.
Eventually, collecting information about music technology became a hobby in itself. And naturally, that led me to the next stage:
I bought a Macintosh computer and sequencing software, and gradually fell deep into the world of DTM.
From there, years passed in a cycle of composing, upgrading equipment, buying new gear, and spending alarming amounts of money.
At the time, music technology was still extremely expensive.
I practically emptied my savings.
Still, even though I never became a conductor, one of my dreams had finally come true:
I could compose orchestral music and actually hear it with my own ears.
And that brings me to the real subject of this essay:
my long struggle with digital music itself.
Today, many of MIDI’s fundamental problems are widely understood and technically improved.
(And no—I am absolutely not saying MIDI is “bad.”)
But early MIDI-based music production had two major weaknesses.
One came from the sound sources themselves.
The other came from something much deeper:
music being constructed on top of the perfectly rigid timing of computer clocks.
Ironically, in the early days of DTM, this precision was considered its greatest strength.
People were amazed by the idea that computers could create ensembles with absolute rhythmic accuracy.
And indeed, they could.
Functions like quantization allowed notes to align with superhuman precision—far beyond what human performers could achieve naturally.
At the time, this “machine-like accuracy” was viewed almost as musical perfection itself.
But it didn’t take long to realize there was a problem.
Human musicality often exists precisely in the opposite direction.
Take meter, for example.
In real music, beats are not merely equal mathematical divisions of time, as they are often taught in school.
Strong beats and weak beats create motion, pulse, and the transfer of energy.
And importantly, those differences even affect note length itself.
Professional musicians understand this instinctively.
In fact, some 18th-century performance treatises explicitly state that strong beats should be played slightly longer.
There is another important point as well:
when humans perform ascending or descending musical lines, tiny accelerations and hesitations naturally emerge.
These fluctuations are rooted in human physiology itself.
That is why genuinely “natural” performances often contain subtle imperfections.
And this is where things become interesting in the AI era.
Because modern AI has already learned much of this “human-ness.”
The reason AI-generated singing can sound so human is not simply because it reproduces vocal tone—it has also learned patterns of behavior and expression.
But precisely because of that, I believe it becomes increasingly important for creators to understand these underlying mechanical tendencies and consciously manipulate them.
This, in my view, is one of the major walls creators must eventually overcome if they truly wish to pursue originality.
Because no matter how sophisticated AI becomes, what it generates by default is ultimately a kind of optimized “safe answer” designed to satisfy the broadest possible range of users.
And that is not necessarily identical to one’s personal artistic sensibility.
At this level, the issue is no longer technical.
It becomes a matter of perception.
A matter of individuality.
Because individuality is inherently unique.
No one else can replace it.
Not even AI.
In fact, that is precisely why we call it individuality.
At this point, AI ceases to be merely a “composition machine that also performs.”
It becomes something closer to a creative partner.
The road beyond this point is probably endless.
But honestly, I think that is part of the excitement.
And when we finally move beyond that wall—
what kind of music will AI create then?
That is something I genuinely look forward to discovering.
Thank you very much for reading.