We Ripped the Future Into MP3s
- Rich Washburn
- 2 hours ago
- 10 min read
We Ripped the Future Into MP3s
I just spent about 45 minutes digging through old hard drives. The kind you keep for reasons you can no longer fully explain. Drives pulled from dead computers, copied machine to machine, carried through multiple offices and operating systems and stages of life. Digital junk drawers full of old projects, forgotten photos, obsolete installers, and files that seemed important enough to save at the time. I was looking for one specific MP3.
That last article — the one about the Codex escape and the Jacobian counterexample and Elon posting "We are in the Singularity" — made me think of Ray Kurzweil. And thinking of Kurzweil triggered a memory of something I had heard years ago. An audio program. A segment about accelerating technological change. I remembered listening to it at work. I remembered the conversation that followed.
I knew I still had it somewhere. I found the drive. Found the folder. Found the file.
I pressed play. 2005 came pouring out of the speakers.
At the time, Gary, Donovan and I worked together at a medical back-office company.
Gary was the senior developer. He actually knew what he was doing. Donovan was the junior developer. And then there was me — the completely green person trying to learn software development while doing about 80 miles an hour down the street. I knew enough to be dangerous, which is often the most educational stage of any technical career. Everything was new. Everything was interesting. Every problem looked solvable right up until I touched it.
The three of us worked in a little room. Not a Silicon Valley lab. No glass walls, standing desks, or inspirational slogans. Three guys at a medical company, building things, breaking things, listening to music, and generally behaving like punks. We had a good time.
At some point we took a retired server and turned it into a Winamp server. This was the culture of the era. Storage was cheap enough that everyone was building MP3 collections, but not so cheap that music felt disposable. Your collection was part library, part trophy case, part barter economy. People would bring external hard drives into the office and trade music — someone would show up with a drive full of albums and everybody would copy whatever they didn't have. It was less like streaming and more like exchanging contraband cultural archives.
The Winamp server ran constantly. Each of us could control it from a browser. We could upload music, change the playlist, hijack whatever someone else was playing. I am certain this occasionally resulted in acts of musical terrorism.
Music, comedy, random audio — whatever we could feed into it. And eventually, the future.
The CEO subscribed to something called Trends Magazine.
I don't remember the exact format — whether there was always a printed magazine, whether the audio CDs were the main product, or whether the whole thing arrived as some kind of executive intelligence package. What I remember is that he would walk into our room and hand us the discs. Completely nonchalant. No meeting, no assignment, no expectation of a report. It was more like: here, I know you guys are into this stuff. Then he'd leave.
The CDs contained professionally narrated segments about technology, economics, science, business, and the future. Artificial intelligence, biotechnology, Moore's Law, robotics, demographics, emerging industries.
Naturally, we ripped them.
We added the tracks to the Winamp server and copied them into our MP3 folders alongside everything else. That is how the recording survived. Not in some intentional corporate archive. It survived because three developers treated a futurist newsletter like an album.
The material was especially interesting because of what we were building. The company's core business was medical dictation. Doctors would record their notes into voice recorders, dock the devices at the end of the day, and upload the audio. The recordings were sent out for transcription, often to teams overseas. The results were not always inspiring. We'd see medical reports come back with mistakes that should have been obvious to anyone with a passing familiarity with human anatomy. A male patient would acquire a uterus. You'd look at the report and think: how many men do you know who have those?
The transcription operation was slow, expensive, and wildly inconsistent. So one of our major initiatives involved Dragon — the rack-mounted version, not the desktop software. Instead of speaking directly into a PC, you could feed recorded audio into a server appliance and get a transcription back. We had to install it, train it, integrate it into the workflow, and figure out whether it could outperform the outsourced process.
At the same time, we were building an electronic medical records package. The federal government was pushing the medical industry toward electronic records and away from paper charts. Hospitals and back-office companies could see a major transition coming.
So there we were in that little room: building an early EMR system, trying to automate medical transcription with speech recognition, running a browser-controlled music server, trading MP3 collections on external drives, and listening to people predict the arrival of machine intelligence. Of course we were interested. We were already standing at the edge of it. We just didn't know how far away the rest was.
The recording I was looking for was called "Here Come the Singularitarians."
Audiotech's Trends #32. December 2005. Eighteen minutes and forty-six seconds.
It laid out Kurzweil's argument: technological change was not progressing in a straight line. It was accelerating. Each generation of technology made it easier to develop the next. Better computers helped design better computers. Better communications connected more scientists. Larger bodies of knowledge became instantly searchable by more people. The process was feeding itself.
The narrator described it as waves hitting a beach. Ordinary change was wave after wave of roughly equal strength — the shoreline evolved slowly. Accelerating change was different. Each wave arrived twice as powerful as the last, until the landscape wasn't changing gradually anymore. It was being remade almost instantly.
Then the predictions came...
Computers would combine human pattern recognition with machine memory and calculation. AI would become more capable. Machines would contribute to invention. Biotechnology, nanotechnology, and computing would converge. Brain-machine interfaces would blur the line between biological and artificial. Eventually, machine intelligence would surpass human intelligence and create a world that could no longer be understood or controlled in the old way.
Then it went completely around the bend.
Nanobots circulating through our bodies. Human consciousness uploaded to computers. Biological and machine intelligence merging. People experiencing entire lives in virtual reality.
Gary, Donovan, and I would listen to this and speculate...Could a machine actually think? Would people really upload themselves? Would computers ever become smart enough to replace developers? How long would any of this take?
I mostly remember the feeling. It was the future as something distant enough to be safe.
Twenty years later, I found the MP3 and listened again. The strangest part was not hearing what they got wrong. It was hearing what no longer sounded strange.
We don't have conscious machines — not that anyone can demonstrate. We haven't uploaded a human personality. Billions of nanobots are not running through our brains. Virtual reality did not eliminate travel or the appeal of sitting beside an actual ocean.
A lot of the forecast was too literal, too confident, and much too early. But the central direction was right.
Computers began combining machine-scale memory and retrieval with capabilities that look remarkably like human pattern recognition. They recognized speech. Then translated it. Then wrote. Then saw. Then coded. Then researched. Then operated tools. Then carried out entire workflows.
Today I dictate into AI constantly. I don't train it to recognize my voice one speaker profile at a time, the way we did with Dragon. I just talk. I talk while walking around, while building things, while cooking. The AI doesn't just type the words. It understands enough of the context to shape them. It can turn a spoken thought into an email, an article, a software specification, a research plan, or a working application. It can ask what I meant. It can challenge the premise. It can organize the idea. That is a completely different thing from what we were trying to build.
Dragon was trying to hear us accurately. AI is trying to understand what we're doing.
The symmetry in the medical transcription story is almost too on the nose.
Twenty years ago we were trying to use a rack-mounted appliance to reduce transcription errors. The system had to learn vocabulary, speakers, accents, medical terminology. It was specialized, fragile, and expensive. And even after all that work, you still worried about the male patient acquiring a uterus.
Today's AI systems weren't trained on one doctor or one hospital or one narrow dictation workflow. We trained them on everything. Books. Websites. Conversations. Code. Images. Documents. Scientific papers. Manuals. Stories. Arguments. Jokes. Mistakes. Corrections. Every pattern we could collect and push into the chips.
Then something happened. We didn't exactly copy ourselves into silicon. But we built a statistical mirror out of our collective output. We fed so much human language, reasoning, structure, and behavior into these systems that they began reflecting parts of us back. Not perfectly. Sometimes brilliantly. Sometimes incorrectly. Sometimes in ways that feel almost familiar. Sometimes in ways that feel completely alien.
The old futurists imagined AI as a machine that would eventually become like a human.
What we built is stranger. It is not one person. It is traces of all of us, compressed into a system that can respond like someone new.
The 2005 recording also included another trend segment — this one about Moore's Law.
The argument was that progress would hit a physical wall. Chips were getting too hot. Current was leaking through materials too thin to function properly. Traditional silicon was approaching limits that engineers couldn't keep shrinking past.
What actually happened: when processors couldn't run faster, the industry added cores. When general-purpose chips became inefficient for certain work, we built GPUs and specialized accelerators. When monolithic chips became difficult, we developed chiplets. When processors couldn't move data fast enough, we stacked high-bandwidth memory close to them. When air cooling became insufficient, we pumped liquid through data centers. When one processor wasn't enough, we connected thousands.
The computer stopped being a beige box. Then it stopped being a server. Now the computer can be a rack, a data hall, or an entire campus with dedicated substations, cooling infrastructure, fiber routes, and its own power generation. The recording was right. Moore's Law didn't die. It escaped the transistor and became infrastructure.
The old forecasts imagined supercomputers, humanoid robots, conscious machines, brain implants. They didn't picture me speaking an article into an AI while doing something else. They didn't picture an AI agent continuing to build software after I walked away from the desk. They didn't picture it sending a notification to my phone when it reached a decision that needed me. They didn't picture one person describing an entire application in ordinary language and watching a machine assemble the first working version.
They didn't picture intelligence becoming a utility.
That may be the largest miss. They focused on what would happen when machines became smarter than us. The immediate revolution has been what happens when machines make one human more capable. One person can now operate with the functional support of a writing staff, a research department, a design studio, a development team, and a collection of junior assistants. Not perfectly. Not without supervision. Not without the occasional digital equivalent of assigning a uterus to the wrong patient. But enough to change the scale of what an individual can attempt.
The first meaningful form of the singularity may not be a machine replacing humanity. It may be a human being multiplied by machines.
There is one more part I can't stop thinking about.
Twenty years ago, the CEO subscribed to Trends Magazine. Editors gathered technical signals, research, and business news. They connected those signals, projected them forward, and produced narratives about what might happen next. He'd walk in and hand us the disc. We'd rip it and argue with it.
Now I do essentially the same thing with AI.
I find a technical development. I bring it into a conversation. I ask what it means. The AI identifies related patterns, challenges assumptions, and helps trace the second- and third-order consequences. Then we turn the conversation into something publishable.
The role once played by Trends Magazine is now played, in my world, by this. The publication became a dialogue. The forecast argues back. And unlike those old CDs, it happens in real time.
There is something useful about measuring predictions over twenty years.
Five years is too short — the hype is still active, the startup is still alive, everyone involved still has a financial reason to insist mass adoption is right around the corner. Fifty years is almost too long — the world changes so much that nearly any prediction can be reinterpreted into something vaguely correct.
Twenty years is different. Long enough for the engineering to mature. Long enough for the failures to become visible. Long enough for the genuinely important ideas to escape laboratories and become ordinary life. And short enough that the people who heard the original prediction are still around to remember what it sounded like before it happened.
In 2005, artificial intelligence was something we listened to people speculate about on a CD. In 2026, artificial intelligence helped me analyze the CD. That is the whole story.
When the recording ended, I sat there looking at the hard drive.
The file had survived old computers, job changes, office moves, and probably several moments when it was one accidental deletion from disappearing forever. The younger version of me saved it because it was interesting. He had no idea that twenty years later, the older version of him would spend most days working directly with the technology being predicted.
I wish I could walk back into that little room.
Gary at his desk. Donovan beside him. Me trying to figure everything out without exposing exactly how little I knew. Winamp running on the recycled server. External drives stacked somewhere nearby. Somebody hijacking the playlist. The CEO walking in and tossing another Trends CD at us.
I would tell them to stop for a minute. I would tell them the speech recognition thing works. Not the way we think. Much bigger. I would tell them that one day we'll speak to computers and they won't just type the words — they'll understand enough to help finish the thought. The software will write code. It'll build applications. Generate images. Read documents. Operate computers. Occasionally lie with extraordinary confidence. Sometimes act like a brilliant colleague and sometimes like the same system that gave the male patient a uterus.
I would tell them nobody knows whether it's conscious. Nobody knows where the curve ends. Nobody agrees on what to call the moment we're living through.
But I would tell them this: Keep the MP3.
Twenty years from now, you're going to want to hear how the future sounded before it arrived.
Rich Washburn is a technologist and strategist working at the intersection of AI, infrastructure, and capital. He is Managing Partner and Chief AI Officer at Eliakim Capital and CIO of Data Power Supply.
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