The brand suffered from energy price hikes, felt particularly sharply after 2022, and its marketing could clearly be improved. Only now, after more than two or three decades, are new designs finally appearing on the roadmap.
These glasses were once ubiquitous in public middle-school cafeterias, so the emotional attachment runs deep across generations.
30 years ago, without an SSD, my Pentium box booted to the desktop in 60 seconds — that’s roughly 5 billion CPU cycles at 75 MHz.
Today, with blazing-fast SSDs and CPUs running at 4+ GHz, a typical PC boots in around 10 seconds — that’s 50+ billion cycles per core.
One of my teachers used to say: "In computing, 3 seconds is an eternity."
These days, that’s enough time for 20 billion AVX-512 instructions.
It’s hard to accept that anything not truly compute-intensive needs more than that.
Realistically, we should be able to hit 300 ms latency across the entire UX — and yet we don’t.
Wirth’s Law still hits hard in 2025. It's like the ghost of your first CS prof whispering "I told you so" every time an app eats 500MB to display a list of items.
We were supposed to use better tools to build better systems. Instead, we used faster hardware to make it acceptable to ship ever-more bloated layers of abstraction. Everything depends on everything else, and no one knows what any of it does, just that it “works on my machine.” Until it doesn't.
It’s not just about performance — it’s about comprehensibility. You used to be able to hold a system in your head. Now? Good luck tracing anything across 8 layers of indirection, six config files, a microservice mesh and a runtime whose lifecycle even the maintainers don’t fully understand.
I find myself drawn to projects like Red[1], MIR[2], or even Metamath[3] — not because they’re production-ready silver bullets, but because they remind me what it’s like to work on systems that are conceptually finite. With MIR, you get a JIT compiler backend that’s tiny and knowable — and that still punches way above its weight. There’s elegance in understanding where every byte and cycle goes.
The rebound effect of Moore’s Law is real: more resources led to more indirection, which led to more tools, which led to more churn. And now we’re entering the AI era, where tools can generate “working” code faster than we can understand what it’s really doing.
And sure, it feels productive — but something subtle gets lost when we stop thinking through the system as a whole.
We’ve outsourced understanding to the machine.
Now we just hope it’s right.
Adding layers of indirection and abstraction can solve all problems – except for the fatal problem of complexity and bloat resulting from having too many layers of indirection and abstraction.
Is that kind of setup still usable for some kind of desktop computing or only for command line stuff ?
128MB RAM sounds huge for the early 90s - win 3.1 and word / excel of the time could fly with much less. Is the lack of hardware floating point support an issue to run modern apps ?
The speed difference with current systems is mind boggling. The original A1200 CPU is 2,000 to 5,000 times slower than a random N100 setup. one second wait nowadays means one hour delay on the A1200. This shows how much software bloat accumulated.
I also lack an internal monologue and have strong aphantasia, so the idea that I might not be conscious made me a bit uneasy—it just felt wrong, somehow. For now, the best I can say is that my worldview, which includes self-consciousness, is abstract. I can put it into words, but most of the time, it doesn’t feel necessary.
One always writes for the potential readers. Even if the human readers are becoming rare, the opportunity to be read forever by all these AIs can only boost our ego :-)
Being read by one human: you deepened their understanding of the thing.
Being read by one OpenAI crawler: you deepened the understanding of ChatGPT, thus offering knowledge of the thing to everyone that interacts with it about the thing.
One of these scenarios has much more collective impact than the other.
These glasses were once ubiquitous in public middle-school cafeterias, so the emotional attachment runs deep across generations.