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Comment by ganafagol | Hacker News Reader

I have no idea what the author is trying to say.

Given that they "just recently" learned about microcode, I'd not hold my breath expecting a profound insight about computer architecture or anything computer science though.

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Seems to be asking for some sort of optical FPGA thing with the hope that light will be immensely faster than electricity. Maybe not knowing that it's not?

Also some hints at wanting this "optical FPGA" thing to be analog, rather than digital. And some notion that the various layers of abstraction (silicon->microcode->asm->code) must be wasting lots of cycles.

I'm not really clear on where he thinks 40 years of instant fast-forward might come from.

> Seems to be asking for some sort of optical FPGA thing with the hope that light will be immensely faster than electricity. Maybe not knowing that it's not?

But really it is. Except for interconnects or analog RF stages, ICs aren’t built as if they were solid states waveguides. Indeed speed is determined by how powerful the charge pumps are in moving electrons, not quite the speed of EM propagation

He's hoping for "a million times faster", and "that it might be possible, with today’s technology".

You can certainly go back to analog for calculating ML. In a way, that’s what Rain Neuromorphics is doing.

If you look at some of the earliest Synthetic Aperture Radar (SAR) systems, you'll find that they used exposed film (i.e. light) to perform some serious fourier-style computations using diffractive optics. I.e. you can use physical processes to perform useful computations. It's not entirely out of the realm of possibility... it's just that silicon & Moore's law generated a lot of deterministic, general-purpose compute capability -- whether CPU or GPU.

it's kind of akin to certain compute jobs using quantum effects: There are a class of algorithms that can benefit from that kind of co-processor.

Off the cuff, I don't know of any compute jobs where optical "computers" give you major speedups compared to standard digital processes. But it's not altogether crazy.

On the one hand:

> Could that task be performed by simply the right set of transistors, at the hardware level, no matter how insanely arranged?

> What shortcuts could be taken?

Seems to be suggesting ASICs as is done with Bitcoin mining. On the other about optical rather than electrical which could be more efficient, i.e. produce less heat.

I was expecting a completely different post about evolution of brains that operate with photons, and another jump to entangled ones.

but that's basically already solved with FPGA, right? You can create any circuit on the fly with code.

They propose to implement an algorithm such as a trained neural network by an single-purpose analog computer (whether electronic or optical).

This is sound idea and subject to research but he himself lists some disadvantages and I can imagine there are many more. Generally, nonlinear analog systems are VERY fickle.

> G enerally, nonlinear analog systems are VERY fickle.

You have used a whole bunch of non linear analog systems to write this text..

Of course all existing systems are analog, I know everything digital is just a pretension. But that does not help us in this discussion.

So...I am sure you know what I mean, can you please help me to express it better?

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