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The absurdity of suggesting optical computing is a good pathway to efficiency is that our brains efficiently use electrons and are doing just fine.
It really isn't a simple thing.
The absurdity of suggesting optical computing is a good pathway to efficiency is that our brains efficiently use electrons and are doing just fine.
The absurdity of suggesting optical computing is a good pathway to efficiency is that our brains efficiently use electrons and are doing just fine.
Our brains are subject to very different design constraints. Wheels are very efficient, but nature doesn't use them because the environment and the exigencies of biological reproduction and repair indicate other strategies. It really isn't a simple thing.
The mark of a maturing domain is the evolution from only general tools to general + specialized. We've gone from only CPUs to CPU + GPU to specialized AI chips (Neural Engine, Tensor chips etc.) and specialized computing is a big tent which can fit many different architectures together. Analog computing is the closest thing to bioengineering in fundamental computer science that I know of, so I am confident that it wi…
One of the things that I fully not expect to be successful is optical computing. There are just a lot of academic groups that are doing optics and they like to invent new reasons why whatever they are up to is relevant. For physics reasons the integration density of optical compute elements is abysmal and will remain so forever . Other technologies like spintronics at least have the chance to work sometime in the fut…
Could you give some details? Claims about "forever" often don't hold up. I guess you're referring to things like component size in relation to the wavelength of light used? One could use smaller wavelengths. Integrated photonics is certainly being done and also commercially relevant (in telecommunications). What integration density would you consider not-abysmal? How much does integration density matter if you have very low loss (which means low power dissipation, a huge problem for semiconductor electronics) and can just make big chips?
There is also research arguing that optoelectronics might eventually be very useful for computing, e.g. recently [1]. (Yes, this is by researchers who need to appear relevant. However, if we dismiss their arguments based on that alone, we can abolish all research altogether.) Why do you disagree? Again, you were talking about forever.
If you know of any startup working on this let me know because I'd love to join the revolution.
The mark of a maturing domain is the evolution from only general tools to general + specialized. We've gone from only CPUs to CPU + GPU to specialized AI chips (Neural Engine, Tensor chips etc.) and specialized computing is a big tent which can fit many different architectures together. Analog computing is the closest thing to bioengineering in fundamental computer science that I know of, so I am confident that it wi…
Maybe I'm missing something, but wouldn't any optical computer have to still funnel signal through binary logic gates at some point? In what sense is that any more analog than (digital recordings on analog) magnetic tape decoded by a modem? The ultimate computation is still 1/0
Probably the best 20 minutes you can spend if you haven't really heard of analog computers. https://www.youtube.com/watch?v=IgF3OX8nT0w
Earlier quoted context omitted.
Maybe I'm missing something, but wouldn't any optical computer have to still funnel signal through binary logic gates at some point? In what sense is that any more analog than (digital recordings on analog) magnetic tape decoded by a modem? The ultimate computation is still 1/0
You can do math with analog circuits. This was the original purpose of the opamp (operational amplifier) [1]. [1] https://en.wikipedia.org/wiki/Operational_amplifier
Analog will likely come back but for other reasons: Neural networks don't require precise calculations and Hintons forward forward networks put into hardware would be several orders of magnitudes more efficient, even without photons. "AI inferencing is heavily dependent on multiply/accumulate operations, which are highly efficient in analog." If you know of any startup working on this let me know because I'd love to…