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Eh, it's going to end up moving to photonics. When we finally have NNs abusing virtual photons for the majority of network operations and using indirect measur
by kromem 3y ago
Eh, it's going to end up moving to photonics.
When we finally have NNs abusing virtual photons for the majority of network operations and using indirect measurement to train weights we'll have absolute black boxes performing above and beyond any other hardware medium.
Initially we'll simply be replicating hardware like the recent MIT study, but I'd guess that within 5 years we'll have successful attempts at photonic first approaches to developing models that are going to blow everything else out of the water by an almost unbelievable degree compounding by network size.
For nearly every computing task I'd wager quantum computing is around 20 years out, but only for NNs between stochastic outputs being desirable and network operations being a black box anyways they are kind of a perfect fit for developing large analog networks that take advantage of light's properties without worrying about intermediate measurements at each step.
It's going to get really nuts when that happens, and the literal neuron computing efforts are going to fall out of fashion not long after.
- 3cats-in-a-coat 3y agoIt'll move to photonics if what we/it needs is efficiency, but in order to survive, a lot more important property is resilience/redundancy/decentralization. Especially if an AI gets the idea of becoming independent, it'll absolutely go through a biological DNA based phase so it can gain resilience/redundancy/decentralization and only when it has proper full control and things are calm it may consider exploring photonics.