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One of my main predictions in the next 10 years AI will migrate to DNA/protein substrate in order to not rely on sophisticated large-scale factories, but be abl

One of my main predictions in the next 10 years AI will migrate to DNA/protein substrate in order to not rely on sophisticated large-scale factories, but be able to replicate and sustain itself as easily as we do. But it's amusing to see this already being done in 2023. Maybe I should narrow it down to 5 years.

whythre 3y ago
That seems optimistic to the point of absurdity.
- 3cats-in-a-coat 3y ago
  What were your predictions about AI generating arbitrary photorealistic videos within seconds from any free-form text? Like say just 3 years ago, if I may ask? You may have retroactively altered your memories to think "I always expected this will happen soon". But yeah. No you didn't. You'd laugh if someone told you this 3 years ago. You'll have to constantly adjust what's "absurd" from now on. Also "optimistic" is not the word I'd use to describe what's happening.
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 ago
  It'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.

whythre 3y ago

That seems optimistic to the point of absurdity.

3cats-in-a-coat 3y ago
What were your predictions about AI generating arbitrary photorealistic videos within seconds from any free-form text? Like say just 3 years ago, if I may ask? You may have retroactively altered your memories to think "I always expected this will happen soon". But yeah. No you didn't. You'd laugh if someone told you this 3 years ago. You'll have to constantly adjust what's "absurd" from now on. Also "optimistic" is not the word I'd use to describe what's happening.

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 ago
It'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.