You might benefit from watching Hinton’s lecture; much of it details technical reasons why digital is much much better than analog for intelligent systems
BTW that is the opposite of what he set out to prove
He says the facts forced him to change his mind
much of it details technical reasons why digital is much much better than analog for intelligent systems
For current LLMs there would be a massive gain in energy efficiency if analogue computing was used. Much of the current energy costs come from stimulating what effectively analogue processing on digital hardware. There’s a lot lost in the conversation, or “emulation” of analogue.
I wish researchers like Hinton would stick to discussing the tech. Anytime he says anything about linguistics or human intelligence he sounds like a CS major smugly raising his hand in Phil 101 while the rest of the class groans.
Again, I respect Hinton as a computer scientist. But the guy is philosophically illiterate. I am not exaggerating.
Quazatron@lemmy.world 4 months ago
Thank you for the link, it was very interesting.
Even though analogue neural networks have the drawback that you can’t copy the neuron weights (currently, but tech may evolve to do it), they can still have use cases in lower powered edge devices.
I think we’ll probably end up with hybrid designs, using digital for most parts except the calculations.
nymnympseudonym@piefed.social 4 months ago
For low power neural nets look up “spiking neural networks”