- cross-posted to:
- technology@lemmy.world
- cross-posted to:
- technology@lemmy.world
Thermodynamic computing uses physical circuits that changes in response to noise, such random thermal fluctuations in the environment, to perform low-energy computations. A recent spate of experiments, theories and prototype hardware have shown it’s especially good at randomization tasks, and may be equally good at diffusion model tasks (e.g. image generation) in the future.
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Just imagine if a hundredth of this effort was put into making things better for the average person.
Thermodynamic computing… For AI.
Nuclear energy… For AI.
This makes a lot of sense though, from the description it sounds like they’re trying to build an NPU out of memristors. We’ve been expecting them to show up to do this kind of math for a bit, since they’d cut a lot of redundant computation out of the layered matrix calculus that NPUs are optimized for if we can make them small, fast, and reliable enough.
And it’s not just for “AI”. A lot of problems, like physics modeling or speech recognition, can be reduced to matrix math. An analog, programmable memristor network can do that kind of calculus almost passively.
