This is a rare misfire from Quanta. No, there is no practical way to model anything non-trivial - especially not ML - with analog hardware of any kind.
Analog hardware just isn't practical for models of equivalent complexity. And even if it was practical, it wouldn't be any more energy efficient.
Whether it's wheels and pulleys or electric currents in capacitors and resistors, analog hardware has to do real work moving energy and mass around.
Modern digital models do an insane amount of work. But each step takes an almost infinitesimal amount of energy, and the amount of energy used for each operation has been decreasing steadily over time.
> No, there is no practical way to model anything non-trivial - especially not ML - with analog hardware of any kind.
Are you aware that multiple companies (IBM, Intel, others) have prototype neuromorphic chips that use analog units to process incoming signals and apply the activation function?
IBM's NorthPole chip has been provided to the DoD for testing, and IBM's published results look pretty promising (faster and less energy for NN workloads compared to Nvidia GPU).
Intel's Loihi 2 chip has been provided to Sandia National laboratories for testing with presumably similar performance benefits as IBM's.
There are many other's with neuromorphic chips in process.
My opinion is that AI workloads will shift to neuromorphic chips as fast as the technology can mature. The only question is which company to buy stock in, not sure who will win.
EDIT: The chips I listed above are NOT analog, they are digital but with alternate architecture to reduce memory access. I've read about IBM's test chips that were analog and assumed these "neuromorphic" chips were analog.
This is a rare misfire from Quanta. No, there is no practical way to model anything non-trivial - especially not ML - with analog hardware of any kind.
Analog hardware just isn't practical for models of equivalent complexity. And even if it was practical, it wouldn't be any more energy efficient.
Whether it's wheels and pulleys or electric currents in capacitors and resistors, analog hardware has to do real work moving energy and mass around.
Modern digital models do an insane amount of work. But each step takes an almost infinitesimal amount of energy, and the amount of energy used for each operation has been decreasing steadily over time.