Training of Physical Neural Networks
arxiv.org
Training of Physical Neural Networks
1–10 of 51 posts
Re: Training of Physical Neural Networks
#2[deleted]
Re: Training of Physical Neural Networks
#3So it sounds like these PNNs are essentially analog implementations of neural nets? Seems like an odd choice of naming to call them 'physical'.
Re: Training of Physical Neural Networks
#4PNNs resemble neural networks, however at least part of the system is analog rather than digital,
meaning that part or all the input/output data is encoded continuously in a physical parameter, and the weights can also be physical,
with the ultimate goal of surpassing digital hardware in performance or efficiency.
I am trying to understand what format does a node take in PNNs. Is it a transistor? Or is it more complex than that? Or, is it a combination of a few things such as analog signal and some other sensors which work together to form a single node that looks like the one we are all familiar with?
Can anyone please help me understand what exactly is "physical" about PNNs?
Re: Training of Physical Neural Networks
#5PNNs resemble neural networks, however at least part of the system is analog rather than digital, meaning that part or all the input/output data is encoded continuously in a physical parameter, and the weights can also be physical, with the ultimate goal of surpassing digital hardware in performance or efficiency. I am trying to understand what format does a node take in PNNs. Is it a transistor? Or is it more comple…
[deleted]
Re: Training of Physical Neural Networks
#6[deleted]
Re: Training of Physical Neural Networks
#7My knowledge in this area is incredibly limited, but I figured the paper would mention NanoWire Networks (NWNs) as an emerging physical neural network[0].
Last year, researchers from the University of Sydney and UCLA used NWNs to demonstrate online learning of handwritten digits with an accuracy of 93%.
Re: Training of Physical Neural Networks
#8PNNs resemble neural networks, however at least part of the system is analog rather than digital, meaning that part or all the input/output data is encoded continuously in a physical parameter, and the weights can also be physical, with the ultimate goal of surpassing digital hardware in performance or efficiency. I am trying to understand what format does a node take in PNNs. Is it a transistor? Or is it more comple…
It's just a general idea to implement the computation part of neurons directly in hardware instead of software. For example by calculating sums or products using voltages in circuits, i.e. analog computing. The actual implementation is up to the designer, who in turn will try to mimic a certain architecture.
Re: Training of Physical Neural Networks
#9Last time I read about this the main practical difficulty was model transferability.
The very thing that makes it so powerful and efficient is also the thing that make it uncopiable, because sensitivity to tiny physical differences in the devices inevitably gets encoded into the model during training.
It seems intuitive this is an unavoidable, fundamental problem. Maybe that scares away big tech, but I quite like the idea of having invaluable, non-transferable, irreplaceable little devices. Not so easily deprecated by technological advances, flying in the face of consumerism, getting better with age, making people want to hold onto things.
Re: Training of Physical Neural Networks
#10So it sounds like these PNNs are essentially analog implementations of neural nets? Seems like an odd choice of naming to call them 'physical'.
ANN is taken.