Nov 1, 2023 · Here we introduce a nonlinear learning metamaterial -- an analog electronic network made of self-adjusting nonlinear resistive elements based on transistors.
We experimentally demonstrate that nonlinearity enhances machine-learning capabilities in an analog CLLN, establishing a paradigm for scalable learning systems.
Apr 5, 2024 · We demonstrate that the system learns tasks unachievable in linear systems, including XOR and nonlinear regression, without a computer. We find ...
Machine Learning Without a Processor: Emergent Learning in a Nonlinear Electronic Metamaterial · Sam Dillavou, Benjamin D Beyer, +3 authors. D. Durian · Published ...
Nov 2, 2023 · We demonstrate that the system learns tasks unachievable in linear systems, including XOR and nonlinear regression, without a computer. We find ...
The capabilities of digital artificial neural networks grow rapidly with their size. Unfortunately, so do the time and energy required to train them.
Apr 8, 2024 · This study introduces a novel approach to analog machine learning using a nonlinear learning metamaterial.
Aug 13, 2024 · Researchers from the University of Pennsylvania have designed an electrical circuit, similar to a neural network, that can learn tasks such as nonlinear ...
We experimentally demonstrate that nonlinearity enhances machine-learning capabilities in an analog CLLN, establishing a paradigm for scalable learning systems.
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Jun 5, 2024 · The hope is that the prototype will offer a low-power alternative to the energy-guzzling graphical processing unit (GPU) chips widely used in machine learning.