Flexible artificial intelligence optoelectronic sensors towards health monitoring

A paper-based sensor based on the operation of the human brain paves the way for standalone energy-efficient AI-based health monitoring devicesArtificial intelligence is known for its high energy consumption, especially in data-intensive tasks like health monitoring. To address this, researchers have developed a flexible paper-based sensor composed of nanocellulose and zinc oxide nanoparticles that operates like the human eyes and brain.

Considering these criteria, researchers from Tokyo University of Science led by Associate Professor Takashi Ikuno have developed a flexible paper-based sensor that operates like the human brain. Their findings were published online in the journal"A paper-based optoelectronic synaptic device composed of nanocellulose and ZnO was developed for realizing physical reservoir computing.

To test this, the researchers converted MNIST images, a dataset of handwritten digits, into 4-bit optical pulses. They then irradiated the film with these pulses and measured the current response. Using this data as input, a neural network was able to recognize handwritten numbers with an accuracy of 88%.

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Flexible AI optoelectronic sensors pave the way for standalone energy-efficient health monitoring devicesFrom creating images, generating text, and enabling self-driving cars, the potential uses of artificial intelligence (AI) are vast and transformative. However, all this capability comes at a very high energy cost. For instance, estimates indicate that training OPEN AI's popular GPT-3 model consumed over 1,287 MWh, enough to supply an average U.S.
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