“Performing a key machine learning computation at near zero energy is a leap forward for future AI systems,” said study ...

Artificial intelligence is consuming enormous amounts of energy, but researchers at the University of Florida have built a ...

But powering AI models demands heavy electricity, raising questions about efficiency and sustainability. Researchers at the ...

A team at the University of Florida has developed a new kind of computer chip that uses light with electricity to perform one ...

Artificial intelligence (AI) systems are increasingly central to technology, powering everything from facial recognition to language translation. But ...

A team at the University of Florida has developed a new kind of computer chip that uses light with electricity to perform one ...

Offical implementation of "Strip R-CNN: Large Strip Convolution for Remote Sensing Object Detection" we also add our config in https://github.com/zcablii/LSKNet and ...

In this paper, we tackle the high computational overhead of transformers for lightweight image super-resolution. (SR). Motivated by the observations of self-attention's inter-layer repetition, we ...

From a neuroscience perspective, artificial neural networks are regarded as abstract models of biological neurons, yet they rely on biologically implausible backpropagation for training. Energy-based ...

Abstract: Tiny machine learning (TinyML) enables low-power microcontrollers to run neural network inference locally, allowing real-time classification near the sensor with reduced latency and no ...