Accurately tracking atmospheric greenhouse gases requires not only fast predictions but also reliable estimates of ...

The rise of artificial intelligence (AI) deep learning algorithms is helping to accelerate brain-computer interfaces (BCIs). Published in this month’s Nature Neuroscience is new research that shows ...

Researchers generated images from noise, using orders of magnitude less energy than current generative AI models require.

Scientists in Spain have used genetic algorithms to optimize a feedforward artificial neural network for the prediction of energy generation of PV systems. Genetic algorithms use “parents” and ...

As the world grapples with the energy crisis and environmental concerns, the focus on renewable energy sources has intensified. Lithium-ion batteries, with their high energy density and low pollution, ...

In recent years, artificial intelligence technologies, especially the machine learning algorithms, have made great strides. These technologies have enabled unprecedented efficiency in tasks such as ...

Memories can be as tricky to hold onto for machines as they can be for humans. To help understand why artificial agents develop holes in their own cognitive processes, electrical engineers have ...

TPUs are Google’s specialized ASICs built exclusively for accelerating tensor-heavy matrix multiplication used in deep learning models. TPUs use vast parallelism and matrix multiply units (MXUs) to ...

Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...

The Stellar P3E is the first automotive microcontroller to ship with ST’s Neural-ART Accelerator. It offers a 20x to 30x improvement in inference operations compared to a similar MCU without a ...