WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...

AI became powerful because of interacting mechanisms: neural networks, backpropagation and reinforcement learning, attention, ...

How Computers Powered by Light Could Help With AI's Energy Problem ...

The growth and impact of artificial intelligence are limited by the power and energy that it takes to train machine learning ...

The AI terms you’re suddenly expected to understand — explained.

Mark Zuckerberg’s generation built the digital playgrounds where we spent the last two decades, the likes of Alexandr Wang, ...

Mathematics, like many other scientific endeavors, is increasingly using artificial intelligence. Of course, math is the ...

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...

As enterprises pour billions into GPU infrastructure for AI workloads, many are discovering that their expensive compute resources sit idle far more than expected. The culprit isn't the hardware. It’s ...

One would imagine that an AI capable of solving the hardest Olympiad problems would naturally produce novel scientific ...

Operational technology systems are not ready for the recent NIST cybersecurity standards. Given the constraints, ...