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

Fuzzy neural networks and systems represent a synergistic integration of fuzzy logic and artificial neural networks, aiming to encapsulate human-like reasoning within powerful learning frameworks. By ...

Deep learning is increasingly used in financial modeling, but its lack of transparency raises risks. Using the well-known Heston option pricing model as a benchmark, researchers show that global ...

The 2024 Nobel Prize in Physics has been awarded to scientists John Hopfield and Geoffrey Hinton “for foundational discoveries and inventions that enable machine learning with artificial neural ...

A new publication from Opto-Electronic Technology; DOI   10.29026/oet.2025.250011, discusses integrated photonic synapses, neurons, memristors, and neural networks for photonic neuromorphic computing.

Machine learning and neural nets can be pretty handy, and people continue to push the envelope of what they can do both in high end server farms as well as slower systems. At the extreme end of the ...

For example, a Convolutional Neural Network (CNN) trained on thousands of radar echoes can recognize the unique spatial signature of a small metallic fragment, even when its signal is partially masked ...

Researchers have devised a way to make computer vision systems more efficient by building networks out of computer chips’ logic gates. Networks programmed directly into computer chip hardware can ...

Neural circuits in the brain are highly sophisticated biological systems, orchestrating ultra-fast, parallel computations ...

How do electrical signals become "about" something? Through purely physical processes, neural networks transform activity ...

As artificial intelligence explodes in popularity, two of its pioneers have nabbed the 2024 Nobel Prize in physics. The prize surprised many, as these developments are typically associated with ...