Are AI Models Working Harder Than They Need to?

Much of modern AI runs on multiplication. Neural networks behind everything from generated answers to photo organization and ...
Quanta Magazine

Novel Architecture Makes Neural Networks More Understandable

“Neural networks are currently the most powerful tools in artificial intelligence,” said Sebastian Wetzel, a researcher at the Perimeter Institute for Theoretical Physics. “When we scale them up to ...

Microchip Advances Neural Network Implementation with VectorBlox™ 3.0 Accelerator SDK

To better manage these challenges, Microchip Technology (Nasdaq: MCHP) has released the VectorBlox™ 3.0 Accelerator Software Development Kit (SDK) to help simplify FPGA‑based AI implementation and ...
Semiconductor Engineering

Building Fixed HW Implementations of Neural Networks (Yale, Cornell et al.)

“Foundation models are deep neural networks (such as GPT-5, Gemini~3, and Opus~4) trained on large datasets that can perform diverse downstream tasks — text and code generation, question answering, ...
Tech Xplore on MSN

Quantum randomness helps neural network recognize troublesome handwritten digits

Quantum computing and AI are among the most rapidly developing modern technologies. AI, in the form of machine learning, has ...
The Conversation

A quantum neural network can see optical illusions like humans do. Could it be the future of AI?

Optical illusions, quantum mechanics and neural networks might seem to be quite unrelated topics at first glance. However, in new research I have used a phenomenon called “quantum tunnelling” to ...