Tech Xplore on MSN

Ultrafast nanolasers mimic how the brain imagines unseen parts of the world

A new study has demonstrated how networks of spiking nanolasers could emulate a key principle of brain function: to imagine ...
Blue Headlineq

No Gradients, No GPUs: A Radical Neural Network Breakthrough

No gradients. No GPUs. Discover how Hamiltonian neural networks use logic and low-precision computing to challenge deep learning’s dominance.

Multi-stage dual-domain progressive network enhances sparse-view CT reconstruction

A research team led by Professor Wang Hongzhi from the Hefei Institute of Physical Science of the Chinese Academy of Sciences has developed a multi-stage, dual-domain, progressive network with ...

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

WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification BEIJING, Feb.06, 2026––WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the ...
Psychology Today

Why the New Artificial Intelligence Is So Powerful

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

Rapid assessment models for neutron beams of BNCT based on backpropagation neural network

Abstract: With the rising global cancer incidence, addressing cancer has become a major international priority. Efficient cancer treatment methods are in high demand. Boron Neutron Capture Therapy ...

The rise of Moltbook suggests viral AI prompts may be the next big security threat

History may soon repeat itself with a novel new platform: networks of AI agents carrying out instructions from prompts and sharing them with other AI agents, which could spread the instructions ...
Communications of the ACM

Building Intelligent Agents with Neuro-Symbolic Concepts

The agent acquires a vocabulary of neuro-symbolic concepts for objects, relations, and actions, represented through a ...
IEEE

Adaptive Stochastic Conjugate Gradient Optimization for Backpropagation Neural Networks

Abstract: Backpropagation neural networks are commonly utilized to solve complicated issues in various disciplines. However, optimizing their settings remains a significant task. Traditional ...