Biologically plausible learning mechanisms have implications for understanding brain functions and engineering intelligent systems. Inspired by the multi-scale recurrent connectivity in the brain, we ...

Beijing, Feb. 06, 2026 (GLOBE NEWSWIRE) -- 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, training on databases, and special computer chips.

Alibaba Group Holding Ltd. today released an artificial intelligence model that it says can outperform GPT-5.2 and Claude 4.5 Opus at some tasks. The new algorithm, Qwen3.5, is available on Hugging ...

Google’s first-stage retrieval still runs on word matching, not AI magic. Here’s how to use content scoring tools accordingly ...

Umbrella or sun cap? Buy or sell stocks? When it comes to questions like these, many people today rely on AI-supported recommendations. Chatbots such as ChatGPT, AI-driven weather forecasts, and ...

Dr. James McCaffrey presents a complete end-to-end demonstration of decision tree regression from scratch using the C# language. The goal of decision tree regression is to predict a single numeric ...

With the introduction of adaptive deep brain stimulation (aDBS) for Parkinson's disease, new questions emerge regarding who, why, and how to treat. This paper outlines the pathophysiological rationale ...

A new study has demonstrated how networks of spiking nanolasers could emulate a key principle of brain function: to imagine things that we cannot directly perceive by sampling from internal models of ...