Researchers generated images from noise, using orders of magnitude less energy than current generative AI models require.

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 ...

A new study published in the journal Minerals sheds light on this sweeping shift. Titled Big Data and AI in Geoscience: From ...

Data is the life-blood of physical AI. Collecting real-life data is expensive. Generative AI and diffusion to create ...

Ineffable Intelligence Ltd., a startup led by former Google DeepMind principal research scientist David Silver, is reportedly raising $1 billion in funding.

A new study reveals that the next generation of blockchain defenses will not rely on fixed rules alone but on adaptive, learning-based systems capable of evolving alongside intelligent adversaries.

AI became powerful because of interacting mechanisms: neural networks, backpropagation and reinforcement learning, attention, training on databases, and special computer chips.

Drug discovery pipelines are notorious for being costly, slow, and failure-prone, leading to AI and machine learning becoming more commonplace to accelerate progress and improve outcomes. Currently, ...

Researchers have developed a diagnostic panel that identifies cognitive decline by analyzing how blood proteins fold. This ...

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 ...