This blog post is the second in our Neural Super Sampling (NSS) series. The post explores why we introduced NSS and explains its architecture, training, and inference components. In August 2025, we ...

MicroAlgo Inc. (the "Company" or "MicroAlgo") (NASDAQ: MLGO), today announced that they have developed a set of quantum algorithms for feedforward neural networks, breaking through the performance ...

A team of researchers in the Netherlands has proposed a new way of designing computer models of the brain—an approach that ...

Chinese artificial intelligence developer DeepSeek today released a new series of open-source large language models. V4, as ...

MicroCloud Hologram Inc. has announced the creation of a noise-resistant Deep Quantum Neural Network (DQNN) architecture, which aims to advance quantum computing and enhance the efficiency of quantum ...

NAS methods can generally be classified based on tailored designs from the following aspects: search space, search strategy, and evaluation strategy. In particular, search space can be further ...

Building neural networks from scratch in Python with NumPy is one of the most effective ways to internalize deep learning fundamentals. By coding forward and backward propagation yourself, you see how ...

A neural-network-based controller adapts in real time to switching reference signals in piezoelectric nano-positioning stages ...

Graph theory and computational modeling reveal that neural network architecture biases the male Caenorhabditis elegans brain toward prioritized sexual behaviors.

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of neural network quantile regression. The goal of a quantile regression problem is to predict a single numeric ...