WiMi Explores the Application of Neural Networks in Parameter Optimization for Dual-Field Quantum Key Distribution

WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, announced that they are researching the use of neural ...

Hidden seismicity patterns before large earthquakes uncovered

When and where the next large earthquake will strike remains one of the most difficult questions in geoscience. Researchers ...
IEEE

In-Hardware Training Chip Based on CMOS Invertible Logic for Machine Learning

Abstract: Deep Neural Networks (DNNs) have recently shown state-of-the-art results on various applications, such as computer vision and recognition tasks. DNN inference engines can be implemented in ...

In 1989, Yann LeCun helped show that neural networks could read handwritten ZIP codes, laying groundwork for systems that later read bank checks

In 1989, a computer scientist tackled the messy challenge of reading handwritten zip codes for the US Post Office. This ...

In 1986, three scientists improved backpropagation, making neural networks learn effectively from data

A groundbreaking 1986 technique called backpropagation revolutionized artificial intelligence, enabling computers to learn ...
Tech Xplore

Geospatial upgrade gives TabPFN sharper local predictions on datasets up to 70,000 rows

A new development in data science has given one popular machine learning tool an improved sense of place, enabling it to make ...
Tech Xplore on MSN

Forgetting may be the secret to better AI language learning

Giving AI a human-like memory limitation may actually help it learn language better. In their new proof-of-principle study, ...

Toward experiment-guided AlphaFold: Researchers overcome AI tool's single-conformation limitation

The AI-based program AlphaFold predicts a protein's 3D structure with remarkable accuracy. However, it tends to reduce heterogeneous structures to a single dominant conformation, or shape, and ...
GitHub

Deep Learning Framework from Scratch

A lightweight deep learning framework built entirely with NumPy. This project implements the core components of modern neural networks including forward propagation, backpropagation, optimizers, ...