Morning Overview on MSN

Mind-blowing photonic chips teach robots using light instead of electronics

Researchers report building photonic computing chips that use light pulses to train spiking neural networks on robotic-control-style benchmark tasks, aiming to shift more of the learning workload from ...
eLife

“What” × “When” working memory representations using Laplace Neural Manifolds

The results include a comparison between two different basis functions for temporal selectivity and how these generate different predictions for the dynamics of neural populations. The conclusions are ...
The Malaysian Reserve

MicroCloud Hologram Inc. Achieves Breakthrough in Practically Deployable Quantum Recurrent Neural Network (QRNN) Technology Oriented Toward Sequential Learning

MicroCloud Hologram Inc. (NASDAQ: HOLO), (“HOLO” or the “Company”), a technology service provider, released a core quantum machine learning technology oriented toward sequential learning tasks—the ...
i-SCOOP

Attention is all you need, the Paper that revolutionized Natural Language Processing

Discover the groundbreaking concepts behind "Attention Is All You Need," the 2017 Google paper that introduced the Transformer architecture. Learn how self-attention, parallelization, and Q/K/V ...
Neuroscience News

What an AI Birdsong Decoder Tells Us About the Human Brain

Researchers develop TweetyBERT, an AI model that automatically decodes canary songs to help neuroscientists understand the neural basis of speech.

AI Design Copilots Reduce Time-To-Market For Physical Design

Neural Concept is helping launch products at 2X the speed. It does this by capturing past knowledge into AI-based ...
eLife

Dynamics of mesoscale brain network during visual discrimination learning revealed by chronic, large-scale single-unit recording

During the acquisition of correct rejection response, rankings of functional connection separated for cortical and subcortical regions, which is predictive of the peak timing of visual information ...

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

Beijing, Feb. 06, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...
IEEE

Assisting Training of Deep Spiking Neural Networks With Parameter Initialization

Abstract: Spiking neural networks (SNNs) exhibit significant advantages in terms of information encoding, computational capabilities, and power usage. We regard initializing weight distribution as a ...
Beebom

What is CNN in Deep Learning? The AI Behind Computer Vision

CNN in deep learning is a special type of neural network that can understand images and visual information. It works just like human vision: first it detects edges, lines and then recognizes faces and ...
Scientific Research Publishing

Chen, H., Zhang, Y., Kalra, M.K., Lin, F., Chen, Y., Liao, P., et al. (2017) Low-Dose CT with a Residual Encoder-Decoder Convolutional Neural Network. IEEE Transactions on ...

ABSTRACT: Magnetic Resonance Imaging (MRI) is commonly applied to clinical diagnostics owing to its high soft-tissue contrast and lack of invasiveness. However, its sensitivity to noise, attributable ...