Model Showcase 2: New Architectural Approaches in Language Models

This column focuses on open-weight models from China, Liquid Foundation Models, performant lean models, and a Titan from ...
DatacenterDynamics

Etched.ai raises $500m for a $5bn valuation – report

AI chip startup Etched.ai has reportedly raised $500 million in a funding round that was led by investment firm Stripes and ...
Analytics Insight

Best Deep Learning Books to Read in 2026

Overview: Master deep learning with these 10 essential books blending math, code, and real-world AI applications for lasting ...
Beebom

What is Deep Learning in AI? Understanding How AI Really Works

Deep learning uses multi-layered neural networks that learn from data through predictions, error correction and parameter adjustments. It started with the ...
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 ...
VentureBeat

Google’s ‘Nested Learning’ paradigm could solve AI's memory and continual learning problem

Researchers at Google have developed a new AI paradigm aimed at solving one of the biggest limitations in today’s large language models: their inability to learn or update their knowledge after ...
Frontiers

Deep learning in intracranial EEG for seizure detection: advances, challenges, and clinical applications

Deep learning has emerged as a transformative tool for the automated detection and classification of seizure events from intracranial EEG (iEEG) recordings. In this review, we synthesize recent ...
C&EN

Deep Learning-Based Shape Classification for Hyperspectral-Imaged Microplastics

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. Figure 1 illustrates the overall workflow of the hyperspectral ...
Scientific Research Publishing

Yin, C.L., Zhu, Y.F., Fei, J.L. and He, X.Z. (2017) A Deep Learning Approach for Intrusion Detection Using Recurrent Neural Networks. IEEE Access, 5, 21954-21961.

ABSTRACT: Cybersecurity has emerged as a global concern, amplified by the rapid expansion of IoT devices and the growing digitization of systems. In this context, traditional security solutions such ...