Remove AI Research Remove Natural Language Processing Remove Neural Network
article thumbnail

AI trends in 2023: Graph Neural Networks

AssemblyAI

While AI systems like ChatGPT or Diffusion models for Generative AI have been in the limelight in the past months, Graph Neural Networks (GNN) have been rapidly advancing. And why do Graph Neural Networks matter in 2023? What is the current role of GNNs in the broader AI research landscape?

article thumbnail

Artificial Neural Network: A Comprehensive Guide

Pickl AI

Summary: Artificial Neural Network (ANNs) are computational models inspired by the human brain, enabling machines to learn from data. Introduction Artificial Neural Network (ANNs) have emerged as a cornerstone of Artificial Intelligence and Machine Learning , revolutionising how computers process information and learn from data.

professionals

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

This AI Research Diagnoses Problems in Recurrent Neural Networks RNN-based Language Models and Corrects them to Outperform Transformer-based Models on Long Sequence Tasks

Marktechpost

Recurrent Neural Networks were the trailblazers in natural language processing and set the cornerstone for future advances. RNNs were simple in structure with their contextual memory and constant state size, which promised the capacity to handle long sequence tasks. Don’t Forget to join our 55k+ ML SubReddit.

article thumbnail

This AI Paper from Stanford Introduces Codebook Features for Sparse and Interpretable Neural Networks

Marktechpost

Neural networks have become indispensable tools in various fields, demonstrating exceptional capabilities in image recognition, natural language processing, and predictive analytics. The sum of these vectors is then passed to the next layer, creating a sparse and discrete bottleneck within the network.

article thumbnail

Can AI Be Both Powerful and Efficient? This Machine Learning Paper Introduces NASerEx for Optimized Deep Neural Networks

Marktechpost

Deep Neural Networks (DNNs) represent a powerful subset of artificial neural networks (ANNs) designed to model complex patterns and correlations within data. These sophisticated networks consist of multiple layers of interconnected nodes, enabling them to learn intricate hierarchical representations.

article thumbnail

A New AI Research Proposes VanillaNet: A Novel Neural Network Architecture Emphasizing the Elegance and Simplicity of Design while Retaining Remarkable Performance in Computer Vision Tasks

Marktechpost

Artificial neural networks have advanced significantly over the past few decades, propelled by the notion that more network complexity results in better performance. Modern technology has amazing processing capacity, enabling neural networks to perform these jobs excellently and efficiently.

article thumbnail

This Paper Proposes RWKV: A New AI Approach that Combines the Efficient Parallelizable Training of Transformers with the Efficient Inference of Recurrent Neural Networks

Marktechpost

Natural language processing, conversational AI, time series analysis, and indirect sequential formats (such as pictures and graphs) are common examples of the complicated sequential data processing jobs involved in these. All credit for this research goes to the researchers of this project.