Neural Network
A neural network is a computing system inspired by the human brain, composed of interconnected nodes (neurons) organized in layers that process information and learn patterns from data.
In Depth
Neural networks are the building blocks of modern AI. They consist of input layers (receiving data), hidden layers (processing and learning patterns), and output layers (producing results). Each connection between neurons has a weight that adjusts during training, allowing the network to learn from examples.
In customer support AI, neural networks power everything from text classification and entity extraction to response generation and voice processing. Convolutional neural networks (CNNs) handle image analysis for visual support tickets, recurrent neural networks (RNNs) process sequential data like conversation flows, and transformer networks power the large language models that drive modern AI agents. Understanding neural networks helps teams evaluate AI capabilities and set realistic expectations for what AI support systems can and cannot do.
Related Terms
Deep Learning
Deep learning is a subset of machine learning that uses multi-layered neural networks to learn complex patterns and representations from large volumes of data.
Machine Learning
Machine learning is a branch of AI where systems learn patterns from data and improve their performance over time without being explicitly programmed for each task.
Transformer Model
A transformer is a deep learning architecture that uses self-attention mechanisms to process sequential data in parallel, forming the foundation of modern large language models.
Learn More
