neural networks

Black Box Model

A black box model is an AI system whose internal decision process is difficult to inspect or explain, even when its predictions are useful.

Jul 18, 2026 by Samantha Reed • 1 min read

Transformer

A transformer is a neural network architecture built on attention and used in modern language, vision, audio, video, and multimodal AI models.

Jul 15, 2026 by Daniel Mercer • 1 min read

Attention Mechanism

An attention mechanism helps an AI model focus on the most relevant parts of its input when interpreting information or generating an output.

Jul 9, 2026 by Olivia Grant • 1 min read

YOLO (You Only Look Once)

By Marcus Lee Jul 1, 2026 • 1 min read

YOLO (You Only Look Once) is a real-time computer vision approach that detects and classifies multiple objects in one image processing pass.

Neuro-Symbolic AI

By Marcus Lee Jun 23, 2026 • 1 min read

Neuro-symbolic AI combines neural learning with explicit symbols, rules, or logic to support structured reasoning.

Recurrent Neural Network (RNN)

By Daniel Mercer Jun 23, 2026 • 1 min read

A recurrent neural network (RNN) is a deep learning model that carries information across sequential inputs such as text, speech, and time-series data.

X-Vector

By Marcus Lee Jun 4, 2026 • 1 min read

An x-vector is a neural speaker embedding that represents a voice for speaker verification, diarization, clustering, and audio analysis.

Perceptron

By Daniel Mercer Jun 1, 2026 • 1 min read

A perceptron is a simple artificial neuron that combines weighted inputs to make a binary classification and forms a foundation of neural networks.

XOR Problem

By Marcus Lee May 28, 2026 • 1 min read

The XOR problem is a classic machine learning example showing why neural networks need hidden layers and nonlinear activations for some patterns.

Parameter

By Daniel Mercer May 28, 2026 • 1 min read

A parameter is a learned numerical value, such as a neural network weight, that determines how an AI model transforms input into output.

Hybrid AI

By Marcus Lee May 18, 2026 • 1 min read

Hybrid AI combines different artificial intelligence approaches, often linking machine learning with rules, search, or symbolic reasoning.

Normalization

By Daniel Mercer May 14, 2026 • 1 min read

Normalization transforms data or neural network activations into a consistent scale or distribution to support stable and efficient AI model training.

Xception

By Marcus Lee Apr 30, 2026 • 1 min read

Xception is a computer vision architecture that uses depthwise separable convolutions for efficient image classification and feature extraction.

Mixture of Experts (MoE)

By Daniel Mercer Apr 29, 2026 • 1 min read

A mixture of experts (MoE) is an AI architecture that routes each input to selected subnetworks, increasing capacity without activating every parameter.