What Is AI? The Definitions Regulators And Standards Bodies Use
AI has a working definition that the OECD, the EU AI Act and NIST broadly share. Here is what it says, what it leaves out and why the wording matters.
KNOWLEDGE HUB / AI
AI Fundamentals
The core ideas behind artificial intelligence, machine learning and the models built with them.
AI, Machine Learning, Deep Learning And Generative AI: How They Fit Together
These terms are often used as if they mean the same thing. They do not. Here is how they nest inside one another, and where foundation models and generative AI fit.
How A Machine Learning Model Is Built: Data, Training, Parameters And Inference
A plain walk through the life of a machine learning model, from collecting data and training it to running it on new inputs and keeping it healthy in production.
Three Ways Machines Learn: Supervised, Unsupervised And Reinforcement Learning
Machine learning methods differ in the kind of feedback a model gets. Here is how supervised, unsupervised, self-supervised and reinforcement learning work, with examples of each.
Overfitting, Evaluation And The Basics Of Trustworthy AI
A model that aces its training data can still fail in the real world. Learn how overfitting happens, how held-out testing catches it and how NIST describes trustworthy AI.