Supervised Learning
Training a model on examples that are already labelled with the right answer. It is the most common approach when you know exactly what you want the system to produce.
Related terms
Speech Recognition
Turning spoken words into text. It underpins voice search, dictation and call transcription, and it now handles accents and background noise far better than it used to.
Model Drift
When a model gets worse over time because the world moved on and it did not. A pricing or demand model trained two years ago quietly stops matching how customers behave now.
AI Bias
When a system produces unfair results because its training data reflected an unfair world. It matters commercially as well as ethically: a biased model makes confidently wrong decisions about real people.
Recommendation Engine
A system that suggests what somebody might want next based on behaviour — the “customers also bought” of an online shop. One of the oldest commercial uses of machine learning.
PerplexityBot
Perplexity’s crawler. Perplexity cites its sources prominently, so being readable by it is one of the more direct routes to a visible citation.
MCP (Model Context Protocol)
An open standard for connecting AI assistants to outside tools and data in a consistent way. It matters to businesses because it is how an assistant might one day query your booking system directly.