Artificial Intelligence has moved from research labs into everyday products, investment strategies and business operations. But AI terminology can feel opaque, even for experienced operators entering the space.
We work closely with AI and emerging tech businesses every day. This guide gives clear, short explanations of key AI terms, whether you are new to the industry or simply want a sharper reference point.
Artificial Intelligence (AI)
Broad term for computer systems performing tasks that normally require human intelligence, such as pattern recognition or decision making.
Machine Learning (ML)
A subset of AI where systems learn from data rather than being explicitly programmed.
Deep Learning
Advanced machine learning using layered neural networks to process complex data such as images, speech or text.\
Neural Network
A computational model inspired by the human brain that identifies patterns in data.
Natural Language Processing (NLP)
AI systems designed to understand and generate human language.
Large Language Model (LLM)
AI models trained on massive text datasets that generate human-like responses. ChatGPT is an example.
Training Data
The dataset used to teach an AI model how to recognise patterns or generate outputs.
Inference
When a trained AI model applies its knowledge to new data.
Fine Tuning
Adjusting a pre-trained model for a specific task or domain.
AI Agent
An autonomous AI system designed to perform tasks, make decisions or interact with users independently.
Hallucination
When an AI model produces incorrect or invented information.
Compute
The processing power required to train or run AI models.
AI is evolving fast. Understanding the language helps founders, investors and operators make better decisions in an increasingly AI-driven economy.
If you are building or hiring in AI and want market insight or talent guidance, book a call with Priority Tech or reach out directly. Strategic guidance is always available before any recruitment discussion.
