Glossary for Advanced Users
Expert Systems are AI systems that emulate human expertise in specific domains. By capturing and codifying human knowledge, Expert Systems assist businesses in decision-making, problem-solving, and providing expert-level insights to users.
Explainable Artificial Intelligence focuses on developing AI systems that can provide understandable explanations for their decisions and behaviours. Transparent and interpretable AI models are essential for building trust, ensuring fairness, and addressing ethical concerns. Businesses can benefit from explainable AI by gaining insights into AI-driven predictions and making informed decisions based on those insights.
Facial Recognition is an AI technology that involves identifying and verifying individuals based on their facial characteristics. It analyses facial features such as the shape of the face, eyes, nose, and mouth to match or identify individuals. Facial Recognition has applications in security systems, access control, and personalised customer experiences.
Feature Extraction refers to the process of identifying and selecting the most relevant features from raw data to enhance AI model performance. By extracting key information, businesses can improve efficiency, reduce noise, and focus on crucial variables for analysis.
Federated Learning is a privacy-preserving technique where AI models are trained across multiple decentralised devices or systems without sharing raw data. Instead, only aggregated model updates are exchanged, ensuring data privacy and security. Federated Learning enables businesses to harness the collective intelligence of distributed devices while maintaining data confidentiality.
Forecasting involves predicting future outcomes or trends based on historical data and patterns. By analysing past data and applying statistical techniques, businesses can make informed forecasts for sales, demand, market trends, and resource allocation. Accurate forecasting helps organisations optimise operations, plan strategies, and make data-driven decisions.
Fuzzy Logic is a mathematical framework that deals with uncertainty and imprecision. By assigning degrees of truth to statements, Fuzzy Logic allows businesses to handle subjective or ambiguous information, improving decision-making and reasoning in complex situations.
Game Theory is a mathematical framework used to study and analyse strategic decision-making in situations involving multiple actors or players. It helps businesses understand and predict the behaviour of competitors, customers, and other stakeholders. Game Theory finds applications in areas like pricing strategies, auction design, and negotiation tactics.
Generative Adversarial Networks are a type of Machine Learning model that consists of two neural networks: a generator and a discriminator. GANs are used to generate synthetic data that resembles real data by learning from training examples. They find applications in image generation, video synthesis, and data augmentation.
