Semantic segmentation is a process in computer vision where each pixel in an image is classified into a specific category, such as road, car, or tree. This technique helps computers understand the contents and layout of an image at a detailed level. It is used to separate and identify different objects or regions within an…
AI model calibration is the process of adjusting a model so that its confidence scores match the actual likelihood of its predictions being correct. When a model is well-calibrated, if it predicts something with 80 percent confidence, it should be right about 80 percent of the time. Calibration helps make AI systems more trustworthy and…
Transferable representations are ways of encoding information so that what is learned in one context can be reused in different, but related, tasks. In machine learning, this often means creating features or patterns from data that help a model perform well on new, unseen tasks without starting from scratch. This approach saves time and resources…
AI explainability frameworks are tools and methods designed to help people understand how artificial intelligence systems make decisions. These frameworks break down complex AI models so that their reasoning and outcomes can be examined and trusted. They are important for building confidence in AI, especially when the decisions affect people or require regulatory compliance.
Neural network robustness is the ability of a neural network to maintain accurate and reliable performance even when faced with unexpected or challenging inputs, such as noisy data or intentional attacks. Robustness helps ensure that the network does not make mistakes when small changes are made to the input. This is important for safety and…
Contextual bandit algorithms are a type of machine learning method used to make decisions based on both past results and current information. They help choose the best action by considering the context or situation at each decision point. These algorithms learn from feedback over time to improve future choices, balancing between trying new actions and…
AI-driven decision systems are computer programmes that use artificial intelligence to help make choices or solve problems. They analyse data, spot patterns, and suggest or automate decisions that might otherwise need human judgement. These systems are used in areas like healthcare, finance, and logistics to support or speed up important decisions.
Cognitive architecture design is the process of creating a structure that models how human thinking and reasoning work. It involves building systems that can process information, learn from experience, and make decisions in ways similar to people. These designs are used in artificial intelligence and robotics to help machines solve problems and interact more naturally…
Neural network generalisation refers to the ability of a neural network to perform well on new, unseen data after being trained on a specific set of examples. It shows how well the network has learned patterns and rules, rather than simply memorising the training data. Good generalisation means the model can make accurate predictions in…
Behavioural threat analytics is a method used to detect and assess potential security threats by analysing patterns in user or system behaviour. It involves monitoring actions and comparing them to typical behaviour to spot unusual activities that could indicate a risk, such as fraud or cyberattacks. This approach helps organisations identify threats early, often before…