Lexical filters are tools or algorithms used to include or exclude words or phrases based on specific criteria. They help process text by filtering out unwanted or irrelevant terms, making analysis and search tasks more efficient. These filters are commonly used in applications like search engines, spam detection, and text analysis to improve the quality…
Syntax parsing is the process of analysing a sequence of words or symbols according to the rules of a language to determine its grammatical structure. It breaks down sentences or code into parts, making it easier for computers to understand their meaning. Syntax parsing is a key step in tasks like understanding human language or…
Dialogue memory is a system or method that allows a programme, such as a chatbot or virtual assistant, to remember and refer back to previous exchanges in a conversation. This helps the software understand context, track topics, and respond more naturally to users. With dialogue memory, interactions feel more coherent and less repetitive, as the…
Prompt routing is the process of directing user prompts or questions to the most suitable AI model or system based on their content or intent. This helps ensure that the response is accurate and relevant by leveraging the strengths of different models or tools. It is often used in systems that handle a wide variety…
Embedding injection is a security vulnerability that occurs when untrusted input is inserted into a system that uses vector embeddings, such as those used in natural language processing or search. Attackers can exploit this by crafting inputs that manipulate or poison the embedding space, causing systems to retrieve incorrect or harmful results. This can lead…
Token drift refers to the gradual change in the meaning, value, or usage of a digital token over time. This can happen as a result of changes in the underlying technology, platform updates, or shifts in the way users interact with the token. Token drift can cause confusion, unexpected behaviour, or compatibility issues if not…
Semantic inference models are computer systems designed to understand the meaning behind words and sentences. They analyse text to determine relationships, draw conclusions, or identify implied information that is not directly stated. These models rely on patterns in language and large datasets to interpret subtle or complex meanings, making them useful for tasks like question…
Semantic drift compensation is the process of adjusting for changes in the meaning of words or phrases over time or across different contexts. As language evolves, the same term can develop new meanings or lose old ones, which can cause confusion in language models, search engines, or translation systems. Semantic drift compensation uses algorithms or…
AI-powered customer support uses artificial intelligence to help answer customer questions, solve problems, and provide information automatically. It can include chatbots, virtual assistants, and automated email responses, all designed to help customers quickly and efficiently. This technology can work around the clock, handle many requests at once, and learn from previous interactions to improve over…
Semantic knowledge injection is the process of adding meaningful information or context to a computer system, such as a machine learning model or database, so it can understand and use that knowledge more effectively. This often involves including facts, relationships, or rules about a subject, rather than just raw data. By doing this, the system…