Output anchors are specific points or markers in a process or system where information, results, or data are extracted and made available for use elsewhere. They help organise and direct the flow of outputs so that the right data is accessible at the right time. Output anchors are often used in software, automation, and workflow…
Syntax coherence refers to the logical and consistent arrangement of words and phrases within sentences, so that the meaning is clear and easy to follow. It ensures that the structure of sentences supports the intended message, making communication more effective. Without syntax coherence, writing can become confusing or ambiguous, making it harder for the reader…
Token usage refers to the number of pieces of text, called tokens, that are processed by language models and other AI systems. Tokens can be as short as one character or as long as one word, depending on the language and context. Tracking token usage helps manage costs, performance, and ensures that the input or…
Named recognition refers to the process of identifying and classifying proper names, such as people, organisations, or places, within a body of text. This task is often handled by computer systems that scan documents to pick out and categorise these names. It is a foundational technique in natural language processing used to make sense of…
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…
Latent injection is a technique used in artificial intelligence and machine learning where information is added or modified within the hidden, or ‘latent’, layers of a model. These layers represent internal features that the model has learned, which are not directly visible to users. By injecting new data or signals at this stage, developers can…
Sparse vectors are lists of numbers where most of the entries are zero. Instead of storing every value, including the zeros, sparse vectors are often represented by only recording the positions and values of the non-zero elements. This makes them much more efficient to work with when dealing with large datasets that contain mostly zero…
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…
Neural collapse is a phenomenon observed in deep neural networks during the final stages of training, particularly for classification tasks. It describes how the outputs or features for each class become highly clustered and the final layer weights align with these clusters. This leads to a simplified geometric structure where class features and decision boundaries…