Chatbot software is a computer program designed to simulate conversation with human users, usually through text or voice interactions. It uses rules or artificial intelligence to understand questions and provide responses. Chatbots are often used to automate customer service, provide information, or assist with simple tasks.
Transformer decoders are a component of the transformer neural network architecture, designed to generate sequences one step at a time. They work by taking in previously generated data and context information to predict the next item in a sequence, such as the next word in a sentence. Transformer decoders are often used in tasks that…
Sentiment analysis systems are computer programmes that automatically identify and interpret the emotional tone behind pieces of text. They determine whether the sentiment expressed is positive, negative, or neutral, and sometimes even more detailed moods. These systems are commonly used to analyse texts such as social media posts, reviews, and customer feedback to understand public…
Conditional Random Fields, or CRFs, are a type of statistical model used to predict patterns or sequences in data. They are especially useful when the data has some order, such as words in a sentence or steps in a process. CRFs consider the context around each item, helping to make more accurate predictions by taking…
End-to-End Memory Networks are a type of artificial intelligence model designed to help computers remember and use information over several steps. They combine a memory component with neural networks, allowing the model to store facts and retrieve them as needed to answer questions or solve problems. This approach is especially useful for tasks where the…
Intent shadowing occurs when a specific intent in a conversational AI or chatbot system is unintentionally overridden by a more general or broader intent. This means the system responds with the broader intent’s answer instead of the more accurate, specific one. It often happens when multiple intents have overlapping training phrases or when the system…
Intelligent Document Processing (IDP) refers to the use of artificial intelligence and automation technologies to read, understand, and extract information from documents. It combines techniques such as optical character recognition, natural language processing, and machine learning to process both structured and unstructured data from documents like invoices, contracts, and forms. This helps organisations reduce manual…
Language modelling heads are the final layers in neural network models designed for language tasks, such as text generation or prediction. They take the processed information from the main part of the model and turn it into a set of probabilities for each word in the vocabulary. This allows the model to choose the most…
Positional encoding is a technique used in machine learning models, especially transformers, to give information about the order of data, like words in a sentence. Since transformers process all words at once, they need a way to know which word comes first, second, and so on. Positional encoding adds special values to each input so…
Tokenisation strategies are methods used to split text into smaller pieces called tokens, which can be words, characters, or subwords. These strategies help computers process and understand language by breaking it down into more manageable parts. The choice of strategy can affect how well a computer model understands and generates text, as different languages and…