Category: Natural Language Processing

Intent Shadowing

Post author By EfficiencyAI
Post date 31 May 2025
Categories In Artificial Intelligence, Explainability & Interpretability, Natural Language Processing

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

Post author By EfficiencyAI
Post date 31 May 2025
Categories In Artificial Intelligence, Automation Technologies, Natural Language Processing

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

Post author By EfficiencyAI
Post date 31 May 2025
Categories In Artificial Intelligence, Deep Learning, Natural Language Processing

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

Post author By EfficiencyAI
Post date 31 May 2025
Categories In Deep Learning, Embeddings & Representations, Natural Language Processing

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

Post author By EfficiencyAI
Post date 31 May 2025
Categories In Artificial Intelligence, Embeddings & Representations, Natural Language Processing

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…

Transformer Decoders

Post author By EfficiencyAI
Post date 31 May 2025
Categories In Artificial Intelligence, Deep Learning, Natural Language Processing

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…

Few-Shot Prompting

Post author By EfficiencyAI
Post date 31 May 2025
Categories In Artificial Intelligence, Natural Language Processing, Regulatory Compliance

Few-shot prompting is a technique used with large language models where a small number of examples are provided in the prompt to guide the model in performing a specific task. By showing the model a handful of input-output pairs, it can better understand what is expected and generate more accurate responses. This approach is useful…