Neural Language Model
A neural language model is a type of artificial intelligence model that uses neural networks to predict the probability of sequences of words or tokens in natural language. It learns patterns and relationships from large text datasets to generate coherent text, complete sentences, or perform tasks like translation and summarization. These models form the foundation of modern natural language processing (NLP) systems, including large language models (LLMs) like GPT and BERT.
Developers should learn neural language models when working on NLP applications such as chatbots, text generation, sentiment analysis, or machine translation, as they provide state-of-the-art performance in understanding and generating human language. They are essential for building AI-driven features that require contextual language understanding, such as in search engines, content recommendation systems, or automated customer support tools.