Definition of large language model (original) (raw)
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The foundation of many of today's AI systems. AI applications use a large language model (LLM) to understand natural language, answer questions and generate original content. An LLM is a type of artificial neural network (ANN) with billions of interconnections that analyze enormous quantities of text and images. The LLM is "trained" on data, sometimes massive amounts, and this learning phase takes the most computer time. Fine tuning the model makes it usable for different AI applications such as chatbots and text generation. See deep learning, neural network, AI weights and biases and AI transformer.
Part of a Robot
Along with electronic systems for physical motion, mechanical robots use language models for machine vision and natural language.
The World Is Online
The entire world's information is available over the Internet from websites, blogs and social media, from which trillions of data items have been extracted to train a large language model. See AI dataset.
Small, Edge and Reasoning Models
Designed for a specific purpose such as spam detection or website assistance, small language models (SLMs) have fewer layers and interconnections than LLMs. Edge language models are SLMs that run locally in a PC, and reasoning models tackle more complex problems than LLMs (see small language model, edge AI and large reasoning model). See GPT, ChatGPT, LLaMA, LaMDA, PaLM and Gemini chatbot.
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