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Decoding Large Language Models: Their Roles, Costs, and Real-World Impact
Large Language Models (LLMs) have become pivotal in the realm of artificial intelligence, driving advancements in natural language processing (NLP) and enabling a myriad of applications across various industries. These models, trained on vast amounts of data, can understand, generate, and manipulate human language with remarkable proficiency. This article delves into the different types of LLMs available on the internet, highlighting their distinctive features, use cases, and contributions to the evolving landscape of AI.
Understanding Large Language Models (LLMs)
LLMs are deep learning models designed to process and generate human language. They are characterized by their large number of parameters, which enable them to capture complex linguistic patterns and produce coherent text. These models are typically built on transformer architectures, which excel at handling sequential data and maintaining context over long text sequences.
Types of Large Language Models
- GPT Series (Generative Pre-trained Transformers)
