Large-Language-Models
Large-Language-Models (LLMs) are a sophisticated form of Artificial-Intelligence that utilize Deep-Learning to understand, summarize, and generate text. These models are primarily built on the Transformer architecture, which was introduced by researchers at Google in the seminal 2017 paper 'Attention Is All You Need'. By training on massive datasets, LLMs develop a complex understanding of Natural-Language-Processing.
Prominent examples of these models include GPT-4 by OpenAI, Claude by Anthropic, and Llama-3 by Meta. The performance of these systems is often tied to the number of Parameters they contain, with modern models reaching into the trillions. According to research published in Nature, the scale of data and computation has led to emergent abilities in Generative-AI. However, developers must still address challenges such as Hallucination and ethical alignment through techniques like Reinforcement-Learning-from-Human-Feedback.