The Evolution, Application, and Future Challenges of Large Language Model

Large language models have been adopted as a fundamental advance in artificial intelligence, showing natural language understanding and natural language generation systems that are almost humanly good, through pre-training on massive quantities of text. This paper gives an attempt to review its main technologies, extensive usage, and challenges systematically. It begins with outlining the technological platforms behind its growth such as establishment of pre-training and a fine-tuning paradigm, scaling law to emergent capability development and state-of-the-art progress in secure alignment and efficient deployment. Second, its revolutionary effect on content generation, machine translation and intelligent answering of questions were discussed. And then goes to the primary issues that the model has in factual accuracy, security, bias, and energy consumption. And lastly, it has an outlook to the future on how the technology will evolve into additional reliability, security, and accessibility.