生成性人工智能和LLMs自然语言处理和生成性对抗网络

English | 2024 | ISBN: 3111424634 | 289 pages | True EPUB,MOBI | 6.27 MB

Generative artificial intelligence (GAI) and large language models (LLM) are machine learning algorithms that operate in an unsupervised or semi-supervised manner. These algorithms leverage pre-existing content, such as text, photos, audio, video, and code, to generate novel content. The primary objective is to produce authentic and novel material. In addition, there exists an absence of constraints on the quantity of novel material that they are capable of generating. New material can be generated through the utilization of Application Programming Interfaces (APIs) or natural language interfaces, such as the ChatGPT developed by Open AI and Bard developed by Google.

The field of generative artificial intelligence (AI) stands out due to its unique characteristic of undergoing development and maturation in a highly transparent manner, with its progress being observed by the public at large. The current era of artificial intelligence is being influenced by the imperative to effectively utilise its capabilities in order to enhance corporate operations. Specifically, the use of large language model (LLM) capabilities, which fall under the category of Generative AI, holds the potential to redefine the limits of innovation and productivity. However, as firms strive to include new technologies, there is a potential for compromising data privacy, long-term competitiveness, and environmental sustainability.

This book delves into the exploration of generative artificial intelligence (GAI) and LLM. It examines the historical and evolutionary development of generative AI models, as well as the challenges and issues that have emerged from these models and LLM. This book also discusses the necessity of generative AI-based systems and explores the various training methods that have been developed for generative AI models, including LLM pretraining, LLM fine-tuning, and reinforcement learning from human feedback. Additionally, it explores the potential use cases, applications, and ethical considerations associated with these models. This book concludes by discussing future directions in generative AI and presenting various case studies that highlight the applications of generative AI and LLM.

中文|2024|ISBN:3114124634|289页|True EPUB，MOBI|6.27 MB生成型人工智能（GAI）和大型语言模型（LLM）是以无监督或半监督方式运行的机器学习算法。这些算法利用已有的内容，如文本、照片、音频、视频和代码，来生成新颖的内容。主要目标是制作真实新颖的材料。此外，它们能够产生的新材料的数量没有限制。新材料可以通过使用应用程序编程接口（API）或自然语言接口来生成，例如Open AI开发的ChatGPT和谷歌开发的Bard。 生成型人工智能（AI）领域因其以高度透明的方式发展和成熟的独特特征而脱颖而出，其进展受到广大公众的关注。当前的人工智能时代正受到有效利用其能力以加强企业运营的必要性的影响。具体来说，使用大语言模型（LLM）功能（属于生成型人工智能范畴）有可能重新定义创新和生产力的极限。然而，随着企业努力引入新技术，有可能损害数据隐私、长期竞争力和环境可持续性。 本书深入探讨了生成人工智能（GAI）和LLM的探索。它考察了生成式人工智能模型的历史和进化发展，以及这些模型和LLM带来的挑战和问题。本书还讨论了基于生成人工智能系统的必要性，并探讨了为生成人工智能模型开发的各种训练方法，包括LLM预训练、LLM微调和从人类反馈中强化学习。此外，它还探讨了与这些模型相关的潜在用例、应用程序和伦理考虑。本书最后讨论了生成式人工智能的未来发展方向，并介绍了各种案例研究，突出了生成式AI和LLM的应用。

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