Challenges And Applications Of Generative Large Language Models
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Challenges and Applications of Generative Large Language Models
Large Language Models (LLMs) are a form of generative AI, based on Deep Learning, that rely on very large textual datasets, and are composed of hundreds of millions (or even billions) of parameters. LLMs can be trained and then refined to perform several NLP tasks like generation of text, summarization, translation, prediction, and more. Challenges and Applications of Generative Large Language Models assists readers in understanding LLMs, their applications in various sectors, challenges that need to be encountered while developing them, open issues, and ethical concerns. LLMs are just one approach in the huge set of methodologies provided by AI. The book, describing strengths and weaknesses of such models, enables researchers and software developers to decide whether an LLM is the right choice for the problem they are trying to solve. AI is the new buzzword, in particular Generative AI for human language (LLMs). As such, an overwhelming amount of hype is obfuscating and giving a distorted view about AI in general, and LLMs in particular. Thus, trying to provide an objective description of LLMs is useful to any person (researcher, professional, student) who is starting to work with human language. The risk, otherwise, is to forget the whole set of methodologies developed by AI in the last decades, sticking with only one model which, although very powerful, has known weaknesses and risks. Given the high level of hype around such models, Challenges and Applications of Generative Large Language Models (LLMs) enables readers to clarify and understand their scope and limitations.• Provides a clear and objective description of LLMs, with their strengths and weaknesses.• Demonstrates current applications of LLMs, along with strengths and known issues in each application.• Covers not only the advantages but also risks that LLMs bring today, enabling readers to understand whether a particular LLM fits the problem at hand.
Applications, Challenges, and the Future of ChatGPT
The rapid progress of artificial intelligence (AI) technologies has resulted in a complicated landscape for researchers and practitioners. Understanding and navigating the complexities of AI applications, particularly in the context of ChatGPT and its interactions with other AI tools, can be challenging. Researchers and academics need guidance to keep up with these technologies' evolving trends and implications, which leads to gaps in knowledge and implementation strategies. Additionally, the ethical and societal impacts of integrating AI into various domains remain a significant concern, requiring a comprehensive approach to address. Applications, Challenges, and the Future of ChatGPT provide a comprehensive solution to these issues by offering a detailed analysis of the current research trends in AI, focusing on ChatGPT and its interactions with other AI tools. The book delves into how we can effectively utilize ChatGPT and other AI tools to address complex problems by exploring AI applications' collaborative potentials and emerging paradigms. By identifying research gaps and suggesting future directions, this book equips researchers and practitioners with the knowledge and tools necessary to navigate the evolving landscape of AI.
Sustainable Development through Machine Learning, AI and IoT
This book constitutes the refereed proceedings of the Second International Conference on Sustainable Development through Machine Learning, AI and IoT, ICSD 2024, held in Virtual Event, during April 27–28, 2024. The 38 full papers presented here were carefully reviewed and selected from 167 submissions. These papers have been categorized into the following sections: This volume encompassing a diverse array of topics at the intersection of cutting-edge technologies and practical applications. Each chapter delves into innovative approaches and solutions, providing valuable insights into contemporary challenges and opportunities in various domains. Here, we explore the realms of blockchain, data science, machine learning, artificial intelligence, and more, offering in-depth analyses and practical implementations.