Ai Language Models

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Large Language Models - LLMs

Author : Jagdish Krishanlal Arora
Publisher : Jagdish Krishanlal Arora
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.2/5 (249 download)

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Book Synopsis Large Language Models - LLMs by : Jagdish Krishanlal Arora

Download or read book Large Language Models - LLMs written by Jagdish Krishanlal Arora and published by Jagdish Krishanlal Arora. This book was released on 2024-03-28 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Large Language Models (LLMs) have revolutionized the field of artificial intelligence (AI), enabling computers to understand and generate human-like text on an unprecedented scale. In this comprehensive summary, we explore the intricacies of LLMs, their evolution, applications, benefits, challenges, and future prospects. Evolution of LLMs: The journey of LLMs began with early language models like Word2Vec and GloVe, which laid the foundation for understanding word embeddings. The breakthrough came with transformers, particularly the introduction of GPT (Generative Pre-trained Transformer) series by OpenAI, including GPT-2, GPT-3, and beyond. These models leverage self-attention mechanisms and massive amounts of data for training, leading to remarkable improvements in language understanding and generation capabilities. Applications of LLMs: LLMs find applications across diverse domains, including natural language processing (NLP), machine translation, chatbots, question answering systems, text summarization, sentiment analysis, and more. They power virtual assistants like Siri and Alexa, facilitate language translation services, aid in content creation, and enhance user experiences in various digital platforms. Benefits of LLMs: The key benefits of LLMs include their versatility, scalability, and adaptability. A single model can perform multiple tasks, reducing the need for specialized models for each application. Moreover, LLMs can be fine-tuned with minimal data, making them accessible to a wide range of users. Their performance continues to improve with more data and parameters, driving innovation and advancement in AI research. Challenges and Limitations: Despite their impressive capabilities, LLMs face challenges such as bias, explainability, and accessibility. Biases in training data can lead to biased outputs, while the complex inner workings of LLMs make it challenging to understand their decision-making processes. Moreover, access to large-scale computing resources and expertise is limited, hindering widespread adoption and development. Future Prospects: The future of LLMs holds immense potential, with ongoing research focused on addressing challenges and expanding capabilities. Efforts are underway to mitigate bias, improve explainability, and enhance accessibility. Advancements in LLMs are expected to drive innovation in AI-driven applications, revolutionizing industries and reshaping human-computer interaction. In conclusion, Large Language Models represent a significant milestone in AI research, offering unprecedented capabilities in understanding and generating human-like text. While they present challenges and limitations, ongoing efforts to overcome these hurdles pave the way for a future where LLMs play a central role in shaping the AI landscape. As we continue to unravel the wonders of LLMs, the possibilities for innovation and discovery are limitless

AI Foundations of Large Language Models

Author : Jon Adams
Publisher : Green Mountain Computing
ISBN 13 :
Total Pages : 137 pages
Book Rating : 4./5 ( download)

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Book Synopsis AI Foundations of Large Language Models by : Jon Adams

Download or read book AI Foundations of Large Language Models written by Jon Adams and published by Green Mountain Computing. This book was released on with total page 137 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dive into the fascinating world of artificial intelligence with Jon Adams' groundbreaking book, AI Foundations of Large Language Models. This comprehensive guide serves as a beacon for both beginners and enthusiasts eager to understand the intricate mechanisms behind the digital forces shaping our future. With Adams' expert narration, readers are invited to explore the evolution of language models that have transformed mere strings of code into entities capable of human-like text generation. Key Features: In-depth Exploration: From the initial emergence to the sophisticated development of Large Language Models (LLMs), this book covers it all. Technical Insights: Understand the foundational technology, including neural networks, transformers, and attention mechanisms, that powers LLMs. Practical Applications: Discover how LLMs are being utilized in industry and research, paving the way for future innovations. Ethical Considerations: Engage with the critical discussions surrounding the ethics of LLM development and deployment. Chapters Include: The Emergence of Language Models: An introduction to the genesis of LLMs and their significance. Foundations of Neural Networks: Delve into the neural underpinnings that make it all possible. Transformers and Attention Mechanisms: Unpack the mechanisms that enhance LLM efficiency and accuracy. Training Large Language Models: A guide through the complexities of LLM training processes. Understanding LLMs Text Generation: Insights into how LLMs generate text that rivals human writing. Natural Language Understanding: Explore the advancements in LLMs' comprehension capabilities. Ethics and LLMs: A critical look at the ethical landscape of LLM technology. LLMs in Industry and Research: Real-world applications and the impact of LLMs across various sectors. The Future of Large Language Models: Speculations and predictions on the trajectory of LLM advancements. Whether you're a student, professional, or simply an AI enthusiast, AI Foundations of Large Language Models by Jon Adams offers a riveting narrative filled with insights and foresights. Equip yourself with the knowledge to navigate the burgeoning world of LLMs and appreciate their potential to redefine our technological landscape. Join us on this enlightening journey through the annals of artificial intelligence, where the future of digital communication and creativity awaits.

A Beginner's Guide to Large Language Models

Author : Enamul Haque
Publisher : Enamul Haque
ISBN 13 : 1445263289
Total Pages : 259 pages
Book Rating : 4.4/5 (452 download)

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Book Synopsis A Beginner's Guide to Large Language Models by : Enamul Haque

Download or read book A Beginner's Guide to Large Language Models written by Enamul Haque and published by Enamul Haque. This book was released on 2024-07-25 with total page 259 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Beginner's Guide to Large Language Models: Conversational AI for Non-Technical Enthusiasts Step into the revolutionary world of artificial intelligence with "A Beginner's Guide to Large Language Models: Conversational AI for Non-Technical Enthusiasts." Whether you're a curious individual or a professional seeking to leverage AI in your field, this book demystifies the complexities of large language models (LLMs) with engaging, easy-to-understand explanations and practical insights. Explore the fascinating journey of AI from its early roots to the cutting-edge advancements that power today's conversational AI systems. Discover how LLMs, like ChatGPT and Google's Gemini, are transforming industries, enhancing productivity, and sparking creativity across the globe. With the guidance of this comprehensive and accessible guide, you'll gain a solid understanding of how LLMs work, their real-world applications, and the ethical considerations they entail. Packed with vivid examples, hands-on exercises, and real-life scenarios, this book will empower you to harness the full potential of LLMs. Learn to generate creative content, translate languages in real-time, summarise complex information, and even develop AI-powered applications—all without needing a technical background. You'll also find valuable insights into the evolving job landscape, equipping you with the knowledge to pursue a successful career in this dynamic field. This guide ensures that AI is not just an abstract concept but a tangible tool you can use to transform your everyday life and work. Dive into the future with confidence and curiosity, and discover the incredible possibilities that large language models offer. Join the AI revolution and unlock the secrets of the technology that's reshaping our world. "A Beginner's Guide to Large Language Models" is your key to understanding and mastering the power of conversational AI. Introduction This introduction sets the stage for understanding the evolution of artificial intelligence (AI) and large language models (LLMs). It highlights the promise of making complex AI concepts accessible to non-technical readers and outlines the unique approach of this book. Chapter 1: Demystifying AI and LLMs: A Journey Through Time This chapter introduces the basics of AI, using simple analogies and real-world examples. It traces the evolution of AI, from rule-based systems to machine learning and deep learning, leading to the emergence of LLMs. Key concepts such as tokens, vocabulary, and embeddings are explained to build a solid foundation for understanding how LLMs process and generate language. Chapter 2: Mastering Large Language Models Delving deeper into the mechanics of LLMs, this chapter covers the transformer architecture, attention mechanisms, and the processes involved in training and fine-tuning LLMs. It includes hands-on exercises with prompts and discusses advanced techniques like chain-of-thought prompting and prompt chaining to optimise LLM performance. Chapter 3: The LLM Toolbox: Unleashing the Power of Language AI This chapter explores the diverse applications of LLMs in text generation, language translation, summarisation, question answering, and code generation. It also introduces multimodal LLMs that handle both text and images, showcasing their impact on various creative and professional fields. Practical examples and real-life scenarios illustrate how these tools can enhance productivity and creativity. Chapter 4: LLMs in the Real World: Transforming Industries Highlighting the transformative impact of LLMs across different industries, this chapter covers their role in healthcare, finance, education, creative industries, and business. It discusses how LLMs are revolutionising tasks such as medical diagnosis, fraud detection, personalised tutoring, and content creation, and explores the future of work in an AI-powered world. Chapter 5: The Dark Side of LLMs: Ethical Concerns and Challenges Addressing the ethical challenges of LLMs, this chapter covers bias and fairness, privacy concerns, misuse of LLMs, security threats, and the transparency of AI decision-making. It also discusses ethical frameworks for responsible AI development and presents diverse perspectives on the risks and benefits of LLMs. Chapter 6: Mastering LLMs: Advanced Techniques and Strategies This chapter focuses on advanced techniques for leveraging LLMs, such as combining transformers with other AI models, fine-tuning open-source LLMs for specific tasks, and building LLM-powered applications. It provides detailed guidance on prompt engineering for various applications and includes a step-by-step guide to creating an AI-powered chatbot. Chapter 7: LLMs and the Future: A Glimpse into Tomorrow Looking ahead, this chapter explores emerging trends and potential breakthroughs in AI and LLM research. It discusses ethical AI development, insights from leading AI experts, and visions of a future where LLMs are integrated into everyday life. The chapter highlights the importance of building responsible AI systems that address societal concerns. Chapter 8: Your LLM Career Roadmap: Navigating the AI Job Landscape Focusing on the growing demand for LLM expertise, this chapter outlines various career paths in the AI field, such as LLM scientists, engineers, and prompt engineers. It provides resources for building the necessary skillsets and discusses the evolving job market, emphasising the importance of continuous learning and adaptability in a rapidly changing industry. Thought-Provoking Questions, Simple Exercises, and Real-Life Scenarios The book concludes with practical exercises and real-life scenarios to help readers apply their knowledge of LLMs. It includes thought-provoking questions to deepen understanding and provides resources and tools for further exploration of LLM applications. Tools to Help with Your Exercises This section lists tools and platforms for engaging with LLM exercises, such as OpenAI's Playground, Google Translate, and various IDEs for coding. Links to these tools are provided to facilitate hands-on learning and experimentation.

Breaking the Language Barrier: Demystifying Language Models with OpenAI

Author : Rayan Wali
Publisher : Rayan Wali
ISBN 13 :
Total Pages : 301 pages
Book Rating : 4.3/5 (855 download)

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Book Synopsis Breaking the Language Barrier: Demystifying Language Models with OpenAI by : Rayan Wali

Download or read book Breaking the Language Barrier: Demystifying Language Models with OpenAI written by Rayan Wali and published by Rayan Wali. This book was released on 2023-03-08 with total page 301 pages. Available in PDF, EPUB and Kindle. Book excerpt: Breaking the Language Barrier: Demystifying Language Models with OpenAI is an informative guide that covers practical NLP use cases, from machine translation to vector search, in a clear and accessible manner. In addition to providing insights into the latest technology that powers ChatGPT and other OpenAI language models, including GPT-3 and DALL-E, this book also showcases how to use OpenAI on the cloud, specifically on Microsoft Azure, to create scalable and efficient solutions.

Next Generation AI Language Models in Research

Author : Gwanggil Jeon
Publisher :
ISBN 13 : 9781032667935
Total Pages : 0 pages
Book Rating : 4.6/5 (679 download)

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Book Synopsis Next Generation AI Language Models in Research by : Gwanggil Jeon

Download or read book Next Generation AI Language Models in Research written by Gwanggil Jeon and published by . This book was released on 2024-11-13 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this comprehensive and cutting-edge volume, Jeon and Qureshi bring together experts from around the world to explore the potential of artificial intelligence models in research and discuss the potential benefits and the concerns and challenges that the rapid development of this field has raised. The international chapter contributor group provides a wealth of technical information on different aspects of AI, including key aspects of AI, deep learning and machine learning models for AI, natural language processing and computer vision, reinforcement learning, ethics and responsibilities, security, practical implementation, and future directions. The contents are balanced in terms of theory, methodologies and technical aspects, and contributors provide case studies to clearly illustrate the concepts and technical discussions throughout. Readers will gain valuable insights into how AI can revolutionise their work in fields including data analytics and pattern identification, healthcare research, social science research, and more, and improve their technical skills, problem solving abilities, and evidence-based decision making. Additionally, they will be cognizant of the limitations and challenges, the ethical implications, and security concerns related to language models, which will enable them to make more informed choices regarding their implementation. This book is an invaluable resource for undergraduate and graduate students who want to understand AI models, recent trends in the area, and technical and ethical aspects of AI. Companies involved in AI development or implementing AI in various fields will also benefit from the book's discussions on both the technical and ethical aspects of this rapidly growing field.

Demystifying Large Language Models

Author : James Chen
Publisher : James Chen
ISBN 13 : 1738908461
Total Pages : 300 pages
Book Rating : 4.7/5 (389 download)

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Book Synopsis Demystifying Large Language Models by : James Chen

Download or read book Demystifying Large Language Models written by James Chen and published by James Chen. This book was released on 2024-04-25 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a comprehensive guide aiming to demystify the world of transformers -- the architecture that powers Large Language Models (LLMs) like GPT and BERT. From PyTorch basics and mathematical foundations to implementing a Transformer from scratch, you'll gain a deep understanding of the inner workings of these models. That's just the beginning. Get ready to dive into the realm of pre-training your own Transformer from scratch, unlocking the power of transfer learning to fine-tune LLMs for your specific use cases, exploring advanced techniques like PEFT (Prompting for Efficient Fine-Tuning) and LoRA (Low-Rank Adaptation) for fine-tuning, as well as RLHF (Reinforcement Learning with Human Feedback) for detoxifying LLMs to make them aligned with human values and ethical norms. Step into the deployment of LLMs, delivering these state-of-the-art language models into the real-world, whether integrating them into cloud platforms or optimizing them for edge devices, this section ensures you're equipped with the know-how to bring your AI solutions to life. Whether you're a seasoned AI practitioner, a data scientist, or a curious developer eager to advance your knowledge on the powerful LLMs, this book is your ultimate guide to mastering these cutting-edge models. By translating convoluted concepts into understandable explanations and offering a practical hands-on approach, this treasure trove of knowledge is invaluable to both aspiring beginners and seasoned professionals. Table of Contents 1. INTRODUCTION 1.1 What is AI, ML, DL, Generative AI and Large Language Model 1.2 Lifecycle of Large Language Models 1.3 Whom This Book Is For 1.4 How This Book Is Organized 1.5 Source Code and Resources 2. PYTORCH BASICS AND MATH FUNDAMENTALS 2.1 Tensor and Vector 2.2 Tensor and Matrix 2.3 Dot Product 2.4 Softmax 2.5 Cross Entropy 2.6 GPU Support 2.7 Linear Transformation 2.8 Embedding 2.9 Neural Network 2.10 Bigram and N-gram Models 2.11 Greedy, Random Sampling and Beam 2.12 Rank of Matrices 2.13 Singular Value Decomposition (SVD) 2.14 Conclusion 3. TRANSFORMER 3.1 Dataset and Tokenization 3.2 Embedding 3.3 Positional Encoding 3.4 Layer Normalization 3.5 Feed Forward 3.6 Scaled Dot-Product Attention 3.7 Mask 3.8 Multi-Head Attention 3.9 Encoder Layer and Encoder 3.10 Decoder Layer and Decoder 3.11 Transformer 3.12 Training 3.13 Inference 3.14 Conclusion 4. PRE-TRAINING 4.1 Machine Translation 4.2 Dataset and Tokenization 4.3 Load Data in Batch 4.4 Pre-Training nn.Transformer Model 4.5 Inference 4.6 Popular Large Language Models 4.7 Computational Resources 4.8 Prompt Engineering and In-context Learning (ICL) 4.9 Prompt Engineering on FLAN-T5 4.10 Pipelines 4.11 Conclusion 5. FINE-TUNING 5.1 Fine-Tuning 5.2 Parameter Efficient Fine-tuning (PEFT) 5.3 Low-Rank Adaptation (LoRA) 5.4 Adapter 5.5 Prompt Tuning 5.6 Evaluation 5.7 Reinforcement Learning 5.8 Reinforcement Learning Human Feedback (RLHF) 5.9 Implementation of RLHF 5.10 Conclusion 6. DEPLOYMENT OF LLMS 6.1 Challenges and Considerations 6.2 Pre-Deployment Optimization 6.3 Security and Privacy 6.4 Deployment Architectures 6.5 Scalability and Load Balancing 6.6 Compliance and Ethics Review 6.7 Model Versioning and Updates 6.8 LLM-Powered Applications 6.9 Vector Database 6.10 LangChain 6.11 Chatbot, Example of LLM-Powered Application 6.12 WebUI, Example of LLM-Power Application 6.13 Future Trends and Challenges 6.14 Conclusion REFERENCES ABOUT THE AUTHOR

Generative AI and LLMs

Author : S. Balasubramaniam
Publisher : Walter de Gruyter GmbH & Co KG
ISBN 13 : 3111425517
Total Pages : 366 pages
Book Rating : 4.1/5 (114 download)

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Book Synopsis Generative AI and LLMs by : S. Balasubramaniam

Download or read book Generative AI and LLMs written by S. Balasubramaniam and published by Walter de Gruyter GmbH & Co KG. This book was released on 2024-09-23 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Modern Generative AI with ChatGPT and OpenAI Models

Author : Valentina Alto
Publisher : Packt Publishing Ltd
ISBN 13 : 1805122835
Total Pages : 286 pages
Book Rating : 4.8/5 (51 download)

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Book Synopsis Modern Generative AI with ChatGPT and OpenAI Models by : Valentina Alto

Download or read book Modern Generative AI with ChatGPT and OpenAI Models written by Valentina Alto and published by Packt Publishing Ltd. This book was released on 2023-05-26 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: Harness the power of AI with innovative, real-world applications, and unprecedented productivity boosts, powered by the latest advancements in AI technology like ChatGPT and OpenAI Purchase of the print or Kindle book includes a free PDF eBook Key Features Explore the theory behind generative AI models and the road to GPT3 and GPT4 Become familiar with ChatGPT's applications to boost everyday productivity Learn to embed OpenAI models into applications using lightweight frameworks like LangChain Book Description Generative AI models and AI language models are becoming increasingly popular due to their unparalleled capabilities. This book will provide you with insights into the inner workings of the LLMs and guide you through creating your own language models. You'll start with an introduction to the field of generative AI, helping you understand how these models are trained to generate new data. Next, you'll explore use cases where ChatGPT can boost productivity and enhance creativity. You'll learn how to get the best from your ChatGPT interactions by improving your prompt design and leveraging zero, one, and few-shots learning capabilities. The use cases are divided into clusters of marketers, researchers, and developers, which will help you apply what you learn in this book to your own challenges faster. You'll also discover enterprise-level scenarios that leverage OpenAI models' APIs available on Azure infrastructure; both generative models like GPT-3 and embedding models like Ada. For each scenario, you'll find an end-to-end implementation with Python, using Streamlit as the frontend and the LangChain SDK to facilitate models' integration into your applications. By the end of this book, you'll be well equipped to use the generative AI field and start using ChatGPT and OpenAI models' APIs in your own projects. What you will learn Understand generative AI concepts from basic to intermediate level Focus on the GPT architecture for generative AI models Maximize ChatGPT's value with an effective prompt design Explore applications and use cases of ChatGPT Use OpenAI models and features via API calls Build and deploy generative AI systems with Python Leverage Azure infrastructure for enterprise-level use cases Ensure responsible AI and ethics in generative AI systems Who this book is for This book is for individuals interested in boosting their daily productivity; businesspersons looking to dive deeper into real-world applications to empower their organizations; data scientists and developers trying to identify ways to boost ML models and code; marketers and researchers seeking to leverage use cases in their domain – all by using Chat GPT and OpenAI Models. A basic understanding of Python is required; however, the book provides theoretical descriptions alongside sections with code so that the reader can learn the concrete use case application without running the scripts.

AI Language Models

Author : Jers Butler
Publisher : Independently Published
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.3/5 (887 download)

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Book Synopsis AI Language Models by : Jers Butler

Download or read book AI Language Models written by Jers Butler and published by Independently Published. This book was released on 2023-03-27 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: AI Language Models: Your New Secret Weapon is a comprehensive guide to understanding and utilizing AI language models to enhance communication and productivity. This book covers the basics of natural language processing, advanced techniques for improving language models, use cases for AI language models, and best practices for implementation. It also includes case studies of successful implementation and a step-by-step guide for building your own language model. The future of AI language models is also explored, with insights into the latest advancements and potential applications in various industries. Written in an engaging and accessible style, this book is perfect for anyone looking to stay ahead of the curve and leverage the power of AI language models in their business or personal projects. Whether you're a beginner or an experienced developer, AI Language Models: Your New Secret Weapon is an essential resource for anyone interested in the world of AI language models.

Linguistics for the Age of AI

Author : Marjorie Mcshane
Publisher : MIT Press
ISBN 13 : 0262362600
Total Pages : 449 pages
Book Rating : 4.2/5 (623 download)

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Book Synopsis Linguistics for the Age of AI by : Marjorie Mcshane

Download or read book Linguistics for the Age of AI written by Marjorie Mcshane and published by MIT Press. This book was released on 2021-03-02 with total page 449 pages. Available in PDF, EPUB and Kindle. Book excerpt: A human-inspired, linguistically sophisticated model of language understanding for intelligent agent systems. One of the original goals of artificial intelligence research was to endow intelligent agents with human-level natural language capabilities. Recent AI research, however, has focused on applying statistical and machine learning approaches to big data rather than attempting to model what people do and how they do it. In this book, Marjorie McShane and Sergei Nirenburg return to the original goal of recreating human-level intelligence in a machine. They present a human-inspired, linguistically sophisticated model of language understanding for intelligent agent systems that emphasizes meaning--the deep, context-sensitive meaning that a person derives from spoken or written language.

Large Language Models Projects

Author : Pere Martra Manonelles
Publisher : Apress
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.8/5 (688 download)

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Book Synopsis Large Language Models Projects by : Pere Martra Manonelles

Download or read book Large Language Models Projects written by Pere Martra Manonelles and published by Apress. This book was released on 2024-10-20 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers you a hands-on experience using models from OpenAI and the Hugging Face library. You will use various tools and work on small projects, gradually applying the new knowledge you gain. The book is divided into three parts. Part one covers techniques and libraries. Here, you'll explore different techniques through small examples, preparing to build projects in the next section. You'll learn to use common libraries in the world of Large Language Models. Topics and technologies covered include chatbots, code generation, OpenAI API, Hugging Face, vector databases, LangChain, fine tuning, PEFT fine tuning, soft prompt tuning, LoRA, QLoRA, evaluating models, and Direct Preference Optimization. Part two focuses on projects. You'll create projects, understanding design decisions. Each project may have more than one possible implementation, as there is often not just one good solution. You'll also explore LLMOps-related topics. Part three delves into enterprise solutions. Large Language Models are not a standalone solution; in large corporate environments, they are one piece of the puzzle. You'll explore how to structure solutions capable of transforming organizations with thousands of employees, highlighting the main role that Large Language Models play in these new solutions. This book equips you to confidently navigate and implement Large Language Models, empowering you to tackle diverse challenges in the evolving landscape of language processing. What You Will Learn Gain practical experience by working with models from OpenAI and the Hugging Face library Use essential libraries relevant to Large Language Models, covering topics such as Chatbots, Code Generation, OpenAI API, Hugging Face, and Vector databases Create and implement projects using LLM while understanding the design decisions involved Understand the role of Large Language Models in larger corporate settings Who This Book Is For Data analysts, data science, Python developers, and software professionals interested in learning the foundations of NLP, LLMs, and the processes of building modern LLM applications for various tasks

Generative AI with Large Language Models: A Comprehensive Guide

Author : Anand Vemula
Publisher : Anand Vemula
ISBN 13 :
Total Pages : 43 pages
Book Rating : 4./5 ( download)

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Book Synopsis Generative AI with Large Language Models: A Comprehensive Guide by : Anand Vemula

Download or read book Generative AI with Large Language Models: A Comprehensive Guide written by Anand Vemula and published by Anand Vemula. This book was released on with total page 43 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book delves into the fascinating world of Generative AI, exploring the two key technologies driving its advancements: Large Language Models (LLMs) and Foundation Models (FMs). Part 1: Foundations LLMs Demystified: We begin by understanding LLMs, powerful AI models trained on massive amounts of text data. These models can generate human-quality text, translate languages, write different creative formats, and even answer your questions in an informative way. The Rise of FMs: However, LLMs are just a piece of the puzzle. We explore Foundation Models, a broader category encompassing models trained on various data types like images, audio, and even scientific data. These models represent a significant leap forward in AI, offering a more versatile approach to information processing. Part 2: LLMs and Generative AI Applications Training LLMs: We delve into the intricate process of training LLMs, from data acquisition and pre-processing to different training techniques like supervised and unsupervised learning. The chapter also explores challenges like computational resources and data bias, along with best practices for responsible LLM training. Fine-Tuning for Specific Tasks: LLMs can be further specialized for targeted tasks through fine-tuning. We explore how fine-tuning allows LLMs to excel in areas like creative writing, code generation, drug discovery, and even music composition. Part 3: Advanced Topics LLM Architectures: We take a deep dive into the technical aspects of LLMs, exploring the workings of Transformer networks, the backbone of modern LLMs. We also examine the role of attention mechanisms in LLM processing and learn about different prominent LLM architectures like GPT-3 and Jurassic-1 Jumbo. Scaling Generative AI: Scaling up LLMs presents significant computational challenges. The chapter explores techniques like model parallelism and distributed training to address these hurdles, along with hardware considerations like GPUs and TPUs that facilitate efficient LLM training. Most importantly, we discuss the crucial role of safety and ethics in generative AI development. Mitigating bias, addressing potential risks like deepfakes, and ensuring transparency are all essential for responsible AI development. Part 4: The Future Evolving Generative AI Landscape: We explore emerging trends in LLM research, like the development of even larger and more capable models, along with advancements in explainable AI and the rise of multimodal LLMs that can handle different data types. We also discuss the potential applications of generative AI in unforeseen areas like personalized education and healthcare. Societal Impact and the Future of Work: The book concludes by examining the societal and economic implications of generative AI. We explore the potential transformation of industries, the need for workforce reskilling, and the importance of human-AI collaboration. Additionally, the book emphasizes the need for robust regulations to address concerns like bias, data privacy, and transparency in generative AI development. This book equips you with a comprehensive understanding of generative AI, its core technologies, its applications, and the considerations for its responsible development and deployment.

Aum Golly: Poems on Humanity by an Artificial Intelligence

Author : Gpt- Ai
Publisher : Kertojan Aani
ISBN 13 : 9789527397237
Total Pages : 74 pages
Book Rating : 4.3/5 (972 download)

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Book Synopsis Aum Golly: Poems on Humanity by an Artificial Intelligence by : Gpt- Ai

Download or read book Aum Golly: Poems on Humanity by an Artificial Intelligence written by Gpt- Ai and published by Kertojan Aani. This book was released on 2021-10-09 with total page 74 pages. Available in PDF, EPUB and Kindle. Book excerpt: What does AI know about love, happiness and making a difference? Aum Golly is a book of poems written in 24 hours. It was made possible by GPT-3 - an advanced autoregressive language model published in 2020 by OpenAI. "... a collection that surprises with humor and delicateness..." - Goodreads review "... I have to say reading it was a pleasure..." - Finnish radio host Ruben Stiller on Yle "... a beautiful dialogue between man and machine..." - a review of the Finnish audiobook The deep learning model can generate text that is virtually indistinguishable from text written by humans: poems, recipes, summaries, legal text and even pieces of code. GPT-3 is autofill on steroids. Good poetry makes us feel something and see the world differently. Despite the gut reaction some of us may have towards AI-enhanced creativity, Aum Golly is a book like any other. You will love some of the poems. You will hate others. Some will make you wonder, but all of them will make you think. Award-winning writer and TEDx speaker Jukka Aalho has guided the AI and chosen the poems for the collection.

ChatGPT and Gemini Chat 101: A Beginner's Guide to Language Models

Author : M.B. Chatfield
Publisher : M.B. Chatfield
ISBN 13 :
Total Pages : 163 pages
Book Rating : 4./5 ( download)

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Book Synopsis ChatGPT and Gemini Chat 101: A Beginner's Guide to Language Models by : M.B. Chatfield

Download or read book ChatGPT and Gemini Chat 101: A Beginner's Guide to Language Models written by M.B. Chatfield and published by M.B. Chatfield. This book was released on with total page 163 pages. Available in PDF, EPUB and Kindle. Book excerpt: Embark on a journey to explore the fascinating world of language models, with ChatGPT and Gemini Chat as your guides. In this beginner-friendly guide, you will discover the basics of language models, including their history, development, and applications. You will also learn how to use ChatGPT and Gemini Chat, two powerful language models created by OpenAI and Google AI, respectively. Throughout the guide, you will: Gain a comprehensive understanding of language models and their role in artificial intelligence (AI). Explore the capabilities of ChatGPT and Gemini Chat, including their ability to generate human-quality text, translate languages, write different kinds of creative content, and answer your questions in an informative way. This book is perfect for anyone who wants to learn the basics of language models and how to use them. So what are you waiting for? Start your adventure into the world of language models today! With ChatGPT and Gemini Chat as your guides, you're sure to have an enriching and enlightening experience. Join us as we explore the endless possibilities of language models and their impact on the future.

Artificial Intelligence and Large Language Models

Author : Kutub Thakur
Publisher : CRC Press
ISBN 13 : 1040052177
Total Pages : 294 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Artificial Intelligence and Large Language Models by : Kutub Thakur

Download or read book Artificial Intelligence and Large Language Models written by Kutub Thakur and published by CRC Press. This book was released on 2024-07-12 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: Having been catapulted into public discourse in the last few years, this book serves as an in-depth exploration of the ever-evolving domain of artificial intelligence (AI), large language models, and ChatGPT. It provides a meticulous and thorough analysis of AI, ChatGPT technology, and their prospective trajectories given the current trend, in addition to tracing the significant advancements that have materialized over time. Key Features: Discusses the fundamentals of AI for general readers Introduces readers to the ChatGPT chatbot and how it works Covers natural language processing (NLP), the foundational building block of ChatGPT Introduces readers to the deep learning transformer architecture Covers the fundamentals of ChatGPT training for practitioners Illustrated and organized in an accessible manner, this textbook contains particular appeal to students and course convenors at the undergraduate and graduate level, as well as a reference source for general readers.

Artificial Intelligence in Medicine

Author : David Riaño
Publisher : Springer
ISBN 13 : 303021642X
Total Pages : 431 pages
Book Rating : 4.0/5 (32 download)

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Book Synopsis Artificial Intelligence in Medicine by : David Riaño

Download or read book Artificial Intelligence in Medicine written by David Riaño and published by Springer. This book was released on 2019-06-19 with total page 431 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 17th Conference on Artificial Intelligence in Medicine, AIME 2019, held in Poznan, Poland, in June 2019. The 22 revised full and 31 short papers presented were carefully reviewed and selected from 134 submissions. The papers are organized in the following topical sections: deep learning; simulation; knowledge representation; probabilistic models; behavior monitoring; clustering, natural language processing, and decision support; feature selection; image processing; general machine learning; and unsupervised learning.

Demystifying Large Language Models: A Comprehensive Guide

Author : Anand Vemula
Publisher : Anand Vemula
ISBN 13 :
Total Pages : 41 pages
Book Rating : 4./5 ( download)

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Book Synopsis Demystifying Large Language Models: A Comprehensive Guide by : Anand Vemula

Download or read book Demystifying Large Language Models: A Comprehensive Guide written by Anand Vemula and published by Anand Vemula. This book was released on with total page 41 pages. Available in PDF, EPUB and Kindle. Book excerpt: Demystifying Large Language Models: A Comprehensive Guide" serves as an essential roadmap for navigating the complex terrain of cutting-edge language technologies. In this book, readers are taken on a journey into the heart of Large Language Models (LLMs), exploring their significance, mechanics, and real-world applications. The narrative begins by contextualizing LLMs within the broader landscape of artificial intelligence and natural language processing, offering a clear understanding of their evolution and the pivotal role they play in modern computational linguistics. Delving into the workings of LLMs, the book breaks down intricate concepts into digestible insights, ensuring accessibility for both technical and non-technical audiences. Readers are introduced to the underlying architectures and training methodologies that power LLMs, including Transformer models like GPT (Generative Pre-trained Transformer) series. Through illustrative examples and practical explanations, complex technical details are demystified, empowering readers to grasp the essence of how these models generate human-like text and responses. Beyond theoretical underpinnings, the book explores diverse applications of LLMs across industries and disciplines. From natural language understanding and generation to sentiment analysis and machine translation, readers gain valuable insights into how LLMs are revolutionizing tasks once deemed exclusive to human intelligence. Moreover, the book addresses critical considerations surrounding ethics, bias, and responsible deployment of LLMs in real-world scenarios. It prompts readers to reflect on the societal implications of these technologies and encourages a thoughtful approach towards their development and utilization. With its comprehensive coverage and accessible language, "Demystifying Large Language Models" equips readers with the knowledge and understanding needed to engage with LLMs confidently. Whether you're a researcher, industry professional, or curious enthusiast, this book offers invaluable insights into the present and future of language technology.