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Author: Anand Vemula
Publisher: Anand Vemula
ISBN:
Category : Computers
Languages : en
Pages : 72
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Book Description
This book equips you with the skills to harness the power of Generative AI, specifically Large Language Models (LLMs), to create various text formats. Get ready to experiment, explore, and unleash your creative potential! Part 1: Unveiling the Power of Generative AI and LLMs We'll begin by demystifying Generative AI and understanding how it transforms text creation. You'll then delve into the capabilities of LLMs, the powerhouse behind this technology. Through interactive exercises, you'll gain firsthand experience with pre-trained LLMs, exploring their strengths and limitations. Part 2: Mastering Text Generation Techniques Now that you're familiar with the tools, let's explore specific techniques for generating different text formats: Text Inpainting: Imagine restoring missing sections of historical documents or poems. We'll use LLMs to fill the gaps and reconstruct the text, putting your detective skills to the test with hands-on exercises. Text Summarization: Information overload is real! Learn how to leverage LLMs to create concise summaries of lengthy texts, like research papers or news articles. You'll practice generating summaries for presentations or reports through engaging exercises. Part 3: Unleashing Your Inner AI Artist Get ready to tap into your creative side! We'll explore how LLMs can assist you in crafting various artistic text formats: Storytelling: Spark your imagination with a starting line and see where the story unfolds! Prompt the LLM and collaborate on creating engaging narratives. Exercises will guide you in co-writing stories with an LLM, taking turns adding sentences. Poetry: Let the AI muse inspire you! We'll experiment with generating poems in different styles, from classic sonnets to modern haikus. Challenge yourself with themed haiku writing exercises using LLMs. Code Generation: Stuck on a coding problem? Discover how LLMs can become your coding assistant! We'll explore using LLMs for code completion and bug detection, putting their capabilities to the test with practical exercises. Part 4: Refining Your Craft - Advanced Techniques Ready to take your skills a step further? We'll delve into advanced techniques for generating more refined and controlled text outputs: Conditional Text Generation: Imagine guiding the LLM to create text that adheres to specific requirements. We'll experiment with specifying genre, style, or even keywords to influence the narrative in your exercises. Sampling Techniques: Discover how to generate diverse outputs from a single prompt! Explore different sampling techniques with LLMs and see how they impact the creativity and unexpectedness of the generated text. You'll compare and analyze outputs generated with different sampling methods. Style and Tone Control: Want your text to sound formal, funny, or even sarcastic? You'll learn how to control the stylistic elements of the generated text, tailoring it to your specific needs. Exercises will guide you in generating product descriptions with different writing styles. By the end of this workshop, you'll be a confident generative AI text creator, equipped with the skills to experiment with LLMs and produce creative, informative, and engaging text formats tailored to your needs
Author: Anand Vemula
Publisher: Anand Vemula
ISBN:
Category : Computers
Languages : en
Pages : 72
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Book Description
This book equips you with the skills to harness the power of Generative AI, specifically Large Language Models (LLMs), to create various text formats. Get ready to experiment, explore, and unleash your creative potential! Part 1: Unveiling the Power of Generative AI and LLMs We'll begin by demystifying Generative AI and understanding how it transforms text creation. You'll then delve into the capabilities of LLMs, the powerhouse behind this technology. Through interactive exercises, you'll gain firsthand experience with pre-trained LLMs, exploring their strengths and limitations. Part 2: Mastering Text Generation Techniques Now that you're familiar with the tools, let's explore specific techniques for generating different text formats: Text Inpainting: Imagine restoring missing sections of historical documents or poems. We'll use LLMs to fill the gaps and reconstruct the text, putting your detective skills to the test with hands-on exercises. Text Summarization: Information overload is real! Learn how to leverage LLMs to create concise summaries of lengthy texts, like research papers or news articles. You'll practice generating summaries for presentations or reports through engaging exercises. Part 3: Unleashing Your Inner AI Artist Get ready to tap into your creative side! We'll explore how LLMs can assist you in crafting various artistic text formats: Storytelling: Spark your imagination with a starting line and see where the story unfolds! Prompt the LLM and collaborate on creating engaging narratives. Exercises will guide you in co-writing stories with an LLM, taking turns adding sentences. Poetry: Let the AI muse inspire you! We'll experiment with generating poems in different styles, from classic sonnets to modern haikus. Challenge yourself with themed haiku writing exercises using LLMs. Code Generation: Stuck on a coding problem? Discover how LLMs can become your coding assistant! We'll explore using LLMs for code completion and bug detection, putting their capabilities to the test with practical exercises. Part 4: Refining Your Craft - Advanced Techniques Ready to take your skills a step further? We'll delve into advanced techniques for generating more refined and controlled text outputs: Conditional Text Generation: Imagine guiding the LLM to create text that adheres to specific requirements. We'll experiment with specifying genre, style, or even keywords to influence the narrative in your exercises. Sampling Techniques: Discover how to generate diverse outputs from a single prompt! Explore different sampling techniques with LLMs and see how they impact the creativity and unexpectedness of the generated text. You'll compare and analyze outputs generated with different sampling methods. Style and Tone Control: Want your text to sound formal, funny, or even sarcastic? You'll learn how to control the stylistic elements of the generated text, tailoring it to your specific needs. Exercises will guide you in generating product descriptions with different writing styles. By the end of this workshop, you'll be a confident generative AI text creator, equipped with the skills to experiment with LLMs and produce creative, informative, and engaging text formats tailored to your needs
Author: Etienne Noumen
Publisher: Etienne Noumen
ISBN:
Category : Computers
Languages : en
Pages : 147
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Book Description
Dive into the revolutionary world of Artificial Intelligence with 'AI Unraveled: Demystifying Frequently Asked Questions on Artificial Intelligence'. This comprehensive guide is your portal to understanding AI's most intricate concepts and cutting-edge developments. Whether you're a curious beginner or an AI enthusiast, this book is tailored to unveil the complexities of AI in a simple, accessible manner. What's Inside: Fundamental AI Concepts: Journey through the basics of AI, machine learning, deep learning, and neural networks. AI in Action: Explore how AI is reshaping industries and society, diving into its applications in computer vision, natural language processing, and beyond. Ethical AI: Tackle critical issues like AI ethics and bias, understanding the moral implications of AI advancements. Industry Insights: Gain insights into how AI is revolutionizing industries and impacting our daily lives. The Future of AI: Forecast the exciting possibilities and challenges that lie ahead in the AI landscape. Special Focus on Generative AI & LLMs: Latest AI Trends: Stay updated with the latest in AI, including ChatGPT, Google Bard, GPT-4, Gemini, and more. Interactive Quizzes: Test your knowledge with engaging quizzes on Generative AI and Large Language Models (LLMs). Practical Guides: Master GPT-4 with a simplified guide, delve into advanced prompt engineering, and explore the nuances of temperature settings in AI. Real-World Applications: Learn how to leverage AI in various sectors, from healthcare to cybersecurity, and even explore its potential in areas like aging research and brain implants. For the AI Enthusiast: Prompt Engineering: Uncover secrets to crafting effective prompts for ChatGPT/Google Bard. AI Career Insights: Explore lucrative career paths in AI, including roles like AI Prompt Engineers. AI Investment Guide: Navigate the world of AI stocks and investment opportunities. Your Guide to Navigating AI: Do-It-Yourself Tutorials: From building custom ChatGPT applications to running LLMs locally, this book offers step-by-step guides. AI for Everyday Use: Learn how AI can assist in weight loss, social media, and more. 'AI Unraveled' is more than just a book; it's a resource for anyone looking to grasp the complexities of AI and its impact on our world. Get ready to embark on an enlightening journey into the realm of Artificial Intelligence!" More Topics Covered: Artificial Intelligence, Machine Learning, Deep Learning, NLP, AI Ethics, Robotics, Cognitive Computing, ChatGPT, OpenAI, Google Bard, Generative AI, LLMs, AI in Healthcare, AI Investments, and much more. GPT-4 vs Gemini: Pros and Cons Mastering GPT-4: Simplified Guide For everyday Users Advance Prompt Engineering Techniques: [Single Prompt Technique, Zero-Shot and Few-Shot, Zero-Shot and Few-Shot, Generated Knowledge Prompting, EmotionPrompt, Chain of Density (CoD), Chain of Thought (CoT), Validation of LLMs Responses, Chain of Verification (CoVe), Agents - The Frontier of Prompt Engineering, Prompt Chaining vs Agents, Tree of Thought (ToT), ReAct (Reasoning + Act), ReWOO (Reasoning WithOut Observation), Reflexion and Self-Reflection, Guardrails, RAIL (Reliable AI Markup Language), Guardrails AI, NeMo Guardrails] Understanding Temperature in GPT-4: A Guide to AI Probability and Creativity Retrieval-Augmented Generation (RAG) model in the context of Large Language Models (LLMs) like GPT-4 Prompt Ideas for ChatGPT/Google Bard How to Run ChatGPT-like LLMs Locally on Your Computer in 3 Easy Steps ChatGPT Custom Instructions Settings for Power Users Examples of bad and good ChatGPT prompts Top 5 Beginner Mistakes in Prompt Engineering Use ChatGPT like a PRO Prompt template for learning any skill Prompt Engineering for ChatGPT The Future of LLMs in Search What is Explainable AI? Which industries are meant for XAI? ChatGPT Best Tips, Cheat Sheet LLMs Utilize Vector DB for Data Storage The Limitation Technique in Prompt Responses Use ChatGPT to learn new subjects Prompts to proofread anything Topics: Artificial Intelligence Education Machine Learning Deep Learning Reinforcement Learning Neural networks Data science AI ethics Deepmind Robotics Natural language processing Intelligent agents Cognitive computing AI Apps AI impact AI Tech ChatGPT Open AI Safe AI Generative AI Discriminative AI Sam Altman Google Bard NVDIA Large Language Models (LLMs) PALM GPT Explainable AI GPUs AI Stocks AI Podcast Q* AI Certification AI Quiz RAG How to access the AI Unraveled print and audiobook: Amazon print book: https://amzn.to/3xvCfWR Audible at Amazon : https://www.audible.com/pd/B0BXMJ7FK5/?source_code=AUDFPWS0223189MWT-BK-ACX0-343437&ref=acx_bty_BK_ACX0_343437_rh_us (Use Promo code: 37YT3B5UYUYZW) Audiobook at Google: https://play.google.com/store/audiobooks/details?id=AQAAAEAihFTEZM Amazon eBook: https://amzn.to/3KbshkO Google eBook: https://play.google.com/store/books/details?id=oySuEAAAQBAJ Apple eBook: http://books.apple.com/us/book/id6445730691
Author: Kerrie Holley
Publisher: "O'Reilly Media, Inc."
ISBN: 1098160886
Category : Computers
Languages : en
Pages : 218
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Book Description
Large language models (LLMs) and generative AI are rapidly changing the healthcare industry. These technologies have the potential to revolutionize healthcare by improving the efficiency, accuracy, and personalization of care. This practical book shows healthcare leaders, researchers, data scientists, and AI engineers the potential of LLMs and generative AI today and in the future, using storytelling and illustrative use cases in healthcare. Authors Kerrie Holley, former Google healthcare professionals, guide you through the transformative potential of large language models (LLMs) and generative AI in healthcare. From personalized patient care and clinical decision support to drug discovery and public health applications, this comprehensive exploration covers real-world uses and future possibilities of LLMs and generative AI in healthcare. With this book, you will: Understand the promise and challenges of LLMs in healthcare Learn the inner workings of LLMs and generative AI Explore automation of healthcare use cases for improved operations and patient care using LLMs Dive into patient experiences and clinical decision-making using generative AI Review future applications in pharmaceutical R&D, public health, and genomics Understand ethical considerations and responsible development of LLMs in healthcare "The authors illustrate generative's impact on drug development, presenting real-world examples of its ability to accelerate processes and improve outcomes across the pharmaceutical industry."--Harsh Pandey, VP, Data Analytics & Business Insights, Medidata-Dassault Kerrie Holley is a retired Google tech executive, IBM Fellow, and VP/CTO at Cisco. Holley's extensive experience includes serving as the first Technology Fellow at United Health Group (UHG), Optum, where he focused on advancing and applying AI, deep learning, and natural language processing in healthcare. Manish Mathur brings over two decades of expertise at the crossroads of healthcare and technology. A former executive at Google and Johnson & Johnson, he now serves as an independent consultant and advisor. He guides payers, providers, and life sciences companies in crafting cutting-edge healthcare solutions.
Author: S. Balasubramaniam
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 311142507X
Category : Computers
Languages : en
Pages : 290
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Book Description
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.
Author: Adrián González Sánchez
Publisher: "O'Reilly Media, Inc."
ISBN: 1098154959
Category : Computers
Languages : en
Pages : 275
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Book Description
Get the details, examples, and best practices you need to build generative AI applications, services, and solutions using the power of Azure OpenAI Service. With this comprehensive guide, Microsoft AI specialist Adrián González Sánchez examines the integration and utilization of Azure OpenAI Service—using powerful generative AI models such as GPT-4 and GPT-4o—within the Microsoft Azure cloud computing platform. To guide you through the technical details of using Azure OpenAI Service, this book shows you how to set up the necessary Azure resources, prepare end-to-end architectures, work with APIs, manage costs and usage, handle data privacy and security, and optimize performance. You'll learn various use cases where Azure OpenAI Service models can be applied, and get valuable insights from some of the most relevant AI and cloud experts. Ideal for software and cloud developers, product managers, architects, and engineers, as well as cloud-enabled data scientists, this book will help you: Learn how to implement cloud native applications with Azure OpenAI Service Deploy, customize, and integrate Azure OpenAI Service with your applications Customize large language models and orchestrate knowledge with company-owned data Use advanced roadmaps to plan your generative AI project Estimate cost and plan generative AI implementations for adopter companies
Author: Mohamed Lahby
Publisher: Springer Nature
ISBN: 3031656911
Category :
Languages : en
Pages : 440
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Book Description
Author: Amparo Alonso-Betanzos
Publisher: Springer Nature
ISBN: 3031627997
Category :
Languages : en
Pages : 293
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Book Description
Author: Francesco Esposito
Publisher: Microsoft Press
ISBN: 0138280452
Category : Computers
Languages : en
Pages : 605
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Book Description
Use LLMs to build better business software applications Autonomously communicate with users and optimize business tasks with applications built to make the interaction between humans and computers smooth and natural. Artificial Intelligence expert Francesco Esposito illustrates several scenarios for which a LLM is effective: crafting sophisticated business solutions, shortening the gap between humans and software-equipped machines, and building powerful reasoning engines. Insight into prompting and conversational programming—with specific techniques for patterns and frameworks—unlock how natural language can also lead to a new, advanced approach to coding. Concrete end-to-end demonstrations (featuring Python and ASP.NET Core) showcase versatile patterns of interaction between existing processes, APIs, data, and human input. Artificial Intelligence expert Francesco Esposito helps you: Understand the history of large language models and conversational programming Apply prompting as a new way of coding Learn core prompting techniques and fundamental use-cases Engineer advanced prompts, including connecting LLMs to data and function calling to build reasoning engines Use natural language in code to define workflows and orchestrate existing APIs Master external LLM frameworks Evaluate responsible AI security, privacy, and accuracy concerns Explore the AI regulatory landscape Build and implement a personal assistant Apply a retrieval augmented generation (RAG) pattern to formulate responses based on a knowledge base Construct a conversational user interface For IT Professionals and Consultants For software professionals, architects, lead developers, programmers, and Machine Learning enthusiasts For anyone else interested in natural language processing or real-world applications of human-like language in software
Author: Hunaidkhan Pathan
Publisher: BPB Publications
ISBN: 9365891043
Category : Computers
Languages : en
Pages : 306
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Book Description
DESCRIPTION The book is all about the basics of NLP, generative AI, and their specific component LLM. In this book, we have provided conceptual knowledge about different terminologies and concepts of NLP and NLG with practical hands-on. This comprehensive book offers a deep dive into the world of NLP and LLMs. Starting with the fundamentals of Python programming and code editors, the book gradually introduces NLP concepts, including text preprocessing, word embeddings, and transformer architectures. You will explore the architecture and capabilities of popular models like GPT-3 and BERT. The book also covers practical aspects of LLM usage for RAG applications using frameworks like LangChain and Hugging Face and deploying them in real world applications. With a focus on both theoretical knowledge and hands-on experience, this book is ideal for anyone looking to master the art of NLP and LLMs. The book also contains AWS Cloud deployment, which will help readers step into the world of cloud computing. As the book contains both theoretical and practical approaches, it will help the readers to gain confidence in the deployment of LLMs for any use cases, as well as get acquainted with the required generative AI knowledge to crack the interviews. KEY FEATURES ● Covers Python basics, NLP concepts, and terminologies, including LLM and RAG concepts. ● Provides exposure to LangChain, Hugging Face ecosystem, and chatbot creation using custom data. ● Guides on integrating chatbots with real-time applications and deploying them on AWS Cloud. WHAT YOU WILL LEARN ● Basics of Python, which contains Python concepts, installation, and code editors. ● Foundation of NLP and generative AI concepts and different terminologies being used in NLP and generative AI domain. ● LLMs and their importance in the cutting edge of AI. ● Creating chatbots using custom data using open source LLMs without spending a single penny. ● Integration of chatbots with real-world applications like Telegram. WHO THIS BOOK IS FOR This book is ideal for beginners and freshers entering the AI or ML field, as well as those at an intermediate level looking to deepen their understanding of generative AI, LLMs, and cloud deployment. TABLE OF CONTENTS 1. Introduction to Python and Code Editors 2. Installation of Python, Required Packages, and Code Editors 3. Ways to Run Python Scripts 4. Introduction to NLP and its Concepts 5. Introduction to Large Language Models 6. Introduction of LangChain, Usage and Importance 7. Introduction of Hugging Face, its Usage and Importance 8. Creating Chatbots Using Custom Data with LangChain and Hugging Face Hub 9. Hyperparameter Tuning and Fine Tuning Pre-Trained Models 10. Integrating LLMs into Real-World Applications–Case Studies 11. Deploying LLMs in Cloud Environments for Scalability 12. Future Directions: Advances in LLMs and Beyond Appendix A: Useful Tips for Efficient LLM Experimentation Appendix B: Resources and References
Author: Vishal Anand
Publisher: BPB Publications
ISBN: 9355516975
Category : Computers
Languages : en
Pages : 249
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Book Description
DESCRIPTION Generative AI can streamline technical and business processes, increase efficiency, and free up your resources’ time to focus on more strategic initiatives. This book takes the readers through a series of steps to deepen their understanding of the forces that shape an organization’s implementation of Generative AI at scale and successfully dealing with them. This book starts with GenAI potential uses, challenges and enterprise deployment strategies. You will learn to scale GenAI models along with LLMOps, choose the right LLM, and use prompt engineering and fine-tuning to customize the outputs. This book introduces a GenAI operating system as well as an orchestration platform for workflow automation. It discusses ethical considerations, designing a target operating model, cost optimization, Retrieval-augmented Generation (RAG), Model as a Service (MaaS), and Confidential AI. Finally, it explores the future of multi-modal AI assistants in enterprises. This book makes it easier for readers to debunk myths, and address fallacies and common misconceptions that could harm organizational investment and reputation. There are also practical and enterprise class scenarios and information that could help in improving implementations, within your organization, enabling you to achieve success beyond scaling challenges. KEY FEATURES ● Understand challenges and dimensions of model at scale. ● Understand model selection criteria, deployment patterns, and positioning. ● Design operating system and demarcation of landing zones. ● Understand enterprise application of prompt engineering and fine-tuning. ● Understand operating model, orchestration platform, multi AI assistants and ethical considerations. ● Understand various latency factors for Gen AI solutions. WHAT YOU WILL LEARN ● Strategies for scaling GenAI models and discovering LLMOps for managing them. ● How to leverage GenAI to streamline enterprise class processes, boost efficiency, and explore new possibilities. ● Implementations in the enterprise class deployments, addressing potential issues and connecting with enablers and accurate growth strategy and execution principles. WHO THIS BOOK IS FOR This book is for decision makers like CIOs, CTOs, CAIOs, Enterprise Architects, Chief Engineers, and anyone who wishes to learn how to have a rewarding implementation of Generative AI for their organizations and clients. TABLE OF CONTENTS 1. The Rise of Generative AI in Enterprises 2. Complex Needs of Production 3. Model Selection for Enterprises 4. Model Deployment for Enterprises 5. Operating System for Enterprises 6. Prompt Engineering for Enterprises 7. Fine-tuning for Enterprises 8. Orchestration of Generative AI Workflows 9. Six Ethical Dimensions for Enterprises 10. Designing a Target Operating Model 11. Cost Optimization Strategies 12. Retrieval-augmented Generation for Enterprises 13. Model as a Service for Enterprises 14. Confidential AI 15. Latency in Generative AI Solutions 16. Multi-modal Multi-agentic Assistant Framework for Enterprises
