Author: Zhihan Lyu
Publisher: Springer Nature
ISBN: 3031462386
Category :
Languages : en
Pages : 607

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Book Description

Author: Anand Vemula
Publisher: Independently Published
ISBN:
Category : Computers
Languages : en
Pages : 0

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Book Description
Generative AI in Computer Science: Navigating Ethical and Societal Frontiers" offers a comprehensive exploration of the burgeoning field of generative artificial intelligence (AI). This book delves into the ethical considerations and societal implications surrounding the development and deployment of generative AI technologies. Readers will gain insights into crucial topics such as bias and fairness, privacy concerns, transparency, and accountability. Through real-world examples, use cases, case studies, and scenarios, the book illuminates the potential of generative AI to revolutionize various domains, from natural language processing and computer vision to healthcare and beyond. Additionally, it discusses emerging trends in AI art and addresses potential challenges such as the spread of misinformation. As generative AI continues to shape the future of technology, this book serves as a roadmap for navigating its complexities while fostering responsible development and deployment practices.

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: David Foster
Publisher: "O'Reilly Media, Inc."
ISBN: 1492041890
Category : Computers
Languages : en
Pages : 360

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Book Description
Generative modeling is one of the hottest topics in AI. It’s now possible to teach a machine to excel at human endeavors such as painting, writing, and composing music. With this practical book, machine-learning engineers and data scientists will discover how to re-create some of the most impressive examples of generative deep learning models, such as variational autoencoders,generative adversarial networks (GANs), encoder-decoder models and world models. Author David Foster demonstrates the inner workings of each technique, starting with the basics of deep learning before advancing to some of the most cutting-edge algorithms in the field. Through tips and tricks, you’ll understand how to make your models learn more efficiently and become more creative. Discover how variational autoencoders can change facial expressions in photos Build practical GAN examples from scratch, including CycleGAN for style transfer and MuseGAN for music generation Create recurrent generative models for text generation and learn how to improve the models using attention Understand how generative models can help agents to accomplish tasks within a reinforcement learning setting Explore the architecture of the Transformer (BERT, GPT-2) and image generation models such as ProGAN and StyleGAN

Author: Jonas Bjerg
Publisher: Springer Nature
ISBN:
Category :
Languages : en
Pages : 191

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Book Description

Author: Tristan Behrens
Publisher: BoD – Books on Demand
ISBN: 3758382718
Category : Computers
Languages : en
Pages : 139

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Book Description
"Rewrite for Readability" is a captivating memoir of 1 year in the life of the author, a multifaceted artist and technologist, that intertwines his personal journey with the evolving landscape of Artificial Intelligence. Born in a small German village in the 1980s, the author's life is a vivid tapestry of creativity and technological exploration. From his early days drawing fantastic beasts, inspired by the serene nature of the Harz Mountains, to his dynamic career spanning computer science, music composition, and AI, this book offers a unique perspective on the synergy of human creativity and machine intelligence. The author's narrative is deeply personal, recounting his upbringing in a quintessential German family, his transformative childhood and youth, and his academic pursuits. Professionally, the author has achieved a doctorate in Computer Science, with a focus on Artificial Intelligence, and has successfully published creative music influenced by computational methods. His philosophy is rooted in the power of learning and creativity to unlock human potential, a theme that resonates throughout his story. "Rewrite for Readability" is not just a memoir; it is a testament to the harmonious collaboration between human thought and AI. The author shares his experiences as an AI Music Artist in Residence and his involvement with the innovative ensemble Hexagon Machine, illustrating how AI has become an integral part of his creative process. The book is adorned with AI-generated images, complementing the narrative and inviting readers to engage their own imagination. This book is a must-read for anyone interested in the intersection of technology, creativity, and personal growth.

Author: Midhun Moorthi C
Publisher: Academic Guru Publishing House
ISBN: 8119338790
Category : Study Aids
Languages : en
Pages : 209

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Book Description
This book provides a thorough introduction to two cutting-edge technologies known as Generative AI and ChatGPT. Both of these technologies have received much attention in recent years. Generative AI and ChatGPT can completely reshape sectors and society as a whole by increasing productivity and innovation and making it possible to have more tailored experiences. The natural language processing tool, ChatGPT, powered by artificial intelligence technology, enables you to engage in human-like conversation with the chatbot and provides several other benefits. The language model can answer inquiries and assist with activities such as the composition of emails, essays, and code. This book aims to give a comprehensive overview of the technologies, architectures, and training techniques mentioned above, including their history, the process by which they were developed, and their present status. This book assists in discovering novel applications of these technologies that have been put into practice to generate quantifiable advantages, such as increased efficiency, customer happiness, security, and revenue growth. The book also discusses the book's potential applicability across a variety of sectors and use cases.

Author: Mohamed Lahby
Publisher: Springer Nature
ISBN: 3031656911
Category :
Languages : en
Pages : 440

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Book Description

Author: Chris Fregly
Publisher: "O'Reilly Media, Inc."
ISBN: 1098159187
Category :
Languages : en
Pages : 323

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Book Description
Companies today are moving rapidly to integrate generative AI into their products and services. But there's a great deal of hype (and misunderstanding) about the impact and promise of this technology. With this book, Chris Fregly, Antje Barth, and Shelbee Eigenbrode from AWS help CTOs, ML practitioners, application developers, business analysts, data engineers, and data scientists find practical ways to use this exciting new technology. You'll learn the generative AI project life cycle including use case definition, model selection, model fine-tuning, retrieval-augmented generation, reinforcement learning from human feedback, and model quantization, optimization, and deployment. And you'll explore different types of models including large language models (LLMs) and multimodal models such as Stable Diffusion for generating images and Flamingo/IDEFICS for answering questions about images. Apply generative AI to your business use cases Determine which generative AI models are best suited to your task Perform prompt engineering and in-context learning Fine-tune generative AI models on your datasets with low-rank adaptation (LoRA) Align generative AI models to human values with reinforcement learning from human feedback (RLHF) Augment your model with retrieval-augmented generation (RAG) Explore libraries such as LangChain and ReAct to develop agents and actions Build generative AI applications with Amazon Bedrock

Author: David Foster
Publisher: "O'Reilly Media, Inc."
ISBN: 109813415X
Category : Computers
Languages : en
Pages : 456

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Book Description
Generative AI is the hottest topic in tech. This practical book teaches machine learning engineers and data scientists how to use TensorFlow and Keras to create impressive generative deep learning models from scratch, including variational autoencoders (VAEs), generative adversarial networks (GANs), Transformers, normalizing flows, energy-based models, and denoising diffusion models. The book starts with the basics of deep learning and progresses to cutting-edge architectures. Through tips and tricks, you'll understand how to make your models learn more efficiently and become more creative. Discover how VAEs can change facial expressions in photos Train GANs to generate images based on your own dataset Build diffusion models to produce new varieties of flowers Train your own GPT for text generation Learn how large language models like ChatGPT are trained Explore state-of-the-art architectures such as StyleGAN2 and ViT-VQGAN Compose polyphonic music using Transformers and MuseGAN Understand how generative world models can solve reinforcement learning tasks Dive into multimodal models such as DALL.E 2, Imagen, and Stable Diffusion This book also explores the future of generative AI and how individuals and companies can proactively begin to leverage this remarkable new technology to create competitive advantage.