Liza Macasukit Gernal - Böcker
Visar alla böcker från författaren Liza Macasukit Gernal. Handla med fri frakt och snabb leverans.
3 produkter
3 produkter
Large Language Models, AI, and Workforce Transformation
Strategies for Resilience and Growth
Häftad, Engelska, 2026
694 kr
Kommande
This book explains how cutting-edge AI tools, such as chatbots and predictive systems, are transforming our approach to work and problem-solving. It simplifies how businesses and individuals can utilize these technologies to enhance decision-making, increase productivity, and respond to fresh challenges.By using real-life scenarios and useful advice, the book illustrates how AI can assist individuals in acquiring new abilities, staying up to date in their careers, and generating chances for advancement, all while upholding fairness, ethics, and inclusivity in the work environment. It delves into the major impact of large language models (LLMs) on workforce dynamics and industry transformation. It assesses the impact of advanced AI systems such as GPT on running processes, decision-making, and required skills in fields like healthcare, marketing, education, and insurance.This book is a valuable resource for industry leaders as it brings together LLMs with practical applications that provide insight into how AI tools can drive innovation and agility in today’s businesses. This book explores practical approaches to integrating LLMs into professional training programs while overcoming the obstacles posed by rapid technological change. It provides in-depth insights into how companies can use LLMs to streamline regular tasks, increase efficiency, and facilitate strategic decision-making.The research also highlights strategies for training, reskilling, and upskilling employees using AI, to make sure they can work efficiently with AI systems. Through case studies and examples, the book shows how these models can be used to drive innovation and support ethical, sustainable business practices.
Large Language Models, AI, and Workforce Transformation
Strategies for Resilience and Growth
Inbunden, Engelska, 2026
1 655 kr
Kommande
This book explains how cutting-edge AI tools, such as chatbots and predictive systems, are transforming our approach to work and problem-solving. It simplifies how businesses and individuals can utilize these technologies to enhance decision-making, increase productivity, and respond to fresh challenges.By using real-life scenarios and useful advice, the book illustrates how AI can assist individuals in acquiring new abilities, staying up to date in their careers, and generating chances for advancement, all while upholding fairness, ethics, and inclusivity in the work environment. It delves into the major impact of large language models (LLMs) on workforce dynamics and industry transformation. It assesses the impact of advanced AI systems such as GPT on running processes, decision-making, and required skills in fields like healthcare, marketing, education, and insurance.This book is a valuable resource for industry leaders as it brings together LLMs with practical applications that provide insight into how AI tools can drive innovation and agility in today’s businesses. This book explores practical approaches to integrating LLMs into professional training programs while overcoming the obstacles posed by rapid technological change. It provides in-depth insights into how companies can use LLMs to streamline regular tasks, increase efficiency, and facilitate strategic decision-making.The research also highlights strategies for training, reskilling, and upskilling employees using AI, to make sure they can work efficiently with AI systems. Through case studies and examples, the book shows how these models can be used to drive innovation and support ethical, sustainable business practices.
Learning-Driven Data Fabrics for Sustainability
Cloud-to-Thing Continuum Solutions for Global Challenges
Inbunden, Engelska, 2026
1 682 kr
Skickas inom 10-15 vardagar
This book explores the distinct problems, trends, and future trajectories for constructing cohesive, sustainable data infrastructures that correspond with the United Nations Sustainable Development Goals (SDGs). In the contemporary digital ecosystem, the amalgamation of data across diverse platforms and environments—from cloud to edge to IoT—has become imperative for fostering creativity, sustainability, and efficiency. “Learning-Driven Data Fabric for Sustainable Cloud-to-Thing Continuum” examines the optimization of integration through sophisticated data fabrics enhanced by machine learning and AI. This book initiates its exploration by analyzing the fundamental concepts of a learning-driven data fabric that integrates cloud and IoT ecosystems, facilitating real-time decision-making and minimizing energy consumption. It offers comprehensive insights into how intelligent data management throughout the cloud-to-thing continuum may be utilized to enhance resource efficiency, facilitate smart city planning, and promote advancements in sectors such as healthcare, transportation, and agriculture. This book emphasizes how data fabrics may advance objectives related to affordable and clean energy (SDG 7), industrial innovation (SDG 9), and sustainable cities and communities (SDG 11), with sustainability as its central theme. This book illustrates how learning-driven data architectures are revolutionizing businesses and tackling global challenges through real-world case studies and upcoming trends. Subjects encompass edge computing, real-time data analytics, safe data transmission, and the reduction of carbon footprints via effective data processing. This study examines how data fabrics might alleviate the risks associated with cyberattacks and data breaches, while ensuring regulatory compliance and fostering sustainable, ethical AI operations. This book offers a detailed framework for utilizing data fabric technologies to create sustainable, safe, and intelligent cloud-to-thing ecosystems, regardless of whether you are a data scientist, IoT specialist, cloud architect, or policymaker. This book promotes data-driven decision-making throughout the infrastructure, enabling organizations to design scalable and sustainable solutions that advance global development objectives.