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AI modelling depends on several key components and factors that contribute to the development and deployment of effective artificial intelligence models.
AI is expected to become more global, integrated, and powerful
AI is expected to become more global, integrated, and powerful in various aspects of our lives. AI will create new opportunities for businesses and individuals to increase efficiency, productivity, and innovation, as well as enable new technologies like autonomous driving and medical diagnosis. However, AI also poses some risks and challenges, such as its impact on human meaning, autonomy, agency, and capabilities, and its potential to become uncontrollable and dangerous.
AI has the potential to significantly improve our quality of life in areas such as education and even at home. Humanoid robots are boosting the process of personalized learning. And while at home, cloud-connected robots can do chores such as vacuuming and cooking.
In the AI-enabled future, humans are going to be ready to converse and interact with one another within the language of choice, not having to stress about miscommunicating intentions. Machine learning models are going to be ready to understand context, nuance, and colloquialisms that help to fill the gaps in human communication.
AI systems so far relied on these for improvement: increased computing power, availability of more data, better algorithms and better tools. In all 4 areas, there is potential for dramatic improvements though it is hard to put these against a timeline.
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In AI Project: Role of Big Data, AI, ML, and Deep Learning
1. Big Data:
Big Data refers to large and complex sets of data that exceed the capabilities of traditional data processing applications. It involves vast volumes of structured, semi-structured, and unstructured data collected from various sources, such as social media, sensors, transactions, and more. The three main characteristics of Big Data are known as the three Vs: Volume (huge amounts of data), Velocity (the high speed at which data is generated and processed), and Variety (diverse types of data).
2. AI (Artificial Intelligence):
Artificial Intelligence is the simulation of human intelligence in machines that are programmed to think and act like humans. The goal of AI is to create systems that can perform tasks that typically require human intelligence, such as reasoning, problem-solving, learning, understanding natural language, and perception. AI can be either narrow AI (focused on specific tasks) or general AI (capable of handling any intellectual task).
3. ML (Machine Learning):
Machine Learning is a subset of AI that focuses on designing algorithms and statistical models that enable machines to learn from and make predictions or decisions based on data, without being explicitly programmed for each task. ML algorithms use patterns in the data to improve their performance over time, making them more accurate and effective. It is widely used in various applications like image recognition, natural language processing, recommendation systems, and more.
4. Deep Learning:
Deep Learning is a specialized field of Machine Learning that involves artificial neural networks, inspired by the structure and function of the human brain. Deep Learning models, known as deep neural networks, consist of multiple layers of interconnected nodes (neurons) that process and transform data at different levels of abstraction. Deep Learning has shown remarkable success in complex tasks such as image and speech recognition, natural language understanding, and playing games.
In summary, Big Data deals with handling massive and diverse datasets, AI involves creating intelligent systems, ML enables machines to learn from data and improve their performance, and Deep Learning focuses on building sophisticated neural networks to solve complex problems. These technologies often complement each other and are driving significant advancements in various industries and domains.
Preface of the Book: "AI-powered Enterprise Resource Planning"
Author and Researcher: Pradeep K. Suri
" AI-powered Enterprise Resource Planning "
(The Book Content is based on Author's Experience and Research)
Welcome to "AI-powered Enterprise Resource Planning" In this book, we embark on an exciting journey into the realm of AI and its integration with Enterprise Resource Planning (ERP) systems. Over the years, AI has rapidly emerged as a transformative force, revolutionizing industries, and redefining the way businesses operate. The convergence of AI and ERP brings forth a new era of possibilities, empowering enterprises to unlock the full potential of their data and make more informed, strategic decisions.
As the author, I have dedicated my career to the fields of computer science and business data processing, witnessing firsthand the evolution of technology and its impact on organizations. Through this book, I aim to provide a comprehensive understanding of how AI is reshaping the enterprise landscape and how it can be effectively harnessed within ERP systems.
Part I lays the groundwork by exploring the foundations of AI in the enterprise. We delve into various AI technologies, such as machine learning, natural language processing, and computer vision, to establish a solid understanding of the tools and techniques driving AI-driven solutions. Additionally, we dive into the evolution of ERP systems, their components, and the challenges they have traditionally faced.
In Part II, we shift our focus to practical applications of AI in ERP systems. We explore how AI optimizes supply chain management, enhances sales and customer relationship management, enables financial management, and transforms human resources and talent management. Each chapter provides valuable insights into how AI can streamline processes, improve decision-making, and drive business growth in these key areas.
Part III is dedicated to the implementation of AI-driven ERP solutions. We address the obstacles and challenges that arise when integrating AI with ERP, including data integration, ethical considerations, change management, and security. Furthermore, we provide best practices for successful AI-ERP implementation, guiding you through defining business objectives, selecting the right solution, ensuring data governance, and building a skilled team.
Throughout this book, I emphasize the importance of striking a balance between human and machine collaboration. While AI presents tremendous opportunities, it is crucial to recognize the unique strengths and limitations of both humans and machines. By embracing this synergy, enterprises can harness the power of AI while preserving the invaluable human touch.
I hope this book serves as a valuable resource for business leaders, IT professionals, researchers, and anyone passionate about leveraging AI in the enterprise. The possibilities are vast, and by embracing AI-driven ERP solutions, organizations can position themselves for sustainable competitive advantage in an increasingly digital world.
I invite you to join me on this enlightening journey as we uncover the transformative power of artificial intelligence within the enterprise realm.
Pradeep K. Suri
Author and Researcher