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Learn Autonomous Programming with Python : Utilize Python’s capabilities in artificial intelligence, machine learning, deep learning and robotic process automation
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Food Engineering Automation with Robotics and AI
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Artificial Intelligence and Learning Futures : Critical Narratives of Technology and Imagination in Higher Education
Artificial Intelligence and Learning Futures: Critical Narratives of Technology and Imagination in Higher Education explores the implications of artificial intelligence’s adoption in higher education and the challenges to building sustainable instead of dystopic schooling.As AI becomes integral to both pedagogy and profitability in today’s colleges and universities, a critical discourse on these systems and algorithms is urgently needed to push back against their potential to enable surveillance, control, and oppression.This book examines the development, risks, and opportunities inherent to AI in education and curriculum design, the problematic ideological assumptions of intelligence and technology, and the evidence base and ethical imagination required to responsibly implement these learning technologies in a way that ensures quality and sustainability.Leaders, administrators, and faculty as well as technologists and designers will find these provocative and accessible ideas profoundly applicable to their research, decision-making, and concerns.
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Foundations of Artificial Intelligence and Robotics : Volume 2 A Historical Background
Artificial intelligence (AI) is a complicated science that combines philosophy, cognitive psychology, neuroscience, mathematics and logic (logicism), economics, computer science, computability, and software.Meanwhile, robotics is an engineering field that compliments AI.There can be situations where AI can function without a robot (e.g., Turing Test) and robotics without AI (e.g., teleoperation), but in many cases, each technology requires each other to exhibit a complete system: having "smart" robots and AI being able to control its interactions (i.e., effectors) with its environment.This book provides a complete history of computing, AI, and robotics from its early development to state-of-the-art technology, providing a roadmap of these complicated and constantly evolving subjects. Divided into two volumes covering the progress of symbolic logic and the explosion in learning/deep learning in natural language and perception, this second volume goes more in-depth into the history of artificial intelligence, starting with key people and important events that bring us to the present day. Key Features:Builds on the insights provided in volume 1 to look into the future of AI and robotics. Provides a holistic view of AI, and touches on all the misconceptions and tangents to the technologies through taking a systematic approach. Provides a glossary of terms, list of notable people, and extensive references. Provides the interconnections and history of the progress of technology for over 100 years as both the hardware (Moore’s Law, GPUs) and software, i.e., generative AI, has advanced. Intended as a complete reference, this book is useful to undergraduate and postgraduate students of computing, as well as the general reader.It can also be used as a textbook by course convenors.If you only had one book on AI and robotics, this set would be the first reference to acquire and learn about the theory and practice.
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Which programming language is used for robotics and artificial intelligence?
Python is commonly used for robotics and artificial intelligence due to its simplicity, readability, and extensive libraries for machine learning and robotics. It is also known for its flexibility and ease of integration with hardware, making it a popular choice for developing robotics and AI applications. Additionally, Python's strong community support and active development make it a suitable language for these rapidly evolving fields.
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Is machine learning already artificial intelligence?
Machine learning is a subset of artificial intelligence. It involves training a machine to learn from data and make predictions or decisions without being explicitly programmed to do so. Artificial intelligence, on the other hand, encompasses a broader range of technologies and applications that enable machines to perform tasks that typically require human intelligence, such as understanding natural language, recognizing patterns, and solving problems. While machine learning is an important component of artificial intelligence, AI also includes other techniques such as natural language processing, computer vision, and robotics.
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What is Automation 2?
Automation 2 refers to the next level of automation in a system or process. It involves the use of advanced technologies such as artificial intelligence, machine learning, and robotics to further streamline and optimize tasks and operations. Automation 2 aims to reduce human intervention even further, increase efficiency, and improve accuracy in various industries such as manufacturing, logistics, and customer service. This level of automation often requires more sophisticated and complex systems to be implemented.
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How difficult is a study of robotics and automation?
The study of robotics and automation can be challenging due to its interdisciplinary nature, requiring knowledge in fields such as mechanical engineering, electrical engineering, computer science, and control systems. Additionally, the rapid advancements in technology and the need to stay updated with the latest developments can add to the complexity of the study. However, with dedication, problem-solving skills, and a strong foundation in mathematics and physics, students can overcome these challenges and excel in the field of robotics and automation.
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Advances in Robotics and Artificial Intelligence
The reality of autonomous machines with artificial intelligence is becoming more real every day.The ability of machines to think and learn fascinates everyone, but now even the most reluctant readers have a chance to engage in learning about the history and future of robotics.This book covers everything from the 18th century French automatons to Ada Lovelace and Alan Turing, from self-driving cars and smart homes to assembly and military robots.Each spread is complimented with vivid artwork that further illuminates the accessible, exciting text.
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Artificial Intelligence And Innovation Management
Artificial Intelligence and Innovation Management contributes to the ongoing debate among innovation scholars and practitioners focusing on the potential impact of Artificial Intelligence (AI) on the ways companies and organizations do business, operate and innovate.It considers AI as a source of innovation both in terms of innovation within the field of AI itself (AI innovation) and in terms of how it enables or disrupts innovation in other fields (AI-driven innovation).The book's content is driven by several important conclusions:It is therefore both necessary and timely to explore the different aspects of the relationship between AI and IM.The contributors to this book include both scholars and practitioners from multiple countries and different types of institutions.They were selected based on their ability to provide a relevant distinctive perspective on the relationship between AI and IM; the degree of their professional engagement with the field; their ability to contribute to the thematic and contextual diversity of the contributions; and their ability to provide actionable insights for both innovation scholars and practitioners.Helena Blackbright (Mälardalen University, Sweden) and Stoyan Tanev (Carleton University, Canada) are chairing the Special Interest Group on AI and IM at the International Society for Professional Innovation Management (https://www.ispim-innovation.com/).
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Adopting Artificial Intelligence Tools in Higher Education : Teaching and Learning
The book offers a modern exploration of the intersection of technology and education.It examines the prospects of integrating different AI tools into higher education and explores the challenges, opportunities, and innovative solutions for the different issues surrounding the use of AI in higher education. Each chapter discusses a different area where AI can enhance the educational landscape, such as AI Integration in Higher Education and Immersive Virtual Reality-Based Learning Environments.The book also emphasizes Student-Centered Learning, AI-powered frameworks for academic excellence, and Learner-Centric Pedagogies.Furthermore, it delves into the role of AI in Personalized Learning in STEM courses, the development of AI-based Tutoring Systems, and the use of Machine Learning to identify students' mental health status.The volume concludes with "Dynamic Horizon," which examines how AI and gamification are shaping higher education. This book is essential for educators, administrators, researchers, and policymakers who want to leverage AI to create an adaptive, personalized, and engaging learning environment. "Adopting Artificial Intelligence Tools in Higher Education" provides valuable insights into the future of education, paving the way for a more empowered and enlightened academic world.
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Adopting Artificial Intelligence Tools in Higher Education : Teaching and Learning
This book offers a modern exploration of the intersection of technology and education.It examines the prospects of integrating different AI tools into higher education and explores the challenges, opportunities, and innovative solutions for the different issues surrounding the use of AI in higher education. Each chapter discusses a different area where AI can enhance the educational landscape, such as AI integration in higher education and immersive virtual reality-based learning environments.The book also emphasizes student-centered learning, AI-powered frameworks for academic excellence, and learner-centric pedagogies.Furthermore, it delves into the role of AI in personalized learning in STEM courses, the development of AI-based tutoring systems, and the use of machine learning to identify students’ mental health status.The volume concludes with "Dynamic Horizon," which examines how AI and gamification are shaping higher education. This book is essential for educators, administrators, researchers, and policymakers who want to leverage AI to create an adaptive, personalized, and engaging learning environment.Adopting Artificial Intelligence Tools in Higher Education provides valuable insights into the future of education, paving the way for a more empowered and enlightened academic world.
Price: 130.00 £ | Shipping*: 0.00 £
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How could society of tomorrow look like as artificial intelligence and automation continue to advance?
As artificial intelligence and automation continue to advance, the society of tomorrow could see significant changes in various aspects of life. There may be increased efficiency and productivity in industries, leading to a shift in the job market and the need for new skill sets. There could also be advancements in healthcare, transportation, and communication, improving the overall quality of life. However, there may also be concerns about job displacement and the ethical implications of AI, leading to a need for new regulations and policies to ensure a fair and equitable society. Overall, the society of tomorrow could be more technologically advanced, but it will also require careful consideration of the social and ethical impacts of these advancements.
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How can one learn to become an electronics technician for industrial engineering or automation technology?
To become an electronics technician for industrial engineering or automation technology, one can start by pursuing a relevant educational program, such as an associate degree in electronics engineering technology or industrial automation. These programs typically cover topics such as electrical circuits, industrial control systems, and automation technologies. Additionally, gaining hands-on experience through internships or apprenticeships with companies in the industrial engineering or automation field can provide valuable practical skills. Seeking professional certifications, such as those offered by organizations like the International Society of Automation (ISA) or the Electronics Technicians Association (ETA), can also demonstrate expertise and knowledge in the field. Finally, staying updated with the latest advancements in industrial engineering and automation technology through continuous learning and professional development is essential for a successful career in this field.
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Is artificial intelligence an opportunity or a risk for learning in school?
Artificial intelligence can be both an opportunity and a risk for learning in school. On one hand, AI can personalize learning experiences, provide instant feedback, and offer additional resources to support student learning. This can enhance student engagement and understanding. However, there are also concerns about the potential for AI to replace teachers, compromise student privacy, and perpetuate biases in the learning process. Therefore, it is important for educators to carefully consider how to integrate AI into the classroom in a way that maximizes its benefits while minimizing its risks.
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Is artificial intelligence an opportunity or a risk for learning in schools?
Artificial intelligence presents both opportunities and risks for learning in schools. On one hand, AI can personalize learning experiences, provide instant feedback, and assist teachers in managing administrative tasks. This can lead to more efficient and effective learning outcomes for students. However, there are concerns about the potential for AI to replace human teachers, invade student privacy, and perpetuate biases in the education system. Therefore, it is important for schools to carefully consider how to integrate AI in a way that maximizes its benefits while mitigating its risks.
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