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  • A Perfect Explanation
    A Perfect Explanation

    Longlisted for the Not the Booker Prize 2019 Longlisted for The Desmond Elliott Prize 2019 Observer: Fiction to look out for in 2019 The i Paper’s 30 of the best new debut novels to read in 2019 Scottish Review of Books: 2019 in Prospect As featured on BBC Woman’s Hour, Sky Sunrise and London Live ‘Filled with cerebral intensity and scintillating dialogue’ —The Desmond Elliott Prize Exploring themes of ownership and abandonment, Eleanor Anstruther’s bestselling debut is a fictionalised account of the true story of Enid Campbell (1892–1964), granddaughter of the 8th Duke of Argyll. Interweaving one significant day in 1964 with a decade during the interwar period, A Perfect Explanation gets to the heart of what it is to be bound by gender, heritage and tradition, to fight, to lose, to fight again.In a world of privilege, truth remains the same; there are no heroes and villains, only people misunderstood.Here, in the pages of this extraordinary book where the unspoken is conveyed with vivid simplicity, lies a story that will leave you reeling.

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  • Levels of Explanation
    Levels of Explanation

    This is an open access title available under the terms of a CC BY-NC-ND 4.0 International licence.It is free to read at Oxford Scholarship Online and offered as a free PDF download from OUP and selected open access locations. The different sciences furnish us with a wide variety of explanations: some work at macroscopic scales, some work at microscopic scales, and some operate across different levels.How do these different explanatory levels relate to one another, and what is an explanatory level in the first place?Over the last 50 years, more and more philosophers--both reductionists and anti-reductionists--no longer subscribe to the idea that the best explanation resides at the fundamental physical level.New challenges arise from the success of scientific explanations employing multi-level models which mix levels of explanation, from distinctive differences between levels structures in biology, cognitive science, and social science, from the apparently radical reimagining of the explanatory role of spacetime in our current best theories of fundamental physics, and from the enduring mystery of how higher-level explanations are possible in the first place.These questions naturally connect to classic philosophical ways of thinking about the relationships between levels: reduction, emergence, and fundamentality.This volume presents a snapshot of cutting-edge research on explanatory levels, from their conceptual foundations to the details of how they are used in scientific practice.

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  • Explanation and Understanding
    Explanation and Understanding

    Science aims to describe reality, to predict the future and to supply us with technology.But it also aims to explain and understand the world.What does it take to explain a phenomenon? Why are some explanations better than others? How do explanation and understanding relate to each other?In this thorough and clearly written introduction, Arnon Levy explores philosophical theories of explanation and understanding which can help answer these questions.Highlighted themes include:What are explanations and what makes some explanations better than others?Empiricism about explanation: Hempel's Deductive-Nomological model and its discontentsCausation and Causal theories of explanation: From Lewis, through Woodward to StrevensExplanatory models, the role idealization and abstraction in generating understandingMechanistic explanation: What is a mechanism?What kind of understanding do mechanistic models supply?Mathematical and other non-causal explanationsUnderstanding and its relation to explanation. Arguments are fleshed out with examples, chapter summaries, a glossary of key terms, and accompanying illustrations.As such, Explanation and Understanding is suitable for independent study or as a companion to classes in philosophy of science, metaphysics and other areas of philosophy in which explanation looms large.

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  • Explanation and Understanding
    Explanation and Understanding

    Science aims to describe reality, to predict the future and to supply us with technology.But it also aims to explain and understand the world.What does it take to explain a phenomenon? Why are some explanations better than others? How do explanation and understanding relate to each other?In this thorough and clearly written introduction, Arnon Levy explores philosophical theories of explanation and understanding which can help answer these questions.Highlighted themes include:What are explanations and what makes some explanations better than others?Empiricism about explanation: Hempel's Deductive-Nomological model and its discontentsCausation and Causal theories of explanation: From Lewis, through Woodward to StrevensExplanatory models, the role idealization and abstraction in generating understandingMechanistic explanation: What is a mechanism?What kind of understanding do mechanistic models supply?Mathematical and other non-causal explanationsUnderstanding and its relation to explanation. Arguments are fleshed out with examples, chapter summaries, a glossary of key terms, and accompanying illustrations.As such, Explanation and Understanding is suitable for independent study or as a companion to classes in philosophy of science, metaphysics and other areas of philosophy in which explanation looms large.

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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.

  • 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.

  • Can you give a brief explanation of education?

    Education is the process of acquiring knowledge, skills, values, and attitudes through various methods such as teaching, training, and research. It is a lifelong journey that begins at a young age and continues throughout one's life. Education can take place in formal settings such as schools and universities, as well as informal settings such as at home or in the community. Its ultimate goal is to empower individuals to reach their full potential and contribute to the betterment of society.

  • 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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  • Learn Autonomous Programming with Python : Utilize Python’s capabilities in artificial intelligence, machine learning, deep learning and robotic process automation
    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
    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

    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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  • The Explanation of Behaviour
    The Explanation of Behaviour

    The Explanation of Behaviour was the first book written by the renowned philosopher Charles Taylor.A vitally important work of philosophical anthropology, it is a devastating criticism of the theory of behaviourism, a powerful explanatory approach in psychology and philosophy when Taylor's book was first published.However, Taylor has far more to offer than a simple critique of behaviourism.He argues that in order to properly understand human beings, we must grasp that they are embodied, minded creatures with purposes, plans and goals, something entirely lacking in reductionist, scientific explanations of human behaviour. Taylor’s book is also prescient in according a central place to non-human animals, which like human beings are subject to needs, desires and emotions.However, because human beings have the unique ability to interpret and reflect on their own actions and purposes and declare them to others, Taylor argues that human experience differs to that of other animals.Furthermore, the fact that human beings are often directed by their purposes has a fundamental bearing on how we understand the social and moral world.Taylor’s classic work is essential reading for those in philosophy and psychology as well as related areas such as sociology and religion. This Routledge Classics edition includes a new Preface by the author and a new Foreword by Alva Noë, setting the book in philosophical and historical context.

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  • What is the explanation for voltage in volts in electrical engineering?

    Voltage in electrical engineering is a measure of the electric potential difference between two points in a circuit. It is measured in volts, which is the unit of electric potential. Voltage is the force that pushes electric charges through a circuit, and it is the driving force behind the flow of electric current. In simple terms, voltage is the amount of energy that each unit of charge possesses, and it is essential for understanding and designing electrical circuits.

  • 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.

  • 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.

  • 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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