Böcker av Salman Khan

Whether we like it or not, the AI revolution is coming to education. In Brave New Words, Salman Khan, the visionary behind Khan Academy, explores how artificial intelligence and GPT technology will transform learning, offering a roadmap for teachers, parents, and students to navigate this exciting (and sometimes intimidating) new world.An insider in the world of education technology, Khan explains the ins and outs of these cutting-edge tools and how they will forever change the way we learn and teach. Rather than approaching the ChatGPT revolution with white-knuckled fear, Khan wants parents and teachers to embrace AI and adapt to it (while acknowledging its imperfections and limitations), so that every student can complement the work they're already doing in profoundly new and creative ways, to personalize learning, adapt assessments, and support success in the classroom.But Brave New Words is not just about technology - it's about what this technology means for our society, and the practical implications for administrators, guidance counsellors, and hiring managers who can harness the power of AI in education and the workplace. Khan also delves into the ethical and social implications of AI and GPT, offering thoughtful insights into how we can use these tools to build a more accessible education system for students around the world.

The Concept of Inner PeaceIn today's fast-paced and demanding world, finding inner peace seems like an elusive goal. We are constantly juggling multiple responsibilities, striving for success, and trying to keep up with the ever-increasing demands of our personal and professional lives. However, amidst this chaos, there exists a concept that can bring solace and tranquility into our lives - the concept of inner peace.Inner peace is not just a state of mind; it is a way of life. It is the ability to maintain a sense of calm and harmony within ourselves, regardless of external circumstances. It is about finding a balance between our work and personal life and nurturing our mental, emotional, and spiritual well-being.In the modern world, where the lines between work and life are often blurred, achieving inner peace becomes even more crucial. Balancing work and life is essential for our overall well-being and happiness. When we are constantly overwhelmed by the demands of work, it can take a toll on our mental and physical health, leading to stress, anxiety, and burnout. On the other hand, neglecting our work responsibilities can lead to feelings of guilt and dissatisfaction.To achieve inner peace, we need to create a mindful balance between our work and life. This involves setting clear boundaries, prioritizing self-care, and cultivating healthy habits. It means learning to say no when necessary, delegating tasks, and seeking support when needed. It also means making time for activities that bring us joy and nourish our soul, such as spending time with loved ones, pursuing hobbies, or simply taking a moment to connect with nature.Finding inner peace also requires a deep understanding of ourselves and our values. It involves exploring our beliefs, desires, and fears, and aligning our actions with our truest selves. It means letting go of attachments and expectations and embracing the present moment fully. Inner peace is not about achieving a state of perpetual happiness; it is about accepting theinevitable ups and downs of life with grace and equanimity.

Computer vision has become increasingly important and effective in recent years due to its wide-ranging applications in areas as diverse as smart surveillance and monitoring, health and medicine, sports and recreation, robotics, drones, and self-driving cars. Visual recognition tasks, such as image classification, localization, and detection, are the core building blocks of many of these applications, and recent developments in Convolutional Neural Networks (CNNs) have led to outstanding performance in these state-of-the-art visual recognition tasks and systems. As a result, CNNs now form the crux of deep learning algorithms in computer vision.This self-contained guide will benefit those who seek to both understand the theory behind CNNs and to gain hands-on experience on the application of CNNs in computer vision. It provides a comprehensive introduction to CNNs starting with the essential concepts behind neural networks: training, regularization, and optimization of CNNs.The book also discusses a wide range of loss functions, network layers, and popular CNN architectures, reviews the different techniques for the evaluation of CNNs, and presents some popular CNN tools and libraries that are commonly used in computer vision. Further, this text describes and discusses case studies that are related to the application of CNN in computer vision, including image classification, object detection, semantic segmentation, scene understanding, and image generation.This book is ideal for undergraduate and graduate students, as no prior background knowledge in the field is required to follow the material, as well as new researchers, developers, engineers, and practitioners who are interested in gaining a quick understanding of CNN models.