This book enables STEMM researchers to write effective papers for publication as well as other research-related texts such as a doctoral thesis, technical report, or conference abstract. Science Research Writing uses a reverse-engineering approach to writing developed from extensive work with STEMM researchers at Imperial College London. This approach unpacks current models of STEMM research writing and helps writers to generate the writing tools needed to operate those models effectively in their own field. The reverse-engineering approach also ensures that writers develop future-proof strategies that will evolve alongside the coming changes in research communication platforms. The Second Edition has been extensively revised and updated to represent current practice and focuses on the writing needs of both early-stage doctoral STEMM researchers and experienced professional researchers at the highest level, whether or not they are native speakers of English. The book retains the practical, user-friendly form

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, and offers a road map for teachers, parents, and students to navigate this exciting (and sometimes intimidating) new world. A pioneer in the field of education technology, Khan examines the ins and outs of these cutting-edge tools and how they will revolutionize the way we learn and teach. For parents concerned about their children s success, Khan illustrates how AI can personalize learning by adapting to each student s individual pace and style, identifying strengths and areas for improvement, and offering tailored support and feedback to complement traditional classroom instruction. Khan emphasizes that embracing AI in education is not about replacing human interaction but enhancing it with customized and accessible learning tools that encourage creative problem-solving skills and prepare

A rich, narrative explanation of the mathematics that has brought us machine learning and the ongoing explosion of artificial intelligence Machine learning systems are making life-altering decisions for us: approving mortgage loans, determining whether a tumour is cancerous, or deciding whether someone gets bail. They now influence developments and discoveries in chemistry, biology, and physics the study of genomes, extra-solar planets, even the intricacies of quantum systems. And all this before large language models such as ChatGPT came on the scene. We are living through a revolution in machine learning-powered AI that shows no signs of slowing down. This technology is based on relatively simple mathematical ideas, some of which go back centuries, including linear algebra and calculus, the stuff of seventeenth- and eighteenth-century mathematics. It took the birth and advancement of computer science and the kindling of 1990s computer chips designed for video games to ignite the explosion of AI that we s