Artificial Intelligence for Science: A Deep Learning Revolution

This unique collection introduces AI, Machine Learning (ML), and deep neural network technologies leading to scientific discovery from the datasets generated both by supercomputer simulation and by modern experimental facilities.Huge quantities of experimental data come from many sources -- telescopes, satellites, gene sequencers, accelerators, and electron microscopes, including international facilities such as the Large Hadron Collider (LHC) at CERN in Geneva and the ITER Tokamak in France. These sources generate many petabytes moving to exabytes of data per year. Extracting scientific insights from these data is a major challenge for scientists, for whom the latest AI developments will be essential.The timely handbook benefits professionals, researchers, academics, and students in all fields of science and engineering as well as AI, ML, and neural networks. Further, the vision evident in this book inspires all those who influence or are influenced by scientific progress.

這本獨特的收藏品介紹了人工智慧（AI）、機器學習（ML）和深度神經網絡技術，這些技術可以從超級計算機模擬和現代實驗設施生成的數據集中進行科學發現。大量的實驗數據來自多個來源，包括望遠鏡、衛星、基因序列儀、加速器和電子顯微鏡，其中包括位於日內瓦的歐洲核子研究組織（CERN）的大型強子對撞機（LHC）和法國的ITER托卡馬克。這些來源每年產生數百萬億到數百億億字節的數據。從這些數據中提取科學見解對科學家來說是一個重大挑戰，他們將需要最新的人工智慧發展。這本及時的手冊對所有科學和工程領域的專業人士、研究人員、學者和學生以及人工智慧、機器學習和神經網絡領域的人士都有益處。此外，這本書所展示的願景也激勵著所有影響或受到科學進步影響的人們。