Scholarlink

As we have seen, the roots of AI lie in a fusion of ideas and visionary efforts, driven by pioneering reflections on the possibility of endowing machines with intelligence. From these origins, AI has undergone a rapid developmental trajectory, constantly redefining the boundaries of our interaction with intelligent technology. However, despite its 70-year history, the spectacular progress we have witnessed over the last quarter-century is also due to two other essential factors: the extraordinary power of computers, particularly those based on GPUs (graphics processing units), which are especially efficient in training and implementing machine learning algorithms, and the vast availability of data—Big Data—which, in many fields, is essential for training machine learning algorithms (see Fig. 3.1).

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Machine Learning: When Computers Learn (On Their Own!)

  • 章节

  • 发表日期：

    2025年

查看全文
  • Alfio Quarteroni

摘要

As we have seen, the roots of AI lie in a fusion of ideas and visionary efforts, driven by pioneering reflections on the possibility of endowing machines with intelligence. From these origins, AI has undergone a rapid developmental trajectory, constantly redefining the boundaries of our interaction with intelligent technology. However, despite its 70-year history, the spectacular progress we have witnessed over the last quarter-century is also due to two other essential factors: the extraordinary power of computers, particularly those based on GPUs (graphics processing units), which are especially efficient in training and implementing machine learning algorithms, and the vast availability of data—Big Data—which, in many fields, is essential for training machine learning algorithms (see Fig. 3.1).