{"resolved":true,"match_type":"uuid","source_type":"original_book","book_id":"cf76bc49-7e9b-4f42-bee8-3050a9fb9feb","title":"智慧的疆界 从图灵机到人工智能","author":null,"edition":null,"publisher":null,"year":null,"isbn":"9787111778004","requested_by":"printed_page","book":{"source_type":"original_book","book_id":"cf76bc49-7e9b-4f42-bee8-3050a9fb9feb","id":"cf76bc49-7e9b-4f42-bee8-3050a9fb9feb","uuid":"cf76bc49-7e9b-4f42-bee8-3050a9fb9feb","title":"智慧的疆界 从图灵机到人工智能","normalized_title":"智慧的疆界从图灵机到人工智能","author":null,"edition":null,"publisher":null,"year":null,"isbn":"9787111778004","isbns":["9787111778004","9787111695714"],"parsed":true,"ai_readable":true,"document_type":"book","page_count":456,"navigation_url":"https://workshop.closeclaw.top/ai/book/cf76bc49-7e9b-4f42-bee8-3050a9fb9feb","title_url":"https://workshop.closeclaw.top/ai/title/%E6%99%BA%E6%85%A7%E7%9A%84%E7%96%86%E7%95%8C%20%E4%BB%8E%E5%9B%BE%E7%81%B5%E6%9C%BA%E5%88%B0%E4%BA%BA%E5%B7%A5%E6%99%BA%E8%83%BD","fixed_page_url_template":"https://workshop.closeclaw.top/ai/book/cf76bc49-7e9b-4f42-bee8-3050a9fb9feb/page/{printed_page}","path_api_url_template":"https://workshop.closeclaw.top/api/ai/book/cf76bc49-7e9b-4f42-bee8-3050a9fb9feb/page/{printed_page}","read_url":"https://workshop.closeclaw.top/api/ai/read/cf76bc49-7e9b-4f42-bee8-3050a9fb9feb","page_url":"https://workshop.closeclaw.top/api/ai/books/cf76bc49-7e9b-4f42-bee8-3050a9fb9feb/page","search_url":"https://workshop.closeclaw.top/api/ai/books/cf76bc49-7e9b-4f42-bee8-3050a9fb9feb/search"},"page":{"printed_page":310,"pdf_page":325,"physical_index":325,"physical_index_base":0,"printed_page_status":"recognized","page_sha256":"7843e8ca5caadfbb8adcb4dfc8bf592f8e23764bce9b236c3076509d434ec368"},"chapter":"内容简介","content":"另外，当下同时面向多个输入源头的“多模态学习”（Multi-modalLearning）与同时面向多个输出目标的“多任务学习”（Multi-task Learning）方法正在兴起。2020 年来自谷歌大脑项目团队和多伦多大学的研究人员发表了一篇关于多模型学习的新论文，通过综合视觉、语言和语音神经网络的优势可以实现同时解决多种不同任务的深度学习模型，包括图像识别、翻译和语音识别等方面，致力于创造出一种可以适应多种任务的神经网络架构。\n\n7.9 本章小结\n\n人工智能发展至今已经经历了两次低谷，对于某个依赖人工智能这门学科生存的研究人员和从业人员个体而言，人工智能的寒冬可能会带来很严重的打击，甚至可能令人从此一蹶不振。但是对于人工智能整个学科而言，寒冬其实并没有那么可怕，物理学家马克斯·普朗克（Max Planck，1858—1947）曾说过：“科学每经历一次葬礼就前进一步（Science advances one funeral at atime）<sup>○一</sup>。”即使在人工智能的冰河时期，尽管主角更迭，但机器学习这个领域\n\n310\n\n第三部分 第三波高潮\n\n○一 原意是指持有旧观念的科学家死亡或退出并非坏事，因为它会给新一代持有新观念的科学家让出舞台从而推动科学的进步。","previous_page":309,"next_page":311}