{"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":275,"pdf_page":290,"physical_index":290,"physical_index_base":0,"printed_page_status":"recognized","page_sha256":"b2b703f00afcfa63322e327d912612608d4cc044ae29c61909c7620f3d222018"},"chapter":"内容简介","content":"8 层的 AlexNet 开始，发展到 2015 年，来自微软研究院的 152 层的残差网络（ResNet）以仅 3.57% 的错误率赢得了 ILSVRC 2015 的冠军。“3.57%”这个错误率在三四年之前是谁都不可能想象的。李飞飞教授曾经组织过一批志愿者，直接以人类代替机器来参赛，这批志愿者在这个竞赛里，通过肉眼辨识图像的平均错误率是 5.1%，换言之，从 2015 年起，机器在对图像进行识别和分类这项技能上的成绩事实上已经超越了人类水平。这不仅是一个人工智能在认知领域超越人类的案例，更是深度神经网络的一次巨大成功，而且，它似乎还可以作为一个令人难以抗拒的“越深度越强大”的有力论据。\n\n在 ILSVRC 赛场一战成名，深度学习的热潮自此掀起，一波接一波向前迅猛推进，进入一个又一个领域并连战连捷，势如破竹，终于形成今天锐不可当的深度学习狂潮。\n\n7.5.5 越深度越强大吗\n\n今天我们还处于深度学习浪潮的顶峰，在深度学习不断攻城略地的同时，笔者也在思考几个问题：真的会是“越深度越强大”吗？神经网络会随着隐层数量的增加而继续无往不利吗？在深度不断发展的最后，是能够触碰到我们梦寐以求的机器智能，还是在一定深度之后，必然要与之前的浅层学习方法一样，触碰到天花板乃至拐点，仍然无法接触到智能的身影呢？\n\n第 7 章 深度学习时代\n\n275\n\n○一 纵坐标为错误率，越低结果越优秀。","previous_page":274,"next_page":276}