University of Bristol, United Kingdom.
Neural Netw. 2010 May;23(4):466-70. doi: 10.1016/j.neunet.2010.01.006. Epub 2010 Feb 10.
Statistical approaches to Artificial Intelligence are behind most success stories of the field in the past decade. The idea of generating non-trivial behaviour by analysing vast amounts of data has enabled recommendation systems, search engines, spam filters, optical character recognition, machine translation and speech recognition, among other things. As we celebrate the spectacular achievements of this line of research, we need to assess its full potential and its limitations. What are the next steps to take towards machine intelligence?
过去十年中，人工智能领域的大多数成功案例都得益于统计方法。通过分析大量数据来生成非平凡行为的想法，使得推荐系统、搜索引擎、垃圾邮件过滤器、光学字符识别、机器翻译和语音识别等技术成为可能。在庆祝这一研究领域取得巨大成就的同时，我们也需要评估其全部潜力和局限性。那么，迈向机器智能的下一步是什么？
