自然语言处理和人工智能的最新技术进展
Recent Technological Advances in Natural Language Processing and Artificial Intelligence
摘要：
计算机技术的最新进展使科学家们能够实现和测试那些在很长一段时间内（或不知道）就已经知道但计算成本很高的算法。两个这样的项目是IBM的Jeopardy作为其DeepQA项目的一部分[1]和Wolfram的WolframAlpha[2]。这两种方法都实现了自然语言处理（人工智能科学家的另一个目标），并试图回答用户提出的问题。虽然这两个项目的目标是相似的，但它们的核心都有不同的过程。在接下来的章节中，我们将解释IBM的Jeopardy和Wolfram alpha的机制和历史，以及这些项目在实现Ray Kurzweil [3]到2029年通过图灵测试的梦想方面的意义。还解释了将上述项目提升到一个新水平的秘诀。
英文摘要：
A recent advance in computer technology has permitted scientists to implement and test algorithms that were known from quite some time (or not) but which were computationally expensive. Two such projects are IBM's Jeopardy as a part of its DeepQA project [1] and Wolfram's Wolframalpha[2]. Both these methods implement natural language processing (another goal of AI scientists) and try to answer questions as asked by the user. Though the goal of the two projects is similar, both of them have a different procedure at it's core. In the following sections, the mechanism and history of IBM's Jeopardy and Wolfram alpha has been explained followed by the implications of these projects in realizing Ray Kurzweil's [3] dream of passing the Turing test by 2029. A recipe of taking the above projects to a new level is also explained.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
