This research report introduces the generation of textual entailment within the project CSIEC (Computer Simulation in Educational Communication), an interactive web-based human-computer dialogue system with natural language for English instruction. The generation of textual entailment (GTE) is critical to the further improvement of CSIEC project. Up to now we have found few literatures related with GTE. Simulating the process that a human being learns English as a foreign language we explore our naive approach to tackle the GTE problem and its algorithm within the framework of CSIEC, i.e. rule annotation in NLML, pattern recognition (matching), and entailment transformation. The time and space complexity of our algorithm is tested with some entailment examples. Further works include the rules annotation based on the English textbooks and a GUI interface for normal users to edit the entailment rules.
CSIEC (Computer Simulation in Educational Communication), is not only an intelligent web-based human-computer dialogue system with natural language for English instruction, but also a learning assessment system for learners and teachers. Its multiple functions—including grammar-based gap filling exercises, scenario show, free chatting and chatting on a given topic—can satisfy the various requirements for students with different backgrounds and learning abilities. After a brief explanation of the conception of our dialogue system, as well as a survey of related works, we will illustrate the system structure, and describe its pedagogical functions with the underlying AI techniques in detail such as NLP and rule-based reasoning. We will summarize the free Internet usage within a six month period and its integration into English classes in universities and middle schools. The evaluation findings about the class integration show that the chatting function has been improved and frequently utilized by the users, and the application of the CSIEC system on English instruction can motivate the learners to practice English and enhance their learning process. Finally, we will conclude with potential improvements.
A team of researchers at the Beth Israel Deaconess Medical Center (BIDMC) and Harvard Medical School (HMS) in Boston have been working on developing artificial intelligence (AI) tools with potential to significantly change and improve accuracy in cancer and other disease diagnosis. Noting that pathology methods for diagnosing disease have stayed largely the same for the past 100 years with tissue samples manually reviewed under a microscope, the investigative work suggests diagnostic accuracy can be improved by using computers to interpret pathology images. "Our AI method is based on deep learning, a machine-learning algorithm used for a range of applications including speech recognition and image recognition," said Dr. Andrew Beck director of Bioinformatics at the Cancer Research Institute at Beth Israel Deaconess Medical Center (BIDMC) in press release. Beck, who is also an associate professor at Harvard Medical School said the approach teaches machines to interpret the complex patterns and structure observed in real-life data by building multi-layer artificial neural networks thought to be similar to how the learning occurs in the brain neocortex, where thinking occurs. The Beck lab's approach was recently tested in a competition at the annual meeting of the International Symposium of Biomedical Imaging (ISBI) held in Prague, Czech Republic, in April.
Berlin-based Babbel has announced that the former COO and publisher of Business Insider, Julie Hansen, has been hired as its first "CEO U.S." The company characterizes the position in a press release as "tak[ing] over the lead" from Babbel co-founder Thomas Holl, who is moving to Chief Strategy Officer; Hansen reports to Global CEO and co-founder Markus Witte . Babbel is a major player in the international and highly competitive online language learning market. A recent market report published by Ambient Insight estimated that U.S. consumers spent almost $400 million for digital language learning products in 2016, with a projected five year 3.1% CAGR. Babbel has raised $33 million from five investors since its founding in 2007, with its most recent Series C raise of $22 million in 2015. They now have about 450 employees according to the company.
Robotics projects coupled with agent-oriented trends in artificial intelligence education have the potential to make introductory AI courses at liberal arts schools the gateway for a large new generation of AI practitioners. However, this vision's achievement requires programming libraries and low-cost platforms that are readily accessible to undergraduates and easily maintainable by instructors at sites with few dedicated resources. This article presents and evaluates one contribution toward implementing this vision: the RCXLisp library. The library was designed to support programming of the Lego Mindstorms platform in AI courses with the goal of using introductory robotics to motivate undergraduates' understanding of AI concepts within the agent-design paradigm. The library's evaluation reflects four years of student feedback on its use in a liberal-arts AI course whose audience covers a wide variety of majors. To help establish a context for judging RCXLisp's effectiveness this article also provides a sketch of the Mindstormsbased laboratory in which the library is used.