87 research outputs found

    Knowledge-based systems in Japan

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    This report summarizes a study of the state-of-the-art in knowledge-based systems technology in Japan, organized by the Japanese Technology Evaluation Center (JTEC) under the sponsorship of the National Science Foundation and the Advanced Research Projects Agency. The panel visited 19 Japanese sites in March 1992. Based on these site visits plus other interactions with Japanese organizations, both before and after the site visits, the panel prepared a draft final report. JTEC sent the draft to the host organizations for their review. The final report was published in May 1993

    Can we accelerate medicinal chemistry by augmenting the chemist with Big Data and artificial intelligence?

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    It is both the best of times and the worst of times to be a medicinal chemist. Massive amounts of data combined with machine-learning and/or artificial intelligence (AI) tools to analyze it can increase our capabilities. However, drug discovery faces severe economic pressure and a high level of societal need set against challenging targets. Here, we show how improving medicinal chemistry by better curating and exchanging knowledge can contribute to improving drug hunting in all disease areas. Although securing intellectual property (IP) is a critical task for medicinal chemists, it impedes the sharing of generic medicinal chemistry knowledge. Recent developments enable the sharing of knowledge both within and between organizations while securing IP. We also explore the effects of the structure of the corporate ecosystem within drug discovery on knowledge sharing

    A Personal View of Expert Systems: Looking Back and Looking Ahead

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    this paper, I will do some storytelling--of my career in AI, of the events preceding and accompanying the birth of expert systems, and of the recent birth of the second era of knowledge based systems. When a movie tells a story, sometimes the credits are given at the front and sometimes they are left to the end. I am moved to want to give credit at the very beginning of this paper to many extraordinary people who have been my intellectual companions and great friends along the way. In truth, I feel like a stand-in for the staff and students of the Stanford Heuristic Programming Project, whose work over 15 years was responsible for the birth and early development of expert systems

    The art of artificial intelligence -- 1. Themes and case studies of knowledge engineering

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    The knowledge engineer practices the art of bringing the principles and tools of AI research to bear on difficult applications problems requiring experts' knowledge for their solution. The technical issues of acquiring this knowledge, representing it, and using it appropriately to construct and explain lines-of-reasoning, are important problems in the design of knowledge-based systems. Various systems that have achieved expert level performance in scientific and medical inference illuminate the art of knowledg
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