Artificial intelligence (AI) has already transformed our lives, and it keeps altering different aspects of daily life. From driving autonomous vehicles to translating languages in real time, AI technologies can considerably improve the efficiency of every process in our diverse workplaces. That is why the Data Science Program at the College of Charleston is offering a four-day workshop for students to learn how AI can be integrated into different fields of science and technology. Sponsored by the South Carolina Council on Competitiveness, the Applications of Artificial Intelligence workshop was designed to teach about artificial intelligence through instructional and hands-on training activities. Workshop components include AI in Music and Art, AI in Natural Language Processing, AI in Smart Cities and Autonomous Vehicles, AI in Environmental Informatics, AI in Education and AI at Home.

Report on the 1984 Distributed Artificial Intelligence Workshop. Reprinted in Readings in Artificial Intelligence and Databases, J. Mylopoulos and M. L. Brodie, editors, Morgan Kaufmann Publishers, Inc., 1988. Report on the 1984 Distributed Artificial Intelligence Workshop. Reprinted in Readings in Artificial Intelligence and Databases, J. Mylopoulos and M. L. Brodie, editors, Morgan Kaufmann Publishers, Inc., 1988.

USGIF's Machine Learning and Artificial Intelligence Workshop will bring together a diverse group of individuals from government, industry, and academia to discuss current challenges and strategic initiatives related to the role of artificial intelligence, machine learning, cognitive computing, and deep learning in geospatial intelligence. We will be joined by today's visionary leaders in AI to explore this rapidly evolving and disruptive technology. Dr. C. Lee Giles, David Reese Professor of Information Sciences and Technology, and Interim Associate Dean of Research, Penn State University (invited) Dr. Nathan Jacobs, Associate Professor, Department of Computer Science, University of Kentucky Dr. Zsolt Kira, Branch Chief, Machine Learning and Analytics, Georgia Tech Research Institute Dr. Stella Yu, Director, Vision Group at the International Computer Science Institute, UC Berkeley Dr. C. Lee Giles, David Reese Professor of Information Sciences and Technology, and Interim Associate Dean of Research, Penn State University (invited)

This text analyses the papers accepted for the workshop "Reuse of designs: an interdisciplinary cognitive approach". Several dimensions and questions considered as important (by the authors and/or by us) are addressed: What about the "interdisciplinary cognitive" character of the approaches adopted by the authors? Is design indeed a domain where the use of CBR is particularly suitable? Are there important distinctions between CBR and other approaches? Which types of knowledge -other than cases- is being, or might be, used in CBR systems? With respect to cases: are there different "types" of case and different types of case use? which formats are adopted for their representation? do cases have "components"? how are cases organised in the case memory? Concerning their retrieval: which types of index are used? on which types of relation is retrieval based? how does one retrieve only a selected number of cases, i.e., how does one retrieve only the "best" cases? which processes and strategies are used, by the system and by its user? Finally, some important aspects of CBR system development are shortly discussed: should CBR systems be assistance or autonomous systems? how can case knowledge be "acquired"? what about the empirical evaluation of CBR systems? The conclusion points out some lacking points: not much attention is paid to the user, and few papers have indeed adopted an interdisciplinary cognitive approach.