If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
ODSC East 2018 is one of the largest applied data science conferences in the world. Our speakers include some of the core contributors to many open source tools, libraries, and languages. Attend ODSC East 2018 and learn the latest AI & data science topics, tools, and languages from some of the best and brightest minds in the field. See schedule for many more.. The largest applied data science conference is now 4 days including 2 full training days for even more talks, trainings, and workshops vested in 8 focused courses.
Google's AI chief isn't fretting about super-intelligent killer robots. Instead, John Giannandrea is concerned about the danger that may be lurking inside the machine-learning algorithms used to make millions of decisions every minute. "The real safety question, if you want to call it that, is that if we give these systems biased data, they will be biased," Giannandrea said before a recent Google conference on the relationship between humans and AI systems. The problem of bias in machine learning is likely to become more significant as the technology spreads to critical areas like medicine and law, and as more people without a deep technical understanding are tasked with deploying it. Some experts warn that algorithmic bias is already pervasive in many industries, and that almost no one is making an effort to identify or correct it (see "Biased Algorithms Are Everywhere, and No One Seems to Care").
This new conference series promotes multidisciplinary research on tools and methodologies for efficiently capturing knowledge from a variety of sources and creating representations that can be (or eventually can be) useful for reasoning. The conference attracted researchers from diverse areas of AI, including knowledge representation, knowledge acquisition, intelligent user interfaces, problem solving and reasoning, planning, agents, text extraction, and machine learning. Knowledge acquisition has been a challenging area of research in AI, with its roots in early work to develop expert systems. Driven by the modern internet culture and knowledge-based industries, the study of knowledge capture has a renewed importance. Although there has been considerable work over the years in the area, activities have been distributed across several distinct research communities.
The welcome was given by University of Pittsburgh President Wesley Posvar. The conference cochairmen, Stellan Ohlsson and Jeff Bonar, also gave brief welcomes to the participants. The relatively small size of the conference, about 425 participants, was undoubtedly in part responsible for the congenial ambiance of the meeting. In addition to the opportunity to reunite with old friends, it was easy to establish new relationships with nearly everyone at the conference. With so many attendees from abroad (The Netherlands, Japan, Canada, West Germany, England, Sweden, France, and Hong Kong were all represented by speakers), the international flavor of the conference was well established.
This article presents a report of the conference. For example, such technology can lead to design of environments that are more secure, productive, caring, entertaining, or energy efficient. The development of intelligent environments is considered the first and primary step toward the realization of the ambient intelligence vision and requires input from research and contributions from several scientific and engineering disciplines, including computer science, software engineering, artificial intelligence, architecture, social sciences, art, and design. IE conferences create a unique blend of researchers in these disciplines and foster crossdisciplinary discussions, debate, and collaborations. The Sixth International Conference on Intelligent Environments (IE 10) was held July 19-21 at the Sunway campus of Monash University, Kuala Lumpur, Malaysia.
This article discusses the Thirteenth International Distributed AI Workshop. An overview of the workshop is given as well as concerns and goals for the technology. The central problem in DAI is how to achieve coordinated action among such agents, so that they can accomplish more as a group than as individuals. The DAI workshop is dedicated to advancing the state of the art in this field. This year's workshop took place on the Olympic Peninsula in Washington State on 28 to 30 July 1994 and included 45 participants from North America, Europe, and the Pacific Rim.
There's More to Life Than Making Plans For many years, research in AI plan generation was governed by a number of strong, simplifying assumptions: The planning agent is omniscient, its actions are deterministic and instantaneous, its goals are fixed and categorical, and its environment is static. More recently, researchers have developed expanded planning algorithms that are not predicated on such assumptions, but changing the way in which plans are formed is only part of what is required when the classical assumptions are abandoned. The demands of dynamic, uncertain environments mean that in addition to being able to form plans--even probabilistic, uncertain plans--agents must be able to effectively manage their plans. In this article, which is based on a talk given at the 1998 AAAI Fall Symposium on Distributed, Continual Planning, we first identify reasoning tasks that are involved in plan management, including commitment management, environment monitoring, alternative assessment, plan elaboration, metalevel control, and coordination with other agents. We next survey approaches we have developed to many of these tasks and discuss a plan-management system we are building to ground our theoretical work, by providing us with a platform for integrating our techniques and exploring their value in a realistic problem.
Computer Scaence Department Yale University THE COGNITION AND PROGRAMMING PROJECT (CAPP) in the Computer Science Department at Yale University is an interdisciplinary group exploring a wide range of issues in programming. 'This project is currently being funded by NSF RISE, under grant number SED-81-12403 'This project is currently being funded by NSF IST, under grant number IST-81-14840 We have also shown that when the language construct, agrees with people's natural problem solving strategies they can learn to use such constructs effectively. The implication is that language dcsigners should be more sensitive to cognitive capabilities which people bring to programming and that computing educators should be aware of the systematic misconceptions which arise due to cognztively poor programming language constructs. Using our theory of programming plans, we are developing measures of program complexity that are based on the underlying mental effort needed to understand programs. This approach is in contrast to typical measures of program complexity which are sensitive to only surface features of programs.
The workshop was organized by Jack Minker and John McCarthy. The Program Committee members were Krzysztof Apt, John Horty, Sarit Kraus, Vladimir Lifschitz, John McCarthy, Jack Minker, Don Perlis, and Ray Reiter. The purpose of the workshop was to bring together researchers who use logic as a fundamental tool in AI to permit them to review accomplishments, assess future directions, and share their research in LBAI. This article is a summary of the workshop. The areas selected for discussion at the workshop were abductive and inductive reasoning, applications of theorem proving, commonsense reasoning, computational logic, constraints, logic and high-level robotics, logic and language, logic and planning, logic for agents and actions, logic of causation and action, logic, probability and decision theory, nonmonotonic reasoning, theories of belief, and knowledge representation.
The Sixth International Conference on Enterprise Information Systems (ICEIS) was held in Porto, Portugal; previous venues were in Spain, France, and the United Kingdom. Since its inception in 1999, ICEIS has grown steadily, and is now one of the largest international conferences in the area of information systems. In 2004, more than 600 papers were submitted to the conference and its ten satellite workshops. One of the interesting features of this conference is the high number of invited speakers. In 2004, eighteen keynote speakers were featured at ICEIS and its workshops.