Competitive analysis is a critical part of any business. Product managers, sellers, and marketers spend time and resources scouring through an immense amount of online and offline content, aiming to discover what their competitors are doing in the marketplace to understand what type of threat they pose to their business' financial well-being. Currently, this process is time and labor-intensive, slow and costly. This paper presents Clarity, a data-driven unsupervised system for assessment of products, which is currently in deployment in the global technology company, IBM. Clarity has been running for more than a year and is used by over 4,500 people to perform over 200 competitive analyses involving over 1000 products.

The Health and Human Services Department's Program Support Center on Jan. 10 released a request for proposals for an artificial intelligence multiple-award contract. It's another piece of evidence that the agency has prioritized AI and is likely to spend more on the emerging technology in the next few years. None of HHS's information technology strategies mention artificial intelligence. Yet the way the agency is spending money and planning to obligate future funds tells another story. HHS plans to use automation, machine learning, supervised learning, and machine vision to reduce backlogs, predict fraudulent transactions, identify suspects through facial recognition, and more.

This article is a reflection on the goals and focus of the Innovative Applications of Artificial Intelligence (IAAI) Conference. The author begins with an historical review of the conference. He then goes on to discuss the role of the IAAI conference, including an examination of the relationship between AI scientific research and the application of AI technology. He concludes with a presentation of the new vision for the IAAI conference. Over the past eight years, this conference has undergone modest evolution, but a significant transformation is being planned for the next meeting.

IAAI has been held annually since 1989 and has been collocated with the national (or international) AI conference since 1991. The proceedings were published in book form through 1992. Since 1993, a conference proceedings volume has been published, and selected papers have been republished as articles in AI Magazine. This introduction briefly discusses the 1995 IAAI award winners and presents goals and plans for next year's conference. IAAI features real, deployed AI applications, selected for their innovation.

Horvitz noted two emerging trends at the conference and in the AI field. First is the growing interest in the web as a source of both structured and unstructured knowledge. For example, not only was there a special track on AI and the web, but during the robot competition, robots accessed the web to gather information about the objects they were to find in the scavenger huntlike event. Second is the work in scaling AI to be more integrative. Instead of the ongoing great successes of AI researches on "wedges" of AI expertise and reasoning, there's increasing work on delivering more depth and breadth of capabilities such as sensing, learning, and reasoning.

This meeting represented the most significant transformation in the history of IAAI. IAAI-97 consisted of two paper tracks as well as invited talks and panels. The first paper track, Deployed-Application Case Studies, comprised papers about deployed AI systems that are relied on for operations and have clearly defined business value. This track was equivalent to previous IAAI programs. The deployed applications track's standards for innovation recognize four types: (1) first application of an AI technique in a deployed application, (2) application of an AI technique to a new domain, (3) a high business payoff, and (4) a novel integration of techniques.

This special issue of AI Magazine covers select applications from the IAAI conference held in 2008 in Chicago. The articles address a broad range of very challenging issues and contain great lessons for AI researchers and application developers. Your rice cooker, toaster, and washing machine have their own minds. Your car parks itself; its transmission adapts itself to your driving preferences, and it tells the dealership which parts it thinks it will need to have replaced three months from now. Your PDA knows your preferences and acts as your personal radio station, playing only music you like.

In this and the next issue of AI Magazine, we will present extended versions of papers presented at IAAI-12 (held in Toronto, Ontario, Canada) that were selected for their description of AI technologies that are either in practical use or close to it. We also present an article by Ramon Lopez de Mantaras based on his 2011 Robert S. Engelmore Memorial Lecture. Our selections for this issue begin with Playing with Cases: Rendering Expressive Music with Case-Based Reasoning by Ramon Lopez de Mantaras and Josep Lluís Arcos, based on the Robert S. Engelmore Memorial Lecture at IAAI-11 in San Francisco, California. Lopez de Mantaras received the Robert S. Engelmore Memorial Lecture Award for his pioneering research contributions in a breadth of artificial intelligence areas, especially pattern recognition and case-based reasoning, leading to novel applications in design, diagnosis, and music, and for extensive international leadership and service for the AI community. He is also a founding member of several AI companies.

As in past years, papers were solicited in two categories: (1) deployed applications and (2) emerging applications and technologies. Deployed application papers describe systems that have been in use for at least several months by individuals or organizations other than their developers, have measurable benefits, and incorporate AI technologies. Emerging applications are technologies and systems that are close to deployment and clearly show an innovative implementation of AI technologies. These papers are of value not only to other application developers looking for guidance in applying various techniques to their own applications but also to researchers who need to understand the unique technical challenges provided by real-world problems. For IAAI-2002, we received 54 submissions, containing a wealth of outstanding applications and emerging technology papers (15 deployed and 39 emerging).

In this issue of AI Magazine, we continue our presentation of extended versions of papers presented at IAAI-12 (held in Toronto, Ontario, Canada) that were selected for their description of AI technologies that are in practical use. Our selections for this issue describe deployed applications. They explain the context, requirements, and constraints of the application, how the technology was adapted to satisfy those factors, and the impact that this innovation brought to the operation in terms of cost and performance. The articles also supply useful insights into use cases that we hope can also be translated to other work that the AI community is engaged in. In the first of these deployed application articles, eBird: A Human/Computer Learning Network to Improve Biodiversity Conservation and Research by Steve Kelling, Carl Lagoze, Weng-Keen Wong, Jun Yu, Theodoros Damoulas, Jeff Gerbracht, Daniel Fink, and Carla Gomes, the authors describe an intriguing application that successfully combines the best in human and artificial computing capabilities with an active feedback loop between people and machines.