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AI At Your Service
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"What the field of AI is really about is inventing machines that will help people in a variety of ways, by giving machines some of the sophisticated capabilities that humans have, such as the ability to understand spoken words, or interpret images, or to learn from experience. Usually these machines do not look or act at all like people, but they can be amazingly useful to people by improving and assisting our lives, and complementing rather than replacing the things that we humans like to do. And that's the goal we are collectively working toward." |
Index of Application Domains, Tasks and Technologies
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Advisory Aeromedical Evacuation Planning & Execution Application Names Case Adaptation Concepts Constraint Satisfaction Construction Content personalization Continuity-Guided Regeneration Financial Services Frames Fraud Detection | Government Laws/Regulation
Insurance Application Processing Internet-based TV Listings Knowledge Engineering Microopportunistic Search Natural Language Processing Neural Networks Ontologies Optical Character Recognition Planning Risk Assessment Rules Rule Learning Transportation Planning User Profile Acquisition |
| Application: Falcon Fraud Manager Deploying Organization: HNC Software Location: San Diego, CA Name(s) of Developers Current Version Date of Deployment (mo/yr) Application Domain: Financial Services Application Subdomain Type of Task: Fraud Detection Description of Task: Examine transaction, cardholder and merchant data to detect a wide range of credit and debit card fraud. Target Users: Payment card issuing financial institutions. URL for information: http://www.hnc.com/hnc/business_03/industries_03/fs_03/fin04.html Contact Name: Melinda Bateman Contact Phone: (858) 799-8370 Contact Address: 5935 Cornerstone Court West, San Diego, CA 92121 Cost of Development Cost of Deployment Key Technologies Employed: Neural Networks Key Qualitative Results Key Quantitative Results: Improved fraud detection rates by 30-70% while significantly lowering the rate of false-positives. Value Added ($/yr or other) Performance Statistics Keywords XML or standard ontology tags Date of Entry: 10/2/01 Last Updated | |
| Application: OSHA Expert Advisors Deploying Organization: U.S. Department of Labor, OSHA Location: Washington, DC Name(s) of Developers Current Version Date of Deployment (mo/yr) Application Domain: Government Laws/Regulations Application Subdomain Type of Task: Advisory Description of Task: Provide help to identify fire and other safety hazards in a given workplace and gives specific information on how OSHA regulations apply to a particular work site. Target Users: Small businesses URL for information: http://www.osha-slc.gov/dts/osta/oshasoft/osha-advisors.html >> 2007 update: http://www.osha.gov/dts/osta/oshasoft/index.html#eTools Contact Name Contact Phone Contact Address: OSHA, Directorate of Health Standards Programs, U.S. Department of Labor, 200 Constitution Avenue, N.W., Washington, D.C. 20210 Cost of Development: $100,000 / expert program Cost of Deployment Key Technologies Employed: Expert rules Key Qualitative Results Key Quantitative Results Value Added ($/yr or other) Performance Statistics Keywords XML or standard ontology tags Date of Entry: 10/08/01 Last Updated | |
| Application: FineReader Deploying Organization: ABBYY Software House Location: Moscow, Russia Name(s) of Developers Current Version: 5 Date of Deployment (mo/yr): Nov-00 Application Domain: Natural Language Processing Application Subdomain Type of Task: Optical Character Recognition Description of Task: Convert data scanned from paper documents (such as fax, printer, typewriter, or photocopy outputs) into editable electronic forms. Target Users URL for information: http://www.abbyyusa.com/ Contact Name Contact Phone: (510) 226-6717 Contact Address: ABBYY USA, 46560 Fremont Blvd, Suite 105, Fremont, CA 94538 Cost of Development Cost of Deployment Key Technologies Employed: Frames; something they call IPA technology (Integral Purposeful Adaptive perceptron). See Reviewer's Comment below. Key Qualitative Results Key Quantitative Results Value Added ($/yr or other) Performance Statistics Keywords XML or standard ontology tags Date of Entry: 10/25/01 Last Updated Reviewer's Comment: I think from their description, this is some kind of learning system, based on learning and training perceptrons for recognition of heterogeneous objects, that might be represented as frames; currently tracking down articles. | |
| Application: TRAC2ES (TRANSCOM regulating and command and control evacuation system) Deploying Organization: U.S. Transportation Command (TRANSCOM) Location Name(s) of Developers: Members of TRAC2ES project at Logica Carnegie Group Current Version Date of Deployment (mo/yr): 4QFY01 Application Domain: Transportation Planning Application Subdomain: Dynamic Replanning Type of Task: Aeromedical evacuation planning and execution Description of Task: Provide decision support for planning and scheduling medical evacuation operations globally by air to suitable medical treatment facilities. Target Users: Military and non-military hospital personel, transportation personel, staff at centers who plan and monitor patient movents. URLs for information: http://www.dote.osd.mil/reports/FY00/airforce/00trac2es.html, http://www.transcom.mil/J6/j6o/j6_oi/pubs/p41-1.pdf Contact Name Contact Phone:(618) 256-2895 Contact Address: USTRANSCOM/TCSG, 508 Scott Drive, Scott AFB, Illinois, 62225-5357 Cost of Development: over $163 million Cost of Deployment Key Technologies Employed: Continuity-guided regeneration (CGR), microopportunistic serach Key Qualitative Results: Improved communication of patient movements and movement requests; gave users the ability to quickly and easily create solutions to problems caused by disruptive events. Key Quantitative Results Value Added ($/yr or other) Performance Statistics Keywords XML or standard ontology tags Date of Entry: 10/25/01 Last Updated | |
| Application: DISXPERT Deploying Organization: New York State Department of Social Services Office of Disability Determination Location: New York State Name(s) of Developers: James R. Nolan Current Version Date of Deployment (mo/yr): 1992 Application Domain: Social Security Disability Screening & Referral Application Subdomain: Risk Assessment Type of Task: Case review and assessment Description of Task: Provide support for making unbiased and consistent assessment decision regarding referral of clients to vocational rehabilitation services Target Users: paraprofessional caseworkers URL for information Contact Name Contact Phone Contact Address Cost of Development: $60,000 Cost of Deployment: $30,000 Key Technologies Employed: Expert rules Key Qualitative Results: Increased productivity and reimbursement of SSA funds; decrease in referred client dropout rate Key Quantitative Results: Case assessment increased by 70,000/year; dropout rate declined over 80% Value Added ($/yr or other) Performance Statistics Keywords XML or standard ontology tags: expert systems, knowledge engineering, rule learning Date of Entry: 11/26/01 Last Updated | |
| Application: MITA Deploying Organization: MetLife Location: New York, NY Name(s) of Developers: Barry Glasgow, Alan Mandell, Dan Binney, Lila Ghemri, David Fisher, and developers from Brightware Current Version Date of Deployment (mo/yr): Jun-97 Application Domain: Insurance Application Processing Application Subdomain: Automatic underwriting review Type of Task: free-form textual field analysis Description of Task: Extract significant medical and occupational concepts from free-form textual fields on life insurance applications to help automate the underwriting review process Target Users: insurers URL for information Contact Name Contact Phone Contact Address Cost of Development Cost of Deployment Key Technologies Employed: Information extraction, Pattern matching Key Qualitative Results: Reduction in underwriting time; greater underwriting consistency Key Quantitative Results: 89% of textual fields successfully analyzed Value Added ($/yr or other) Performance Statistics Keywords XML or standard ontology tags: natural language processing, concepts, ontologies, rules, knowledge engineering Date of Entry: 11/26/01 Last Updated | |
| Application: PTV Deploying Organization Location Name(s) of Developers: Barry Smyth and Paul Cotter Current Version: PTVPlus Date of Deployment (mo/yr): Jan-99 Application Domain: Internet-based TV Listings Application Subdomain: Content personalization Type of Task: personalize TV listings Description of Task: Automatically learn individual users' TV viewing preferences and provide them with customized and personalized daily TV program guides Target Users: television viewers with PC or mobile wireless web access URL for information: http://www.ptvplus.com/ Contact Name: James Ryan Contact Phone Contact Address: james.ryan@changingworlds.com Cost of Development Cost of Deployment Key Technologies Employed: case-based reasoning, collaborative recommendation Key Qualitative Results Key Quantitative Results: End-User evaluation: 99% said easy to use for TV listing; 88% said acceptable response time; 3% said poor personalization quality Value Added ($/yr or other) Performance Statistics Keywords XML or standard ontology tags: user profile acquisition Date of Entry: 11/26/01 Last Updated | |
| Application: FASTRAK-APT Deploying Organization: Hyundai Engineering and Construction Location: Korea Name(s) of Developers: Kyoung Jun Lee, Hyun Woo Kim, Jae Kyu Lee (KAIST), and Tae Hwan Kim Current Version Date of Deployment (mo/yr): 1996 Application Domain: Apartment Construction Application Subdomain: Project planning and management Type of Task: apartment construction planning Description of Task: Develop apartment construction plans by identifying similar cases from a knowledge base, and modifying the most similar case to reflect the specifications and constraints of the new construction project Target Users: construction project managers URL for information Contact Name Contact Phone Contact Address Cost of Development: $621,000 Cost of Deployment Key Technologies Employed: case-based reasoning, mixed-initiative planning Key Qualitative Results: Reduction in initial planning time and effort, improved quality and completeness of construction plans Key Quantitative Results: Initial project planning reduced from 7 person-days to 1 person-day, plan updating and modification reduced from 2 person-days to 0.5 person-days Value Added ($/yr or other): $616,000/year Performance Statistics Keywords XML or standard ontology tags: expert systems, planning, frames, constraint satisfaction, case adaptation Date of Entry: 11/28/01 Last Updated | |
| Application Deploying Organization Location Name(s) of Developers Current Version Date of Deployment (mo/yr) Application Domain Application Subdomain Type of Task Description of Task Target Users URL for information Contact Name Contact Phone Contact Address Cost of Development Cost of Deployment Key Technologies Employed Key Qualitative Results Key Quantitative Results Value Added ($/yr or other) Performance Statistics Keywords XML or standard ontology tags Date of Entry Last Updated | |
| Application Deploying Organization Location Name(s) of Developers Current Version Date of Deployment (mo/yr) Application Domain Application Subdomain Type of Task Description of Task Target Users URL for information Contact Name Contact Phone Contact Address Cost of Development Cost of Deployment Key Technologies Employed Key Qualitative Results Key Quantitative Results Value Added ($/yr or other) Performance Statistics Keywords XML or standard ontology tags Date of Entry Last Updated | |
| Application Deploying Organization Location Name(s) of Developers Current Version Date of Deployment (mo/yr) Application Domain Application Subdomain Type of Task Description of Task Target Users URL for information Contact Name Contact Phone Contact Address Cost of Development Cost of Deployment Key Technologies Employed Key Qualitative Results Key Quantitative Results Value Added ($/yr or other) Performance Statistics Keywords XML or standard ontology tags Date of Entry Last Updated | |
| Application Deploying Organization Location Name(s) of Developers Current Version Date of Deployment (mo/yr) Application Domain Application Subdomain Type of Task Description of Task Target Users URL for information Contact Name Contact Phone Contact Address Cost of Development Cost of Deployment Key Technologies Employed Key Qualitative Results Key Quantitative Results Value Added ($/yr or other) Performance Statistics Keywords XML or standard ontology tags Date of Entry Last Updated | |
| Application Deploying Organization Location Name(s) of Developers Current Version Date of Deployment (mo/yr) Application Domain Application Subdomain Type of Task Description of Task Target Users URL for information Contact Name Contact Phone Contact Address Cost of Development Cost of Deployment Key Technologies Employed Key Qualitative Results Key Quantitative Results Value Added ($/yr or other) Performance Statistics Keywords XML or standard ontology tags Date of Entry Last Updated | |
| Application Deploying Organization Location Name(s) of Developers Current Version Date of Deployment (mo/yr) Application Domain Application Subdomain Type of Task Description of Task Target Users URL for information Contact Name Contact Phone Contact Address Cost of Development Cost of Deployment Key Technologies Employed Key Qualitative Results Key Quantitative Results Value Added ($/yr or other) Performance Statistics Keywords XML or standard ontology tags Date of Entry Last Updated | |
Template for Embedded AI
Application
Deploying Organization
Location
Name(s) of Developers
Current Version
Date of Deployment (mo/yr)
Application Domain
Application Subdomain
Type of Task
Description of Task
Target Users
URL for information
Contact Name
Contact Phone
Contact Address
Cost of Development
Cost of Deployment
Key Technologies Employed
Key Qualitative Results
Key Quantitative Results
Value Added ($/yr or other)
Performance Statistics
Keywords XML or standard ontology tags
Date of Entry
Last Updated