START, the world's first Web-based question answering system, has been on-line and continuously operating since December, 1993. It has been developed by Boris Katz and his associates of the InfoLab Group at the MIT Computer Science and Artificial Intelligence Laboratory. Unlike information retrieval systems (e.g., search engines), START aims to supply users with "just the right information," instead of merely providing a list of hits. Currently, the system can answer millions of English questions about places (e.g., cities, countries, lakes, coordinates, weather, maps, demographics, political and economic systems), movies (e.g., titles, actors, directors), people (e.g., birth dates, biographies), dictionary definitions, and much, much more. Below is a list of some of the things START knows about, with example questions. You can type your question above or select from the following examples.
"The Artificial Intelligence (AI) program at the University of Michigan comprises a multidisciplinary group of researchers conducting
theoretical, experimental, and applied investigations of intelligent systems. Current projects include research in rational decision
making, computational game theory, distributed systems of multiple agents, reinforcement learning, machine learning, cognitive modeling,
natural language processing, information retrieval, and robotics."
The Artificial Intelligence (AI) program at the University of Michigan comprises a multidisciplinary group of researchers conducting
theoretical, experimental, and applied investigations of intelligent systems. Current projects include research in rational decision
making, computational game theory, distributed systems of multiple agents, reinforcement learning, machine learning, cognitive modeling,
natural language processing, information retrieval, and robotics.
The modern definition of artificial intelligence (or AI) is "the study and design of intelligent agents" where an intelligent agent is a system that perceives its environment and takes actions which maximizes its chances of success.[1] John McCarthy, who coined the term in 1956,[2] defines it as "the science and engineering of making intelligent machines."[3] Other names for the field have been proposed, such as computational intelligence,[4] synthetic intelligence[4][5] or computational rationality.[6] The term artificial intelligence is also used to describe a property of machines or programs: the intelligence that the system demonstrates.
The DARPA PAL program (the Personalized Assistant that Learns) focused on improving the way that computers support humans through the use of cognitive systems-that is, systems that reason, learn from experience, and accept guidance in order to provide effective, personalized assistance.
SRI International has led the PAL Framework effort to make available many of the successful machine learning and reasoning technologies developed on the PAL program for use by the broader DARPA, research, and military communities. Technical capabilities within the framework have been hardened, modularized, packaged, and where appropriate, adapted to meet industry standards to facilitate their incorporation into potential target applications. The framework further includes various infrastructure components and APIs to simplify integration with the framework technologies.
Therefore, the HBP's first goal is to build an integrated system of six ICT-based research platforms, providing neuroscientists, medical researchers and technology developers with access to highly innovative tools and services that can radically accelerate the pace of their research.
An artificial neural network (ANN), usually called neural network (NN), is a mathematical model or computational model that is inspired by the structure and/or functional aspects of biological neural networks. A neural network consists of an interconnected group of artificial neurons, and it processes information using a connectionist approach to computation. In most cases an ANN is an adaptive system that changes its structure based on external or internal information that flows through the network during the learning phase.
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"Vicarious is developing machine learning software based on the computational principles of the human brain. Our first technology is a visual perception system that interprets the contents of photographs and videos in a manner similar to humans. Powering this technology is a new computational paradigm we call the Recursive Cortical Network ™"
"Loom is a language and environment for constructing intelligent applications. The heart of Loom is a knowledge representation system that is used to provide deductive support for the declarative portion of the Loom language. Declarative knowledge in Loom consists of definitions, rules, facts, and default rules. A deductive engine called a classifier utilizes forward-chaining, semantic unification and object-oriented truth maintainance technologies in order to compile the declarative knowledge into a network designed to efficiently support on-line deductive query processing."
The Artificial Intelligence Group at UCSD engages in a wide range of theoretical and experimental research. Areas of particular strength include machine learning, probabilistic inference, neural computation, and cognitive modeling. Within these areas, students and faculty also pursue real-world applications to problems in computer vision, speech and audio processing, information retrieval, bioinformatics, brain-computer interfaces, and computer systems and networking. The Artificial Intelligence Group is part of a larger campus-wide effort in Computational Statistics and Machine Learning (COSMAL). Interdisciplinary collaborations are strongly supported and encouraged.
Artificial intelligence (AI) is the intelligence of machines and the branch of computer science that aims to create it. AI textbooks define the field as "the study and design of intelligent agents"[1] where an intelligent agent is a system that perceives its environment and takes actions that maximize its chances of success.[2] John McCarthy, who coined the term in 1956,[3] defines it as "the science and engineering of making intelligent machines."[4]
The Automated Mathematician (AM) is one of the earliest successful discovery systems. It was created by Doug Lenat in Lisp, and in 1977 led to Lenat being awarded the IJCAI Computers and Thought Award.
AM worked by generating and modifying short Lisp programs which were t