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Michael Witbrock | |
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Born | Michael John Witbrock Christchurch, New Zealand |
Alma mater | Carnegie Mellon University |
Known for | Cycorp, Cyc, Common Lisp, ObjectStore |
Scientific career | |
Fields | Computer science |
Michael John Witbrock is a computer scientist in the field of artificial intelligence. Witbrock is a native of New Zealand and is the former vice president of Research at Cycorp, which is carrying out the Cyc project in an effort to produce a genuine artificial intelligence.
Witbrock was born in Christchurch, New Zealand, and has a Ph.D. in computer science from Carnegie Mellon University. Before joining Cycorp, he was a principal scientist at Terra Lycos, working on integrating statistical and knowledge-based approaches to understanding Web user behavior; he has also been associated with Just Systems Pittsburgh Research Center and the Informedia Digital Library at Carnegie Mellon.
In 2016, Witbrock joined and led the Reasoning Lab at IBM Watson. [1]
In 2019, Witbrock was recruited by the government and returned to his home country to establish and lead AI research initiatives in New Zealand [2]
Witbrock's dissertation work was on speaker modeling; before going to Cycorp, he published in a broad range of areas, including:
His work at Cycorp has focused on improving its knowledge formation efforts, particularly dialogue processing, machine reasoning, and on improving accessibility to the Cyc project.
At the University of Auckland, Witbrock's research spans natural language processing, multi-hop reasoning, causal inference, graph neural networks, focusing on advancing AI's interpretability, robustness, and real-world applications. [3]
Together with John Mount, Witbrock is credited [4] with genetic art, a kind of Computer-generated art.
Cyc is a long-term artificial intelligence project that aims to assemble a comprehensive ontology and knowledge base that spans the basic concepts and rules about how the world works. Hoping to capture common sense knowledge, Cyc focuses on implicit knowledge. The project began in July 1984 at MCC and was developed later by the Cycorp company.
Planner is a programming language designed by Carl Hewitt at MIT, and first published in 1969. First, subsets such as Micro-Planner and Pico-Planner were implemented, and then essentially the whole language was implemented as Popler by Julian Davies at the University of Edinburgh in the POP-2 programming language. Derivations such as QA4, Conniver, QLISP and Ether were important tools in artificial intelligence research in the 1970s, which influenced commercial developments such as Knowledge Engineering Environment (KEE) and Automated Reasoning Tool (ART).
Douglas Bruce Lenat was an American computer scientist and researcher in artificial intelligence who was the founder and CEO of Cycorp, Inc. in Austin, Texas.
In artificial intelligence, symbolic artificial intelligence is the term for the collection of all methods in artificial intelligence research that are based on high-level symbolic (human-readable) representations of problems, logic and search. Symbolic AI used tools such as logic programming, production rules, semantic nets and frames, and it developed applications such as knowledge-based systems, symbolic mathematics, automated theorem provers, ontologies, the semantic web, and automated planning and scheduling systems. The Symbolic AI paradigm led to seminal ideas in search, symbolic programming languages, agents, multi-agent systems, the semantic web, and the strengths and limitations of formal knowledge and reasoning systems.
The Informedia Digital Library is an ongoing research program at Carnegie Mellon University to build search engines and information visualization technology for many types of media.
Soar is a cognitive architecture, originally created by John Laird, Allen Newell, and Paul Rosenbloom at Carnegie Mellon University.
Bart Selman is a Dutch-American professor of computer science at Cornell University. He is also co-founder and principal investigator of the Center for Human-Compatible Artificial Intelligence (CHAI) at the University of California, Berkeley, led by Stuart J. Russell, and co-chair of the Computing Community Consortium's 20-year roadmap for AI research.
Legal informatics is an area within information science.
Patrick John Hayes is a British computer scientist who lives and works in the United States. He is a Senior Research Scientist Emeritus at the Institute for Human and Machine Cognition (IHMC) in Pensacola, Florida.
Game Description Language (GDL) is a specialized logic programming language designed by Michael Genesereth. The goal of GDL is to allow the development of AI agents capable of general game playing. It is part of the General Game Playing Project at Stanford University.
Jaime Guillermo Carbonell was a computer scientist who made seminal contributions to the development of natural language processing tools and technologies. His extensive research in machine translation resulted in the development of several state-of-the-art language translation and artificial intelligence systems. He earned his B.S. degrees in Physics and in Mathematics from MIT in 1975 and did his Ph.D. under Dr. Roger Schank at Yale University in 1979. He joined Carnegie Mellon University as an assistant professor of computer science in 1979 and lived in Pittsburgh from then. He was affiliated with the Language Technologies Institute, Computer Science Department, Machine Learning Department, and Computational Biology Department at Carnegie Mellon.
Eric Joel Horvitz is an American computer scientist, and Technical Fellow at Microsoft, where he serves as the company's first Chief Scientific Officer. He was previously the director of Microsoft Research Labs, including research centers in Redmond, WA, Cambridge, MA, New York, NY, Montreal, Canada, Cambridge, UK, and Bangalore, India.
The Winograd schema challenge (WSC) is a test of machine intelligence proposed in 2012 by Hector Levesque, a computer scientist at the University of Toronto. Designed to be an improvement on the Turing test, it is a multiple-choice test that employs questions of a very specific structure: they are instances of what are called Winograd schemas, named after Terry Winograd, professor of computer science at Stanford University.
Eric Poe Xing is an American computer scientist whose research spans machine learning, computational biology, and statistical methodology. Xing is founding President of the world’s first artificial intelligence university, Mohamed bin Zayed University of Artificial Intelligence (MBZUAI).
Francesca Rossi is an Italian computer scientist, currently working at the IBM Thomas J. Watson Research Center as an IBM Fellow and the IBM AI Ethics Global Leader.
This glossary of artificial intelligence is a list of definitions of terms and concepts relevant to the study of artificial intelligence (AI), its subdisciplines, and related fields. Related glossaries include Glossary of computer science, Glossary of robotics, and Glossary of machine vision.
Explainable AI (XAI), often overlapping with interpretable AI, or explainable machine learning (XML), is a field of research within artificial intelligence (AI) that explores methods that provide humans with the ability of intellectual oversight over AI algorithms. The main focus is on the reasoning behind the decisions or predictions made by the AI algorithms, to make them more understandable and transparent. This addresses users' requirement to assess safety and scrutinize the automated decision making in applications. XAI counters the "black box" tendency of machine learning, where even the AI's designers cannot explain why it arrived at a specific decision.
Neuro-symbolic AI is a type of artificial intelligence that integrates neural and symbolic AI architectures to address the weaknesses of each, providing a robust AI capable of reasoning, learning, and cognitive modeling. As argued by Leslie Valiant and others, the effective construction of rich computational cognitive models demands the combination of symbolic reasoning and efficient machine learning. Gary Marcus argued, "We cannot construct rich cognitive models in an adequate, automated way without the triumvirate of hybrid architecture, rich prior knowledge, and sophisticated techniques for reasoning." Further, "To build a robust, knowledge-driven approach to AI we must have the machinery of symbol manipulation in our toolkit. Too much useful knowledge is abstract to proceed without tools that represent and manipulate abstraction, and to date, the only known machinery that can manipulate such abstract knowledge reliably is the apparatus of symbol manipulation."
Thomas L. Dean is an American computer scientist known for his work in robot planning, probabilistic graphical models, and computational neuroscience. He was one of the first to introduce ideas from operations research and control theory to artificial intelligence. In particular, he introduced the idea of the anytime algorithm and was the first to apply the factored Markov decision process to robotics. He has authored several influential textbooks on artificial intelligence.