The technological singularity—or simply the singularity—is a hypothetical future point in time at which technological growth becomes uncontrollable and irreversible, resulting in unforeseeable consequences for human civilization. According to the most popular version of the singularity hypothesis, I. J. Good's intelligence explosion model of 1965, an upgradable intelligent agent could eventually enter a positive feedback loop of self-improvement cycles, each successive; and more intelligent generation appearing more and more rapidly, causing a rapid increase ("explosion") in intelligence which would ultimately result in a powerful superintelligence, qualitatively far surpassing all human intelligence.
A Bayesian network is a probabilistic graphical model that represents a set of variables and their conditional dependencies via a directed acyclic graph (DAG). While it is one of several forms of causal notation, causal networks are special cases of Bayesian networks. Bayesian networks are ideal for taking an event that occurred and predicting the likelihood that any one of several possible known causes was the contributing factor. For example, a Bayesian network could represent the probabilistic relationships between diseases and symptoms. Given symptoms, the network can be used to compute the probabilities of the presence of various diseases.
Artificial general intelligence (AGI) is a type of artificial intelligence (AI) that matches or surpasses human cognitive capabilities across a wide range of cognitive tasks. This contrasts with narrow AI, which is limited to specific tasks. Artificial superintelligence (ASI), on the other hand, refers to AGI that greatly exceeds human cognitive capabilities. AGI is considered one of the definitions of strong AI.
Bill Hibbard is a scientist at the University of Wisconsin–Madison Space Science and Engineering Center working on visualization and machine intelligence. He is principal author of the Vis5D, Cave5D, and VisAD open-source visualization systems. Vis5D was the first system to produce fully interactive animated 3D displays of time-dynamic volumetric data sets and the first open-source 3D visualization system.
A Markov logic network (MLN) is a probabilistic logic which applies the ideas of a Markov network to first-order logic, defining probability distributions on possible worlds on any given domain.
Probabilistic logic involves the use of probability and logic to deal with uncertain situations. Probabilistic logic extends traditional logic truth tables with probabilistic expressions. A difficulty of probabilistic logics is their tendency to multiply the computational complexities of their probabilistic and logical components. Other difficulties include the possibility of counter-intuitive results, such as in case of belief fusion in Dempster–Shafer theory. Source trust and epistemic uncertainty about the probabilities they provide, such as defined in subjective logic, are additional elements to consider. The need to deal with a broad variety of contexts and issues has led to many different proposals.
Ben Goertzel is a computer scientist, artificial intelligence researcher, and businessman. He helped popularize the term 'artificial general intelligence'.
A semantic reasoner, reasoning engine, rules engine, or simply a reasoner, is a piece of software able to infer logical consequences from a set of asserted facts or axioms. The notion of a semantic reasoner generalizes that of an inference engine, by providing a richer set of mechanisms to work with. The inference rules are commonly specified by means of an ontology language, and often a description logic language. Many reasoners use first-order predicate logic to perform reasoning; inference commonly proceeds by forward chaining and backward chaining. There are also examples of probabilistic reasoners, including non-axiomatic reasoning systems, and probabilistic logic networks.
Transcendent Man is a 2009 documentary film by American filmmaker Barry Ptolemy about inventor, futurist and author Ray Kurzweil and his predictions about the future of technology in his 2005 book, The Singularity is Near. In the film, Ptolemy follows Kurzweil around his world as he discusses his thoughts on the technological singularity, a proposed advancement that will occur sometime in the 21st century when progress in artificial intelligence, genetics, nanotechnology, and robotics will result in the creation of a human-machine civilization.
Psi-theory, developed by Dietrich Dörner at the University of Bamberg, is a systemic psychological theory covering human action regulation, intention selection and emotion. It models the human mind as an information processing agent, controlled by a set of basic physiological, social and cognitive drives. Perceptual and cognitive processing are directed and modulated by these drives, which allow the autonomous establishment and pursuit of goals in an open environment.
Statistical relational learning (SRL) is a subdiscipline of artificial intelligence and machine learning that is concerned with domain models that exhibit both uncertainty and complex, relational structure. Typically, the knowledge representation formalisms developed in SRL use first-order logic to describe relational properties of a domain in a general manner and draw upon probabilistic graphical models to model the uncertainty; some also build upon the methods of inductive logic programming. Significant contributions to the field have been made since the late 1990s.
A probabilistic logic network (PLN) is a conceptual, mathematical and computational approach to uncertain inference. It was inspired by logic programming and it uses probabilities in place of crisp (true/false) truth values, and fractional uncertainty in place of crisp known/unknown values. In order to carry out effective reasoning in real-world circumstances, artificial intelligence software handles uncertainty. Previous approaches to uncertain inference do not have the breadth of scope required to provide an integrated treatment of the disparate forms of cognitively critical uncertainty as they manifest themselves within the various forms of pragmatic inference. Going beyond prior probabilistic approaches to uncertain inference, PLN encompasses uncertain logic with such ideas as induction, abduction, analogy, fuzziness and speculation, and reasoning about time and causality.
Probabilistic programming (PP) is a programming paradigm in which probabilistic models are specified and inference for these models is performed automatically. It represents an attempt to unify probabilistic modeling and traditional general purpose programming in order to make the former easier and more widely applicable. It can be used to create systems that help make decisions in the face of uncertainty.
The Conference on Artificial General Intelligence is a meeting of researchers in the field of Artificial General Intelligence organized by the AGI Society, steered by Marcus Hutter and Ben Goertzel. It has been held annually since 2008. The conference was initiated by the 2006 Bethesda Artificial General Intelligence Workshop and has been hosted at the University of Memphis ; Arlington, Virginia ; Lugano, Switzerland ; Google headquarters in Mountain View, California ; the University of Oxford, United Kingdom ; and at Peking University, Beijing, China, Quebec City, Canada. The AGI-23 conference was held in Stockholm, Sweden.
Shane Legg is a machine learning researcher and entrepreneur. With Demis Hassabis and Mustafa Suleyman, he cofounded DeepMind Technologies, and works there as the chief AGI scientist. He is also known for his academic work on artificial general intelligence, including his thesis supervised by Marcus Hutter.
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.
The following outline is provided as an overview of, and topical guide to, machine learning:
Sophia is a female social humanoid robot developed in 2016 by the Hong Kong–based company Hanson Robotics. Sophia was activated on February 14, 2016, and made her first public appearance in mid-March 2016 at South by Southwest (SXSW) in Austin, Texas, United States. Sophia was marketed as a "social robot" who can mimic social behavior and induce feelings of love in humans.
ProbLog is a probabilistic logic programming language that extends Prolog with probabilities. It minimally extends Prolog by adding the notion of a probabilistic fact, which combines the idea of logical atoms and random variables. Similarly to Prolog, ProbLog can query an atom. While Prolog returns the truth value of the queried atom, ProbLog returns the probability of it being true.
