History Of Artificial Intelligence Research Articles

Getting Beyond the Toy Domain. Meditations on David Deamer's "Assembling Life".

David Deamer has written another book, Assembling Life, on the origin of life. It is unapologetically polemic, presenting Deamer’s view that life originated in fresh water hydrothermal fields on volcanic islands on early Earth, arguing that this provided a unique environment not just for organic chemistry but for the self-assembling structure that drive that chemistry and form the basis of structure in life. It is worth reading, it is an advance in the field, but is it convincing? I argue that the Origin of Life field as a whole is unconvincing, generating results in Toy Domains that cannot be scaled to any real world scenario. I suggest that, by analogy with the history of artificial intelligence and solar astronomy, we need much more scale, and fundamentally new ideas, to take the field forward.

Artificial intelligence in detecting early RA

To prevent chronicity of Rheumatoid Arthritis (RA) by early treatment, detecting inflammatory signs in an early phase is essential. Since Magnetic Resonance Imaging (MRI) of the wrist, hand and foot can detect inflammation before it is clinically detectable, this modality may play an important role in achieving very early diagnoses. By collecting large amounts of MRI data from healthy controls and patients with arthralgia suspicious for progression to RA, patterns can be studied that are most specific for early development of RA. Furthermore, MRI can be used as outcome parameter for randomized placebo-controlled trials on early RA treatment, by detecting subtle changes in image intensities originating from natural progression or treatment effects. Very large amounts of MRI data, however, make manual quantification impractical and the coarse scale used in visual scoring systems (i.e. whole values between 0 and 3) limits its sensitivity to detect changes that are likely to be very subtle in such an early phase. In recent years, advances in artificial intelligence and especially ‘deep learning’ in interpreting medical images have shown that -in specific areas- a computerized analysis can outperform human observers. Therefore, research has been initiated into applying these artificial intelligence techniques to the quantification of early RA from MRI data. In this paper, an overview is given on the background and history of artificial intelligence, with a special focus on recent developments in ‘deep learning’, and how these techniques could be applied to detect subtle inflammatory changes in MRI data.

ARTIFICIAL INTELLIGENCE TECHNOLOGY IN THE CONTEXT OF THE BUSINESS ENVIRONMENT

This article discusses the concept of artificial intelligence. The purpose of this research is to highlight the current state of the areas in which artificial intelligence can be implemented, as well as to assess the potential of the introduction of this technology in the business sphere. A detailed analysis and reviews of the basic concepts of this technology, and their content is shown. Particular attention is paid to the development of the history of artificial intelligence and the explanation of the folding of this term as an important element of modern IT- infrastructure. The characteristic features of artificial intelligence components are distinguished and described. Attention is also focused on the historical aspect of the formation of all-important characteristics for understanding. The tasks, goals and applications of artificial intelligence are defined. A detailed analysis of the results of the introduction of artificial intelligence in enterprises and indicates the dependence of the success of the organization on the degree of trust and the introduction of artificial intelligence technologies. Experts ' forecasts on the role and extent of the impact of this technology in the business sector in the short and medium term are described.

A Brief History of Artificial Intelligence: On the Past, Present, and Future of Artificial Intelligence

This introduction to this special issue discusses artificial intelligence (AI), commonly defined as “a system’s ability to interpret external data correctly, to learn from such data, and to use those learnings to achieve specific goals and tasks through flexible adaptation.” It summarizes seven articles published in this special issue that present a wide variety of perspectives on AI, authored by several of the world’s leading experts and specialists in AI. It concludes by offering a comprehensive outlook on the future of AI, drawing on micro-, meso-, and macro-perspectives.

Artificial Intelligence in Pathology.

As in other domains, artificial intelligence is becoming increasingly important in medicine. In particular, deep learning-based pattern recognition methods can advance the field of pathology by incorporating clinical, radiologic, and genomic data to accurately diagnose diseases and predict patient prognoses. In this review, we present an overview of artificial intelligence, the brief history of artificial intelligence in the medical domain, recent advances in artificial intelligence applied to pathology, and future prospects of pathology driven by artificial intelligence.

Mythical androids and ancient automatons Gods and Robots: Myths, Machines, and Ancient Dreams of Technology Adrienne Mayor Princeton University Press, 2018. 291 pp.

Technology tales from classical literature reveal the storied history of artificial intelligence

Искусственный интеллект: путь к будущему?

The article analyzes the history and prospects of artificial intelligence as a scientific discipline and technologies. Is it possible to reduce all intelligent human actions to algorithmic procedure and how to find the meta-procedure for private algorithms? The answers to these questions are, to a first approximation, the history of artificial intelligence. This history moves in cycles: it seems that if not today, then tomorrow artificial intelligence will solve all the problems of mankind, then artificial intelligence is only a utopia. Today we have serious reason to believe that in the near future artificial intelligence can truly transform human society. The main reason for the new capabilities of artificial intelligence is the integration of its applications with modern digital technology, Internet technology and Big Data. The article discusses the question of what social and existential threats are associated with the artificial intelligence. The article emphasizes that the positive use of artificial intelligence methods is directly related to our understanding of what is а man. Thus, in the implementation of the development of artificial intelligence technologies, the participation of philosophy becomes vital.

Sobre a natureza da inteligência

No trajecto da história da (Inteligência Artificial) IA, observamos que a procura epistemológica da natureza/compreensão da inteligência tem sido uma constante, embora o ponto de vista dos vários investigadores tenha variado ao longo dos últimos 28 anos. No presente artigo esboçam-se as noções mais pertinentes para a caracterização de «inteligência», noções que estão presentes no projecto e na construção dos sistemas que evidenciam um comportamento inteligente.

The End of the Beginning for the Brain How to Create a Mind The Secret of Human Thought Revealed by Ray Kurzweil Viking, New York, 2012. 352 pp. $27.95, C$29.50. ISBN 9780670025299. Duckworth, London. €20. ISBN 9780715645376

After romping through the history of artificial intelligence, Kurzweil presents hierarchical, hidden Markov models as the means to understanding of the mind.

Artificial intelligence

AbstractArtificial intelligence (AI) is the Science and Engineering domain concerned with the theory and practice of developing systems that exhibit the characteristics we associate with intelligence in human behavior. Starting with a brief history of artificial intelligence, this article presents a general overview of this broad interdisciplinary field, organized around the main modules of the notional architecture of an intelligent agent (knowledge representation; problem solving and planning; knowledge acquisition and learning; natural language, speech, and vision; action processing and robotics) which highlights both the main areas of artificial intelligence research, development and application, and also their integration. WIREs Comput Stat 2012, 4:168–180. doi: 10.1002/wics.200This article is categorized under: Software for Computational Statistics > Artificial Intelligence and Expert Systems

Morphological Analyser and Morphological Generator for Malayalam Tamil Machine Translation

Language Processing (NLP) is both a modern computational technology and a method of investigating and evaluating claims about human language itself. Some prefer the term Computational Linguistics in order to capture this latter function, but NLP is a term that links back into the history of Artificial Intelligence (AI), the general study of cognitive function by computational processes, normally with an emphasis on the role of knowledge representations, that is to say the need for representations of our knowledge of the world in order to understand human language with computers. A morphological analyzer or generator supplies information concerning morphosyntactic properties of the words it analyses or constructs. Morphological Analysis and Generation are important components for building computational grammars as well as Machine Translation. Morphological Analyzer is a program for analyzing the morphology of an input word; the analyzer reads the inflected surface form of each word in a text and provides its lexical form while Generation is the inverse process. Both Analysis and Generation make use of lexicon. Malayalam like the other languages in the Dravidian family exhibits the characteristics of an agglutinative language. Here using a bilingual dictionary, the Malayalam morphological analyzer and the Tamil morphological generator have been described.

Constructions of gender in the history of artificial intelligence

Key developments in the history of artificial intelligence are described in terms of a model of gender (Man of Reason), drawn from the work of philosopher Genevieve Lloyd, and informed by research in gender and technology and feminist epistemology. Significantly, the model demonstrates the elevation of mental knowledge over corporeal knowledge. Recent attempts to address the problem of embodiment in situated robotics go some way toward overcoming this problem but have yet to address the question of situatedness, which feminist and other social science research suggests should be an integral part of our models of knowers.

The 1994 Florida AI Research Symposium

The 1994 Florida AI Research Symposium was held 5-7 May at Pensacola Beach, Florida. This symposium brought together researchers and practitioners in AI, cognitive science, and allied disciplines to discuss timely topics, cutting-edge research, and system development efforts in areas spanning the entire AI field. Symposium highlights included Pat Hayes's comparison of the history of AI to the history of powered flight and Clark Glymour's discussion of the prehistory of AI.

AI: the tumultuous history of the search for artificial intelligence

In the summer of 1956, a group of young scientists sat down to consider the astounding proposition that every aspect of learning or any other feature of intelligence can, in principle, be so precisely described that a machine can be made to simulate it. Armed with their own enthusiasm, the excitement of the idea itself, and lots of government money, they predicted that the whole range of human intelligence would be programmable within their own lifetimes. Nearly half a century later, the field has grown tenfold - with mixed results. Based on extensive interviews with the major players in the history of artificial intelligence, including Marvin Minsky, Herbert Simon, Alan Newell, Raj Reddy and Patrick Winston, this book chronicles their successes, from robotics to world-class chess playing and, equally, their failures. With anecdotes about the founders and leaders and their celebrated feuds and intellectual gamesmanship, the book also discusses the next necessary breakthrough - teaching computers common sense.

Artificial intelligence in medical consultation systems: a review

A history of artificial intelligence (AI) in medicine is presented. Pre-1970 medical consultation systems are described briefly. Early prototypes of AI consultation systems are then examined. The shift from predominantly general-problem solving research to domain-specific knowledge-based systems research is discussed. Two phases in the evolution of ideas during the period from 1975-82 are distinguished. From 1975 to 1978, prototype systems were fully developed and subjected to critical testing, while giving rise to generalizations. During the period from 1978 to 1982, the first general system-building frameworks were produced. The reexamination of the foundations of medical consultation systems and the shift to rule-based systems during the period 1982 to 1987 are discussed.

Artificial intelligence for production engineering: a historical approach

SUMMARYThis paper describes the principles of the advanced programming techniques often dubbed Artificial Intelligence involved in decision making as may be of some value in matters related to production engineering. Automated decision making in the context of production can adopt many aspects. At the most obvious level, a robot may have to plan a sequence of actions on the basis of signals obtained from changing conditions in its environment. These signals may, indeed, be quite complex, for example the input of visual information from a television camera.At another level, automated planning may be required to schedule the entire work cycle of a plant that includes many robots as well as other types of automated machinery. The often-quoted dark factory is an example of this, where not only some of the operations (such as welding) are done by robots, but also the transport of part-completed assemblies is automatically scheduled as a set of actions for autonomic transporters and cranes. It is common practice for this activity to be preprogrammed to the greatest detail. Automated decision making is aimed at adding flexibility to the process so that it can absolve the system designer from having to forsee every eventuality at the design stage.Frequent reference is made in this context to artificial intelligence (AI), knowledge-based and expert systems. Although these topics are more readily associated with computer science, it is the automated factory, in general, and the robot, in particular, that will benefit from success in these fields. In this part of the paper we try to sharpen up this perspective, while in part II we aim to discuss the history of artificial intelligence in this context. In part III we discuss the industrial prospects for the field.

The History of Artificial Intelligence at Rutgers

The founding of a new college at Rutgers in 1969 became the occasion for building a strong computer science presence in the University. Livingston College thus provided the home for the newly organized Department of Computer Science (DCS) and for the beginning of computer science research at Rutgers.

The Knowledge Level: Presidential Address

This is the first presidential address of AAAI, the American Association for Artificial Intelligence. In the grand scheme of history of artificial intelligence (AI), this is surely a minor event. The field this scientific society represents has been thriving for quite some time. No doubt the society itself will make solid contributions to the health of our field. But it is too much to expect a presidential address to have a major impact. So what is the role of the presidential address and what is the significance of the first one? I believe its role is to set a tone, to provide an emphasis. I think the role of the first address is to take a stand about what that tone and emphasis should be-set expectations for future addresses and to communicate to my fellow presidents. Only two foci are really possible for a presidential address: the state of the society or the state of the science. I believe the latter to be correct focus. AAAI itself, its nature and its relationship to the larger society that surrounds it, are surely important. However, our main business is to help AI become a science -- albeit a science with a strong engineering flavor. Thus, though a president's address cannot be narrow or highly technical, it can certainly address a substantive issue. That is what I propose to do.