Theory and development of COMPUTER SYSTEMS which perform tasks that normally require human intelligence. Such tasks may include speech recognition, LEARNING; VISUAL PERCEPTION; MATHEMATICAL COMPUTING; reasoning, PROBLEM SOLVING, DECISION-MAKING, and translation of language.
The ability to learn and to deal with new situations and to deal effectively with tasks involving abstractions.
Computer programs based on knowledge developed from consultation with experts on a problem, and the processing and/or formalizing of this knowledge using these programs in such a manner that the problems may be solved.
Approximate, quantitative reasoning that is concerned with the linguistic ambiguity which exists in natural or synthetic language. At its core are variables such as good, bad, and young as well as modifiers such as more, less, and very. These ordinary terms represent fuzzy sets in a particular problem. Fuzzy logic plays a key role in many medical expert systems.
A computer architecture, implementable in either hardware or software, modeled after biological neural networks. Like the biological system in which the processing capability is a result of the interconnection strengths between arrays of nonlinear processing nodes, computerized neural networks, often called perceptrons or multilayer connectionist models, consist of neuron-like units. A homogeneous group of units makes up a layer. These networks are good at pattern recognition. They are adaptive, performing tasks by example, and thus are better for decision-making than are linear learning machines or cluster analysis. They do not require explicit programming.
Toxic, possibly carcinogenic, monomer of neoprene, a synthetic rubber; causes damage to skin, lungs, CNS, kidneys, liver, blood cells and fetuses. Synonym: 2-chlorobutadiene.
Use of an interactive computer system designed to assist the physician or other health professional in choosing between certain relationships or variables for the purpose of making a diagnostic or therapeutic decision.
Standardized tests that measure the present general ability or aptitude for intellectual performance.
Application of computer programs designed to assist the physician in solving a diagnostic problem.
The ability to understand and manage emotions and to use emotional knowledge to enhance thought and deal effectively with tasks. Components of emotional intelligence include empathy, self-motivation, self-awareness, self-regulation, and social skill. Emotional intelligence is a measurement of one's ability to socialize or relate to others.
A procedure consisting of a sequence of algebraic formulas and/or logical steps to calculate or determine a given task.
Computer-based representation of physical systems and phenomena such as chemical processes.
Tests designed to measure intellectual functioning in children and adults.
Sequential operating programs and data which instruct the functioning of a digital computer.
Intellectual or mental process whereby an organism obtains knowledge.
An individual intelligence test designed primarily for school children to predict school performance and the ability to adjust to everyday demands.
Tests designed to assess neurological function associated with certain behaviors. They are used in diagnosing brain dysfunction or damage and central nervous system disorders or injury.
Disturbances in mental processes related to learning, thinking, reasoning, and judgment.
The continuous sequential physiological and psychological maturing of an individual from birth up to but not including ADOLESCENCE.
Subnormal intellectual functioning which originates during the developmental period. This has multiple potential etiologies, including genetic defects and perinatal insults. Intelligence quotient (IQ) scores are commonly used to determine whether an individual has an intellectual disability. IQ scores between 70 and 79 are in the borderline range. Scores below 67 are in the disabled range. (from Joynt, Clinical Neurology, 1992, Ch55, p28)
A learning situation involving more than one alternative from which a selection is made in order to attain a specific goal.
A set of cognitive functions that controls complex, goal-directed thought and behavior. Executive function involves multiple domains, such as CONCEPT FORMATION, goal management, cognitive flexibility, INHIBITION control, and WORKING MEMORY. Impaired executive function is seen in a range of disorders, e.g., SCHIZOPHRENIA; and ADHD.
Writings having excellence of form or expression and expressing ideas of permanent or universal interest. The body of written works produced in a particular language, country, or age. (Webster, 3d ed)
The aggregate of various economic, political, and social policies by which an imperial power maintains or extends its control over other areas or peoples. It includes the practice of or belief in acquiring and retaining colonies. The emphasis is less on its identity as an ideological political system than on its designation in a period of history. (Webster, 3d ed; from Dr. J. Cassedy, NLM History of Medicine Division)
Those affective states which can be experienced and have arousing and motivational properties.
The faculty of expressing the amusing, clever, or comical or the keen perception and cleverly apt expression of connections between ideas that awaken amusement and pleasure. (From Random House Unabridged Dictionary, 2d ed)
A legal concept that an accused is not criminally responsible if, at the time of committing the act, the person was laboring under such a defect of reason from disease of the mind as not to know the nature and quality of the act done or if the act was known, to not have known that what was done was wrong. (From Black's Law Dictionary, 6th ed)
Using an INTERNET based personal journal which may consist of reflections, comments, and often hyperlinks.

E-CELL: software environment for whole-cell simulation. (1/4007)

MOTIVATION: Genome sequencing projects and further systematic functional analyses of complete gene sets are producing an unprecedented mass of molecular information for a wide range of model organisms. This provides us with a detailed account of the cell with which we may begin to build models for simulating intracellular molecular processes to predict the dynamic behavior of living cells. Previous work in biochemical and genetic simulation has isolated well-characterized pathways for detailed analysis, but methods for building integrative models of the cell that incorporate gene regulation, metabolism and signaling have not been established. We, therefore, were motivated to develop a software environment for building such integrative models based on gene sets, and running simulations to conduct experiments in silico. RESULTS: E-CELL, a modeling and simulation environment for biochemical and genetic processes, has been developed. The E-CELL system allows a user to define functions of proteins, protein-protein interactions, protein-DNA interactions, regulation of gene expression and other features of cellular metabolism, as a set of reaction rules. E-CELL simulates cell behavior by numerically integrating the differential equations described implicitly in these reaction rules. The user can observe, through a computer display, dynamic changes in concentrations of proteins, protein complexes and other chemical compounds in the cell. Using this software, we constructed a model of a hypothetical cell with only 127 genes sufficient for transcription, translation, energy production and phospholipid synthesis. Most of the genes are taken from Mycoplasma genitalium, the organism having the smallest known chromosome, whose complete 580 kb genome sequence was determined at TIGR in 1995. We discuss future applications of the E-CELL system with special respect to genome engineering. AVAILABILITY: The E-CELL software is available upon request. SUPPLEMENTARY INFORMATION: The complete list of rules of the developed cell model with kinetic parameters can be obtained via our web site at: http://e-cell.org/.  (+info)

A prognostic computer model to individually predict post-procedural complications in interventional cardiology: the INTERVENT Project. (2/4007)

AIMS: The purpose of this part of the INTERVENT project was (1) to redefine and individually predict post-procedural complications associated with coronary interventions, including alternative/adjunctive techniques to PTCA and (2) to employ the prognostic INTERVENT computer model to clarify the structural relationship between (pre)-procedural risk factors and post-procedural outcome. METHODS AND RESULTS: In a multicentre study, 2500 data items of 455 consecutive patients (mean age: 61.1+/-8.3 years: 33-84 years) undergoing coronary interventions at three university centres were analysed. 80.4% of the patients were male, 16.7% had unstable angina, and 5.1%/10.1% acute/subacute myocardial infarction. There were multiple or multivessel stenoses in 16.0%, vessel bending >90 degrees in 14.5%, irregular vessel contours in 65.0%, moderate calcifications in 20.9%, moderate/severe vessel tortuosity in 53.2% and a diameter stenosis of 90%-99% in 44.4% of cases. The in-lab (out-of-lab) complications were: 0.4% (0.9%) death, 1.8% (0.2%) abrupt vessel closure with myocardial infarction and 5.5% (4.0) haemodynamic disorders. CONCLUSION: Computer algorithms derived from artificial intelligence were able to predict the individual risk of these post-procedural complications with an accuracy of >95% and to explain the structural relationship between risk factors and post-procedural complications. The most important prognostic factors were: heart failure (NYHA class), use of adjunctive/alternative techniques (rotablation, atherectomy, laser), acute coronary ischaemia, pre-existent cardiac medication, stenosis length, stenosis morphology (calcification), gender, age, amount of contrast agent and smoker status. Pre-medication with aspirin or other cardiac medication had a beneficial effect. Techniques, such as laser angioplasty or atherectomy were predictors for post-procedural complications. Single predictors alone were not able to describe the individual outcome completely.  (+info)

Virtual management of radiology examinations in the virtual radiology environment using common object request broker architecture services. (3/4007)

In the Department of Defense (DoD), US Army Medical Command is now embarking on an extremely exciting new project--creating a virtual radiology environment (VRE) for the management of radiology examinations. The business of radiology in the military is therefore being reengineered on several fronts by the VRE Project. In the VRE Project, a set of intelligent agent algorithms determine where examinations are to routed for reading bases on a knowledge base of the entire VRE. The set of algorithms, called the Meta-Manager, is hierarchical and uses object-based communications between medical treatment facilities (MTFs) and medical centers that have digital imaging network picture archiving and communications systems (DIN-PACS) networks. The communications is based on use of common object request broker architecture (CORBA) objects and services to send patient demographics and examination images from DIN-PACS networks in the MTFs to the DIN-PACS networks at the medical centers for diagnosis. The Meta-Manager is also responsible for updating the diagnosis at the originating MTF. CORBA services are used to perform secure message communications between DIN-PACS nodes in the VRE network. The Meta-Manager has a fail-safe architecture that allows the master Meta-Manager function to float to regional Meta-Manager sites in case of server failure. A prototype of the CORBA-based Meta-Manager is being developed by the University of Arizona's Computer Engineering Research Laboratory using the unified modeling language (UML) as a design tool. The prototype will implement the main functions described in the Meta-Manager design specification. The results of this project are expected to reengineer the process of radiology in the military and have extensions to commercial radiology environments.  (+info)

Meta-manager: a requirements analysis. (4/4007)

The digital imaging network-picture-archiving and communications system (DIN-PACS) will be implemented in ten sites within the Great Plains Regional Medical Command (GPRMC). This network of PACS and teleradiology technology over a shared T1 network has opened the door for round the clock radiology coverage of all sites. However, the concept of a virtual radiology environment poses new issues for military medicine. A new workflow management system must be developed. This workflow management system will allow us to efficiently resolve these issues including quality of care, availability, severe capitation, and quality of the workforce. The design process of this management system must employ existing technology, operate over various telecommunication networks and protocols, be independent of platform operating systems, be flexible and scaleable, and involve the end user at the outset in the design process for which it is developed. Using the unified modeling language (UML), the specifications for this new business management system were created in concert between the University of Arizona and the GPRMC. These specifications detail a management system operating through a common object request brokered architecture (CORBA) environment. In this presentation, we characterize the Meta-Manager management system including aspects of intelligence, interfacility routing, fail-safe operations, and expected improvements in patient care and efficiency.  (+info)

Integrated radiology information system, picture archiving and communications system, and teleradiology--workflow-driven and future-proof. (5/4007)

The proliferation of integrated radiology information system/picture archiving and communication system (RIS/PACS) and teleradiology has been slow because of two concerns: usability and economic return. A major dissatisfaction on the usability issue is that contemporary systems are not intelligent enough to support the logical workflow of radiologists. We propose to better understand the algorithms underlying the radiologists' reading process, and then embed this intelligence into the software program so that radiologists can interact with the system with less conscious effort. Regarding economic return issues, people are looking for insurance against obsolescence in order to protect their investments. We propose to future-proof a system by sticking to the following principles: compliance to industry standards, commercial off-the-shelf (COTS) components, and modularity. An integrated RIS/PACS and teleradiology system designed to be workflow-driven and future-proof is being developed at Texas Tech University Health Sciences Center.  (+info)

Mapping of putative binding sites on the ectodomain of the type II TGF-beta receptor by scanning-deletion mutagenesis and knowledge-based modeling. (6/4007)

Binding surfaces of the type II transforming growth factor (TGF)-beta receptor extracellular domain (TbetaRII-ECD) are mapped by combining scanning-deletion mutagenesis results with knowledge-based modeling of the ectodomain structure. Of the 17 deletion mutants produced within the core binding domain of TbetaRII-ECD, only three retained binding to TGF-beta. Comparative modeling based on the crystal structure of the activin type II receptor extracellular domain (ActRII-ECD) indicates that the TbetaRII mutants which retain TGF-beta binding are deleted in some of the loops connecting the beta-strands in the TbetaRII-ECD model. Interpretation of the mutagenesis data within the structural framework of the ectodomain model allows for the prediction of potential binding sites at the surface of TbetaRII-ECD.  (+info)

Integrated databases and computer systems for studying eukaryotic gene expression. (7/4007)

MOTIVATION: The goal of the work was to develop a WWW-oriented computer system providing a maximal integration of informational and software resources on the regulation of gene expression and navigation through them. Rapid growth of the variety and volume of information accumulated in the databases on regulation of gene expression necessarily requires the development of computer systems for automated discovery of the knowledge that can be further used for analysis of regulatory genomic sequences. RESULTS: The GeneExpress system developed includes the following major informational and software modules: (1) Transcription Regulation (TRRD) module, which contains the databases on transcription regulatory regions of eukaryotic genes and TRRD Viewer for data visualization; (2) Site Activity Prediction (ACTIVITY), the module for analysis of functional site activity and its prediction; (3) Site Recognition module, which comprises (a) B-DNA-VIDEO system for detecting the conformational and physicochemical properties of DNA sites significant for their recognition, (b) Consensus and Weight Matrices (ConsFrec) and (c) Transcription Factor Binding Sites Recognition (TFBSR) systems for detecting conservative contextual regions of functional sites and their recognition; (4) Gene Networks (GeneNet), which contains an object-oriented database accumulating the data on gene networks and signal transduction pathways, and the Java-based Viewer for exploration and visualization of the GeneNet information; (5) mRNA Translation (Leader mRNA), designed to analyze structural and contextual properties of mRNA 5'-untranslated regions (5'-UTRs) and predict their translation efficiency; (6) other program modules designed to study the structure-function organization of regulatory genomic sequences and regulatory proteins. AVAILABILITY: GeneExpress is available at http://wwwmgs.bionet.nsc. ru/systems/GeneExpress/ and the links to the mirror site(s) can be found at http://wwwmgs.bionet.nsc.ru/mgs/links/mirrors.html+ ++.  (+info)

Automated diagnosis of data-model conflicts using metadata. (8/4007)

The authors describe a methodology for helping computational biologists diagnose discrepancies they encounter between experimental data and the predictions of scientific models. The authors call these discrepancies data-model conflicts. They have built a prototype system to help scientists resolve these conflicts in a more systematic, evidence-based manner. In computational biology, data-model conflicts are the result of complex computations in which data and models are transformed and evaluated. Increasingly, the data, models, and tools employed in these computations come from diverse and distributed resources, contributing to a widening gap between the scientist and the original context in which these resources were produced. This contextual rift can contribute to the misuse of scientific data or tools and amplifies the problem of diagnosing data-model conflicts. The authors' hypothesis is that systematic collection of metadata about a computational process can help bridge the contextual rift and provide information for supporting automated diagnosis of these conflicts. The methodology involves three major steps. First, the authors decompose the data-model evaluation process into abstract functional components. Next, they use this process decomposition to enumerate the possible causes of the data-model conflict and direct the acquisition of diagnostically relevant metadata. Finally, they use evidence statically and dynamically generated from the metadata collected to identify the most likely causes of the given conflict. They describe how these methods are implemented in a knowledge-based system called GRENDEL and show how GRENDEL can be used to help diagnose conflicts between experimental data and computationally built structural models of the 30S ribosomal subunit.  (+info)

TY - GEN. T1 - Performance comparison of machine learning classification algorithms. AU - Veena, K. M.. AU - Manjula Shenoy, K.. AU - Ajitha Shenoy, K. B.. PY - 2018/1/1. Y1 - 2018/1/1. N2 - Classification of binary and multi-class datasets to draw meaningful decisions is the key in todays scientific world. Machine learning algorithms are known to effectively classify complex datasets. This paper attempts to study and compare the classification performance if four supervised machine learning classification algorithms, viz., Classification And Regression Trees, k-Nearest Neighbor, Support Vector Machines and Naive Bayes to five different types of data sets, viz., mushrooms, page-block, satimage, thyroid and wine. The classification accuracy of each algorithm is evaluated using the 10-fold cross-validation technique. The Classification And Regression Tree algorithm is found to give the best classification accuracy.. AB - Classification of binary and multi-class datasets to draw meaningful ...
Artificial intelligence can make doctors more efficient by diagnosing a patient quickly without any loss of accuracy, it can even interpret results rapidly. But despite all these benefits, we shouldnt forget that artificial intelligence is but another piece of technology. And like all pieces of technology, there will always be a risk of failure.. Now, the question at hand is whether artificial intelligence can be sued when it causes injury or death to a patient. How is justice meted in such a scenario, and who is liable for damages?. No Laws, No Precedents On Handling AI.. As of this writing, there are no known laws or precedents that govern the use of artificial intelligence as the technology has yet to be implemented into the medical field. However, this does not mean that when an injury is caused by the failure of artificial intelligence, that there are no liabilities to be determined.. However.. Artificial intelligence should be treated as a product rather than its own person, given the ...
Agent--Based Models (ABMs) are indispensable to studying the aggregated impacts of individual actions of heterogeneous interacting adaptive agents. Concurrently, artificial intelligence has been employed for decades to simulate autonomous actions of individual entities that react, learn and exchange information with an environment and one another. There are obvious synergies between the two computational approaches. For example, artificial intelligence is often used to enhance agents behaviour in ABMs. Artificial intelligence learning algorithms (AILAs) allow for a richer agents architecture for operationalization of more realistic learning decisions beyond a simplistic treatment of agents cognitive and sensory capacities. Firstly, we review recent socio--economic and spatial ABMs that employ different AILAs to create individually, socially and spatially intelligent agents. We provide a systematic structured analysis of the types of AILAs employed in various application domains, their specific
However, many different areas of artificial intelligence exist beyond machine learning. Resolution 6. , it consists of two parts, the first part x is the subject of the statement and second part is an integer, is known as a predicate. Logic and Artificial Intelligence research encompasses foundational studies in Logic and a variety of Artificial Intelligence disciplines. If the condition is true, then the action is taken, else not. The simple form of logic is Propositional Logic, also called Boolean Logic. Artificial intelligence (AI) is as much a branch of computer science as are its other branches, which include numerical methods, language theory, programming systems, and hardware systems. Module - 2 Artificial Intelligence Notes pdf (AI notes pdf) Logic Concepts and Logic Programming, Propositional Logic, Natural Deduction Systems, Axiomatic System,Semantic Tableau, System in Propositional logic and Knowledge Representation and more topics. In Existential quantifier, ∃x∃y is similar to ...
Chatbots are computer engineered programs to perform tasks. While Artificial Intelligence depends on what it has learnt previously and its current interactions, so it can adapt to the next scenario. Chatbots will be able to solve queries that are engineered through programs as they rely on limited parameters, on the other hand, artificial intelligence improves with time as it relies on historical patterns and evolves with data.. AI powered virtual assistants and chatbots are your intelligent assistants to customer service agents just like a calculator is for an accountant. Companies that focus on Artificial Intelligence rely on NLP, deep learning and machine learning. Using Artificial Intelligence computers can be trained to accomplish specific job functions and tasks by processing large amounts of data.. Artificial Intelligence will help improve productivity, lower costs, drive sales, and create new growth opportunities. In the not so distant future, AI will offer more personalized experiences ...
As a MarketResearchReports.Biz report, it covers all details inside analysis and opinion in Artificial Intelligence Market. This report mainly introduces volume and value market share by players, by regions, by product type, by consumers and also their price change details.. This report splits Artificial Intelligence Market by Product & Service, by Test Type, by Allergen, which covers the history data information from 2016 to 2024.. The Artificial Intelligence Market report provides analysis of the global artificial intelligence market for the period 2014-2024, wherein the years from 2016 to 2024 is the forecast period and 2015 is considered as the base year. The report precisely covers all the major trends and technologies playing a major role in the artificial intelligence markets growth over the forecast period. It also highlights the drivers, restraints, and opportunities expected to influence the market growth during this period. The study provides a holistic perspective on the ...
Get Free Sample Global Healthcare Artificial Intelligence Market Report 2019″ at: https://www.marketresearchfuture.com/sample_request/5681. Top Companies Operating in Healthcare Artificial Intelligence Market. The prominent players operating the Artificial Intelligence in Healthcare market are Koninklijke Philips N.V., IBM Watson Health, NVIDIA Corporation, CloudMedx Inc., Microsoft Corporation, Google, General Electric, Next IT Corp., Intel Corporation, DEEP GENOMICS, General Vision, and Stryker.. Healthcare Artificial Intelligence Market Potential and Pitfalls. Artificial Intelligence has developed several applications in the healthcare sector, such as delivery of health services, detection of diseases, drug discovery, and management of chronic diseases. It ensures effectiveness and efficiency which is likely to trigger its adoption rate in the coming years. AI has also strengthened its foothold in the healthcare research sector for delivering accurate results. This has further contributed ...
Purpose This paper proposes a real-time knowledge support framework for the development of an RFID-multi-agent based process knowledge-based system which has the ability to solve dynamic logistics process management problems. Design/methodology/approach The proposed system is developed with real-time process management capability which automatically identifies current process status, performs the process logic checking/reasoning, and, provides process knowledge support to staff members when they are tackling logistics activity problems. The unique feature of this on-line knowledge-based system, which enables it to enhance the performance of logistics organizations, is a process management engine incorporating radio-frequency identification (RFID) and multi-agent (MA) technologies.
With the great advancement in robot technology, smart human-robot interaction is considered to be the most wanted success by the researchers these days. If a robot can identify emotions and intentions of a human interacting with it, that would make robots more useful. Electroencephalography (EEG) is considered one effective way of recording emotions and motivations of a human using brain. Various machine learning techniques are used successfully to classify EEG data accurately. K-Nearest Neighbor, Bayesian Network, Artificial Neural Networks and Support Vector Machine are among the suitable machine learning techniques to classify EEG data. The aim of this thesis is to evaluate different machine learning techniques to classify EEG data associated with specific affective/emotional states. Different methods based on different signal processing techniques are studied to find a suitable method to process the EEG data. Various number of EEG data features are used to identify those which give best ...
TY - GEN. T1 - Weka machine learning classification in identifying autonomic dysfunction parameters associated with ACE insertion/deletion genotypes. AU - Ng, Ethan. AU - Hambly, Brett. AU - Matthews, Slade. AU - McLachlan, Craig S.. AU - Jelinek, Herbert F.. PY - 2012/7/16. Y1 - 2012/7/16. N2 - This study was designed to investigate parameters of autonomic dysfunction that may be under the influence of ACE ID genotypes. 136 patients with (47) and without type II diabetes were genotyped. Biomarkers such as HbAlc and eGFR, blood pressure, blood cholesterol are in part regulated by the autonomic nervous system and heart rate variability is an indicator of autonomic balance between the sympathetic and parasympathetic division. Several statistical methods were used, including the J48 decision tree machine learning algorithm to associate parameters of autonomic dysfunction and other biomarkers with ACE genotype. Non-parametric and machine learning methods detected more variables, which were able to ...
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Research of the Section for Artificial Intelligence and Decision Support (AID) focusses on Artificial Intelligence technology and computer-based decison support and its use in the medical domain. This includes the development of software systems for intelligent data analysis, knowledge-based systems technology for decision support and therapy planning, and natural language processing which deals with automatic processing of text and speech.. The department offers lectures in Artificial Intelligence on an introductory as well as an advanced level. With regard to particular study programmes, we offer courses for students of Medicine and of Medical Informatics, as well as for students of the Middle European Master Programme in Cognitive Science. Courses are also offered for computer science students in a cooperation with the University of Vienna.. The department was founded in 1977 as an institute of the Medical Faculty of the University of Vienna. In 2004, it became part of the Center for Brain ...
In recent years rapid progress has been made in neuroscience and artificial intelligence. The advancement of artificial intelligence leads to various applications. The brain is the most complex part of human and require thorough study of each part of brain that depicts a persons thoughts, behavior and response. The thoughts and imagination occurring or happening in a persons mind depicts the mental stability of the person, these thoughts and imaginations are converted into images with the help of artificial intelligence. A brain is an electrochemical organ, electrical activity emanating from the brain is displayed in the form of waves or brain waves .The human brain being a complex system is turning into attention catching term for developing technologies in the field of artificial intelligence. Electroencephalography (EEG) is an electrophysiological observation methodology to record electrical activity of brain. Clinically EEG refers to the recording of the brains spontaneous electrical ...
Artificial Intelligence (AI) Apps (Enterprise Level & Excluding - B2C) Market: Overview. The rising adoption of artificial intelligence in diverse industries and the growing demand to create apps are projected to enhance the growth of the global artificial intelligence apps market in the next few years. The market is expected to register a strong growth rate throughout the forecast period. The research study offers a detailed study of the market and highlights the major factors that are likely to support the growth of the overall market in the next few years. AI Apps (Enterprise Level & Excluding - B2C) Market: Trends A tremendous rise in the big data and the rising demand for intelligent virtual assistants are the key factors that are projected to encourage the growth of the global artificial intelligence apps market in the next few years. The growth in the adoption of cloud-based applications and services is another major factor that is likely to enhance market growth in the near future. On ...
Whats the first thing that comes to mind when you think of the term artificial intelligence? If youre a sci-fi junkie like me, you might immediately jump to thoughts of Cyberdyne Technologies or Marvin, the paranoid Android. But in reality, artificial intelligence already plays an active role in our everyday lives.. You may have already recognized it in phone assistants like Siri or Google Now. Or you may have identified AI when playing Chess against a virtual opponent, or when playing more sophisticated motion-tracking games with the Kinect™. But did you know that artificial intelligence is also present in Google Translate and spam blockers?. Studying artificial intelligence opens a world of opportunities. At a basic level, youll better understand the systems and tools that you interact with on a daily basis. And if you stick with the subject and study more, you can help create cutting edge AI applications, like the Google Self Driving Car, or IBMs Watson.. In the field of artificial ...
Leen dit bij een bibliotheek! Artificial intelligence in medicine : 14th Conference on Artificial Intelligence in Medicine, AIME 2013, Murcia, Spain, May 29-June 1, 2013 : proceedings. [Niels Peek; Roque Marín Morales; Mor Peleg;] -- This book constitutes the refereed proceedings of the 14th Conference on Artificial Intelligence in Medicine, AIME 2013, held in Murcia, Spain, in May/June 2013. The 43 revised full and short papers ...
Engineering & Artificial Intelligence Projects for $10 - $30. There are two artificial intelligence homework. Homework-3 has 6 questions and Homework-4 has 4 questions. The artificial intelligence homework will send with message. Payment will be done after home...
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In this chapter we provide a survey of protein secondary and supersecondary structure prediction using methods from machine learning. Our focus is on machine learning methods applicable to β-hairpin and β-sheet prediction, but we also discuss methods for more general supersecondary structure prediction. We provide background on the secondary and supersecondary structures that we discuss, the features used to describe them, and the basic theory behind the machine learning methods used. We survey the machine learning methods available for secondary and supersecondary structure prediction and compare them where possible.. ...
Artificial Intelligence (A.I.) is a rapidly growing topic. It has been one of the top technologies that companies and startups are looking for to increase the efficiency of their organization. A.I. has gained a lot of attention in the past years, mainly due to rapid progress in machine learning and other areas of artificial intelligence. However, many people misunderstand what A.I. is all about.. Artificial Intelligence (A.I.) is the branch of computer science that deals with making computers do things that look like intelligence, whether that is the ability to recognize objects and situations, understand human speech, or solve problems. The development of this technology has contributed to our ability to gather and utilize vast amounts of data, helping us make smarter decisions about our own health, our homes, and our world.. Machine learning is a technique that allows computers to learn how to solve problems without being explicitly programmed. It is not very different from the way humans ...
The challenge with artificial intelligence is that no single and agreed-upon definition exists. Nils Nilsson defined A.I. as activity devoted to making machines intelligent, and intelligence is that quality that enables an entity to function appropriately and with foresight in its environment. But that definition isnt close to describing how A.I. evolved.. Artificial intelligence began with the Turing Test, proposed in 1950 by Alan Turing, the scientist, cryptanalyst and theoretical biologist. Since then, rapid progress has been made over the last 75 years, advancing A.I. capabilities.. Isaac Asimov proposed the Three Laws of Robotics in 1950. The first A.I. program was coded in 1951. In 1959, MIT began research in the field of artificial intelligence. GM introduced the first robot into its production assembly line in 1961. The 1960s were transformative, with the first machine learning program written and the first demonstration of an A.I. program which understood natural language, and the ...
On the basis of offering, the global artificial intelligence in healthcare market is segmented into hardware, software, and services. The market is further segmented by technology into speech recognition, machine learning, querying method, natural language processing, and context aware processing; by application into medical research, diagnosing diseases, electrocardiography, laparoscopy, medical imaging, personalized health assessments, drug discovery, personalized medicine, and others and by end-users into diagnostic labs, hospitals, clinics, and others.. The global artificial intelligence in healthcare market is anticipated to record a CAGR of 45.3% over the forecast period i.e. 2019-2027.. Artificial intelligence in healthcare is being used in radiology, imaging, electronic health records and others which can be attributed to its low error rate, high speed, accuracy, precision and ability to complete a hazardous task without the involvement of humans. For instance, mishandling of samples for ...
Applying Artificial Intelligence to Financial Investing: 10.4018/978-1-5225-2255-3.ch001: Artificial intelligence techniques have long been applied to financial investing scenarios to determine market inefficiencies, criteria for credit scoring
As part of a recent ESOMAR World article on Artificial Intelligence I was interviewed by Insites Consultings Annelies Verheghe for opinions on the topic and how it may affect marketing research, text and data mining. Today Im sharing part of that Q&A below. Would love your thoughts at the bottom, this is an area that is continually evolving for me as well, and which Ive also written about on the OdinText blog here.]. ESOMAR: What is your experience with Artificial Intelligence & Machine Learning (AI)? Would you describe yourself as a user of AI or a person with an interest in the matter but with no or limited experience?. TomHCA: I would describe myself as both a user of Artificial Intelligence as well as a person with a strong interest in the matter even though I have limited mathematical/algorithmic experience with AI. However, I have colleagues here at OdinText who have PhDs in Computer Science and are extremely knowledgeable as they studied AI extensively in school and used it elsewhere ...
Artificial Intelligence, or AI, transformed the digital landscape in more ways than one. Image-recognition software, semi-autonomous vehicles, medical robots and other AI-enabled technology are all possible with this revolutionary technology.. For marketers, AI also presents opportunities we never couldve dreamed of. With AI marketing, digital markets can improve personalization and generate better performance and profits, adding to an already strong data-driven focus.. With AI, the consumer experience can be personalized in a way thats easier and more cost-effective. This allows brands to achieve incredible gains through a deeper understanding of the customer base.. Learn more about the applications for AI in marketing and see how it can revolutionize your marketing campaigns.. What is Artificial Intelligence (AI)?. Artificial Intelligence is simulated intelligence in machines that are programmed to think like humans and mimic human behavior. At its best, AI can rationalize and take action ...
From genome-scale experimental studies to imaging data, behavioral footprints, and longitudinal healthcare records, the convergence of big data in cancer research and the advances in artificial intelligence is paving the way to develop a systems view of cancer. Nevertheless, this biomedical area is largely characterized by the co-existence of big data and small data resources, highlighting the need for a deeper investigation about the crosstalk between different levels of data granularity, including varied sample sizes, labels, data types, and other data descriptors. This review introduces the current challenges, limitations, and solutions of artificial intelligence in the heterogeneous landscape of data granularity in cancer research. Such a variety of cancer molecular and clinical data call for advancing the interoperability among artificial intelligence approaches, with particular emphasis on the synergy between discriminative and generative models that we discuss in this work with several examples
Technology has played an immense role in the evolution of healthcare delivery for the United States and on an international scale. Today, perhaps no innovation offers more potential than artificial intelligence. Utilizing machine intelligence as opposed to human intelligence for the purposes of planning, offering solutions, and providing insights, AI has the ability to alter traditional dynamics between doctors, patients, and administrators; this reality is now producing both elation at artificial intelligences medical promise and uncertainty regarding its capacity in current systems. Nevertheless, current trends reveal that interest in AI among healthcare stakeholders is continuously increasing, and with the current COVID-19 pandemic highlighting institutional flaws, it is reasonable to assume that many industry changes proposed by artificial intelligence will be further considered in the coming years. Therefore, this research aims to assess the changes proposed by AI and how they might impact
Peptides are routinely identified from mass spectrometry-based proteomics experiments by matching observed spectra to peptides derived from protein databases. The error rates of these identifications can be estimated by target-decoy analysis, which involves matching spectra to shuffled or reversed peptides. Besides estimating error rates, decoy searches can be used by semi-supervised machine learning algorithms to increase the number of confidently identified peptides. As for all machine learning algorithms, however, the results must be validated to avoid issues such as overfitting or biased learning, which would produce unreliable peptide identifications. Here, we discuss how the target-decoy method is employed in machine learning for shotgun proteomics, focusing on how the results can be validated by cross-validation, a frequently used validation scheme in machine learning. We also use simulated data to demonstrate the proposed cross-validation schemes ability to detect overfitting.. ...
Artificial intelligence promises to improve existing goods and services, and, by enabling automation of many tasks, to greatly increase the efficiency with which they are produced. But it may have an even larger impact on the economy by serving as a new general-purpose new method of invention that can reshape the nature of the innovation process and the organization of R&D. This exploratory essay considers this possibility in three interrelated ways. First, Cockburn, Henderson, and Stern review the history of artificial intelligence, focusing in particular on the distinction between automation-oriented applications such as robotics and the potential for recent developments in deep learning to serve as a general-purpose method of invention. The researchers then assess preliminary evidence of this differential impact in changing nature of measurable innovation outputs in artificial intelligence, including papers and patents. They find strong evidence of a shift in the importance of ...
Purpose: The study is conducted to evaluate the adaptability of artificial intelligence in recruitment and to assess the effect of this technology on the performance of the employees. Design/Methodology/Approach: Standard Multiple Linear regression model is used to predict the performance of the employees and one-way ANOVA is used to compare the artificial intelligence based recruitment with performance indicating variables namely reliability, productivity, Automation, Gamification & Training using SPSS. Snowball sampling method has been adopted for a sample size of 440 respondents working in leading recruitment consultancies in urban Bangalore. Findings: There is a greater association between the recruitment and performance variables when artificial intelligence is adopted as it is significant at 0.001 per cent level and productivity being the maximum. However, the impact of implementing gamification for recruitment doesnt have a significant impact on the output due to partial significant
Get information, facts, and pictures about artificial intelligence at Encyclopedia.com. Make research projects and school reports about artificial intelligence easy with credible articles from our FREE, online encyclopedia and dictionary.
Columbia Universitys first MicroMasters program in Artificial Intelligence on edX will launch on January 16. This MicroMasters Program from Columbia University will give participants a rigorous, advanced, professional, graduate-level foundation in Artificial Intelligence. The program represents 25 precent of the coursework toward a Masters degree in Computer Science at Columbia. The MicroMasters Program in Artificial Intelligence is intended for those who have a Bachelors degree in Computer Science or Mathematics and have a basic understanding of statistics, college level algebra, calculus and comfort with programming languages.. Learn more on edX. ...
European CEO: How are you analysing all of this genetic data?. Niels Iversen Møller: Well were using artificial intelligence and supercomputers to analyse the genomes of humans or bacteria. We have trained the artificial intelligence to identify components that are unique to cancer patients, and also the Achilles heel proteins of the pathogens that were analysing.. When we talk about cancer, there are certain components called epitopes that we identify by comparing the DNA from tumours to the DNA of healthy tissue. By looking at differences between cancer DNA and also healthy DNA, we can find the mutations that are critical. And also critical in terms of formulating into a vaccine.. When we talk about bacteria, we again analyse using our artificial intelligence. The DNA of those bacteria, finding the Achilles heel components really in the bacteria that we want to put into a vaccine to illicit a strong and protective immune response.. European CEO: So this is personalised healthcare right down ...
TUESDAY, April 25, 2017 (HealthDay News) -- It may be possible to use artificial intelligence to diagnose tuberculosis in people who live in developing nations, a new study suggests.. TB, among the top 10 causes of death worldwide, can be identified on X-rays. But, the expertise required to screen for and diagnose TB is often lacking in areas that have high rates of the lung disease, according to the studys authors.. The researchers from Thomas Jefferson University in Philadelphia used 1,007 X-rays of people with and without active TB to train artificial intelligence models to identify TB on X-rays. It proved highly accurate -- up to 96 percent-- in diagnosing cases.. The study findings were published online April 25 in the journal Radiology. An artificial intelligence solution that could interpret radiographs for presence of TB in a cost-effective way could expand the reach of early identification and treatment in developing nations, study co-author Dr. Paras Lakhani, an assistant professor ...
Artificial Intelligence is already impacting our lives in a major way. Be it getting driving instructions through our smart phone or getting daily reminders by our fitness device to increase our workouts, all these are manifestations of how Artificial Intelligence is changing the way we function. What is often less understood is the significant role Artificial Intelligence can play in the social sector.
View Notes - Homework1 from ENGL 135 at DeVry Addison. Ginger Binder Artificial Intelligence Homework #1 1. Researching and examining various artificial intelligence articles on the subject
How is Mcculloch-Pitts Neuron Model (artificial intelligence) abbreviated? M-P stands for Mcculloch-Pitts Neuron Model (artificial intelligence). M-P is defined as Mcculloch-Pitts Neuron Model (artificial intelligence) very rarely.
Currently, the risk of network information insecurity is increasing rapidly in number and level of danger. The methods mostly used by hackers today is to attack end-to-end technology and exploit human vulnerabilities. These techniques include social engineering, phishing, pharming, etc. One of the steps in conducting these attacks is to deceive users with malicious Uniform Resource Locators (URLs). As a results, malicious URL detection is of great interest nowadays. There have been several scientific studies showing a number of methods to detect malicious URLs based on machine learning and deep learning techniques. In this paper, we propose a malicious URL detection method using machine learning techniques based on our proposed URL behaviors and attributes. Moreover, bigdata technology is also exploited to improve the capability of detection malicious URLs based on abnormal behaviors. In short, the proposed detection system consists of a new set of URLs features and behaviors, a machine learning
BACKGROUND: Driven by the rapid development of big data and processing power, artificial intelligence and machine learning (ML) applications are poised to expand orthopedic surgery frontiers. Lower extremity arthroplasty is uniquely positioned to most dramatically benefit from ML applications given its central role in alternative payment models and the value equation. METHODS: In this report, we discuss the origins and model specifics behind machine learning, consider its progression into healthcare, and present some of its most recent advances and applications in arthroplasty. RESULTS: A narrative review of artificial intelligence and ML developments is summarized with specific applications to lower extremity arthroplasty, with specific lessons learned from osteoarthritis gait models, joint-specific imaging analysis, and value-based payment models. CONCLUSION: The advancement and employment of ML provides an opportunity to provide data-driven, high performance medicine that can rapidly improve the
Published in Knowledge-Based Systems, 2017. Recommended citation: María Pérez-Ortiz, Pedro Antonio Gutiérrez, M. D. Ayllón-Terán, N. Heaton, R. Ciria, J. Briceño, César Hervás-Martínez, Synthetic semi-supervised learning in imbalanced domains: Constructing a model for donor-recipient matching in liver transplantation. Knowledge-Based Systems, Vol. 123, 2017, pp.75--87. http://doi.org/10.1016/j.knosys.2017.02.020 ...
The mission of the CI group in our Department is to perform research on various aspects of computational intelligence and to contribute to the Business Mathematics and Informatics curriculum. Computational Intelligence belongs to the areas of evolutionary computing, fuzzy computing and neurocomputing. As opposed to traditional logic based artificial intelligence techniques, computational intelligence techniques are generally bottom-up, where order and structure emerges from an unstructured beginning ...
Intelligent systems can optimise their structure and properties in order to successfully function within a complex, partially changing environment. Three sub-areas - perception, learning and action - can be differentiated here. The scientists at the Max Planck Institute for Intelligent Systems are carrying out basic research and development of intelligent systems in all three sub-areas. Research expertise in the areas of computer science, material science and biology is brought together in one Institute, at two different sites.
An Analytical Study on Performance Factors of Automatic Classification based on Machine Learning - automatic classification;text categorization;performance factors;conference paper;rocchio algorithm;multi-label classification;machine learning;
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Artificial Intelligence can not only turn your customer data into business insights but can use that information to make intelligent decisions, predict outcomes, suggest actions and automate tasks based on machine learning. AI makes your business smarter about how and when it engages its customers. Artificial intelligence is a game-changing business technology thats transforming how we work.
Artificial Intelligence can not only turn your customer data into business insights but can use that information to make intelligent decisions, predict outcomes, suggest actions and automate tasks based on machine learning. AI makes your business smarter about how and when it engages its customers. Artificial intelligence is a game-changing business technology thats transforming how we work.
Machine learning is a branch of artificial intelligence science i.e. the systems that can learn data. For example, a machine learning sys...
MACHINE LEARNING Adversarial attacks on medical machine. THE PAPERS The Workshop on Machine Learning in Medical Applications was held on July 15th, 1999 at Chania, Island of Crete, in Greece, and aimed at presenting some of the advances that have been achieved in the field of application of ML methods in medicine., Machine Learning in Medical Imaging. Download Call for Papers (PDF). Machine learning plays an essential role in the field of medical imaging and image informatics. With advances in medical imaging, new machine learning methods and applications are demanded. Due to large variation and complexity, it is necessary to learn representations of. Machine learning will improve the radiology patient experience, at every step. Much of the initial focus for the application of machine learning in medical imaging has been on image analysis and developing tools to make radiologists more efficient and productive. The … Nov 16, 2018 · The measurements in this Machine Learning applications ...
Functional networks play an important role in the analysis of biological processes and systems. The inference of these networks from high-throughput (-omics) data is an area of intense research. So far, the similarity-based inference paradigm (e.g. gene co-expression) has been the most popular approach. It assumes a functional relationship between genes which are expressed at similar levels across different samples. An alternative to this paradigm is the inference of relationships from the structure of machine learning models. These models are able to capture complex relationships between variables, that often are different/complementary to the similarity-based methods. We propose a protocol to infer functional networks from machine learning models, called FuNeL. It assumes, that genes used together within a rule-based machine learning model to classify the samples, might also be functionally related at a biological level. The protocol is first tested on synthetic datasets and then evaluated on a test
Defence Science and Technology Laboratory (Dstl) has awarded a contract of a £1 million investment to Roke Manor Research, an electronics engineering consultancy, to develop artificial intelligence software that is designed to help the Royal Navy handle the growing complexity of threats.. Named STARTLE, the machine situational awareness software continuously monitors and evaluates potential threats using a combination of artificial intelligence techniques. It is designed after the human brain, emulating the mammalian conditioned-fear response mechanism ...
By Dipayan Mitra. Scientists have developed a new artificial intelligence technology that can spot shipwrecks from the ocean surface and also from the air. The University of Texas collaborated with the United State Navys underwater archeology branch to develop this new artificial intelligence software capable of detecting shipwrecks with an accuracy rate of 92%. The newly developed computer model is now ready to be deployed in order to identify unmapped shipwrecks on the coasts of the United States and Puerto Rico. The artificial intelligence algorithm was fed with images of shipwrecks and underwater topology to enable it to recognize unknown wrecks. The platform uses images from publicly available databases of pictures collected from various parts of the globe and the National Oceanic and Atmospheric Administrations database of shipwrecks. It also uses lidar and sonar-based imageries of the seafloor to carry out its operations more accurately. The lead researcher of the project, Leila ...
The researchers used cutting-edge artificial intelligence to create a chatbot interventional radiologist that can automatically communicate with referring clinicians and quickly provide evidence-based answers to frequently asked questions.. This allows the referring physician to provide real-time information to the patient about the next phase of treatment, or basic information about an interventional radiology treatment.. We theorised that artificial intelligence could be used in a low-cost, automated way in interventional radiology as a way to improve patient care, said Edward W. Lee, M.D., Ph.D., assistant professor of radiology at UCLAs David Geffen School of Medicine and one of the authors of the study. Because artificial intelligence has already begun transforming many industries, it has great potential to also transform health care.. In this research, deep learning was used to understand a wide range of clinical questions and respond appropriately in a conversational manner similar ...
Microsoft Azure Machine Learning (MAML) is a fully managed service on Windows Azure which a developer can use to build a predictive analytics model using machine learning over data and then deploy her model as a web service. ML Studio is accessible through a web browser, with no software to purchase or install, and the authoring experience is through visual composition. There are modules in Azure ML to support the end-to-end data science workflow for constructing a predictive model, from ready access to common data sources, data exploration, feature selection and creation, building training and testing sets, machine learning over data, and final model evaluation and experimentation. In this talk I will present an overview of the basic data science workflow, with details on select machine learning algorithms, then build a predictive analytics model using real world data, evaluate several different machine learning algorithms, then deploy the finished model as a machine learning web service within ...
Get this from a library! Artificial intelligence research and development : proceedings of the 14th International Conference of the Catalan Association for Artificial Intelligence. [Cèsar Fernández; Hector Gaffner; Felip Manyà; IOS Press.;] -- This book is a collection of the papers accepted for presentation at the 14th International Conference of the Catalan Association for Artificial Intelligence (CCIA 2011), held at the University of ...
Research in photonic computing has flourished due to the proliferation of optoelectronic components on photonic integration platforms. Photonic integrated circuits have enabled ultrafast artificial neural networks, providing a framework for a new class of information processing machines. Algorithms running on such hardware have the potential to address the growing demand for machine learning and artificial intelligence in areas such as medical diagnosis, telecommunications, and high-performance and scientific computing. In parallel, the development of neuromorphic electronics has highlighted challenges in that domain, particularly related to processor latency. Neuromorphic photonics offers sub-nanosecond latencies, providing a complementary opportunity to extend the domain of artificial intelligence. Here, we review recent advances in integrated photonic neuromorphic systems, discuss current and future challenges, and outline the advances in science and technology needed to meet those challenges.
Educational Data Mining (EDM) is a rich research field in computer science. Tools and techniques in EDM are useful to predict student performance which gives practitioners useful insights to develop appropriate intervention strategies to improve pass rates and increase retention. The performance of the state-of-the-art machine learning classifiers is very much dependent on the task at hand. Investigating support vector machines has been used extensively in classification problems; however, the extant of literature shows a gap in the application of linear support vector machines as a predictor of student performance. The aim of this study was to compare the performance of linear support vector machines with the performance of the state-of-the-art classical machine learning algorithms in order to determine the algorithm that would improve prediction of student performance. In this quantitative study, an experimental research design was used. Experiments were set up using feature selection on a publicly
The course introduces the students into the field of artificial intelligence and gives the necessary basis for designing machine control algorithms. It advances the knowledge of state space search algorithms by including uncertainty in state transition. Students are introduced into reinforcement learning for solving problems when the state transitions are unknown, which also connects the artificial intelligence and cybernetics fields. Bayesian decision task introduces supervised learning. Learning from data is demonstrated on a linear classifier. Students practice the algoritms in computer labs. ...
TY - JOUR. T1 - Detection of breast cancer with mammography. T2 - Effect of an artificial intelligence support system. AU - Rodríguez-Ruiz, Alejandro. AU - Krupinski, Elizabeth A. AU - Mordang, Jan Jurre. AU - Schilling, Kathy. AU - Heywang-Köbrunner, Sylvia H.. AU - Sechopoulos, Ioannis. AU - Mann, Ritse M.. PY - 2019/3/1. Y1 - 2019/3/1. N2 - Purpose: To compare breast cancer detection performance of radiologists reading mammographic examinations unaided versus supported by an artificial intelligence (AI) system. Materials and Methods: An enriched retrospective, fully crossed, multireader, multicase, HIPAA-compliant study was performed. Screening digital mammographic examinations from 240 women (median age, 62 years; range, 39-89 years) performed between 2013 and 2017 were included. The 240 examinations (100 showing cancers, 40 leading to false-positive recalls, 100 normal) were interpreted by 14 Mammography Quality Standards Act-qualified radiologists, once with and once without AI support. ...
Challenges for Socially-Beneficial Artificial Intelligence. Daniel S. Weld. University of Washington. Stephen Hawking, Bill Gates, and other luminaries warn that an intelligence explosion may lead to the extinction of humanity at the hands of rampant robots. At the same time, many pundits see a prosperous future in which self-driving cars reduce highway fatalities , while AI advisors improve medical care and minimize malpractice. Weld argues that the utopian outcome is more likely, but only if we address several key social and technical challenges.. Daniel S. Weld is Thomas J. Cable / WRF Professor of Computer Science & Engineering and Entrepreneurial Faculty Fellow at the University of Washington. After formative education at Phillips Academy, he received bachelors degrees in both Computer Science and Biochemistry at Yale University in 1982. He landed a Ph.D. from the MIT Artificial Intelligence Lab in 1988, received a Presidential Young Investigators award in 1989, an Office of Naval ...
HVAC systems are used in buildings to provide a comfortable thermal environment to the occupants. They are one of the most significant sources of energy consumption in buildings. While thermal comfort level tends to be different among individuals, traditional HVAC systems are operated based on fixed setpoints and do not automatically consider the changing building conditions. With traditional HVAC systems, users have to adjust the thermal levels manually. Other than that, indoor activities also affect the proper optimization of these systems. More ventilation would be required in a kitchen space than in the workplace. Continually adjusting the settings is a difficult task. These situations can effectively be tackled by the use of Artificial Intelligence (AI). Artificial Intelligence can be integrated into the HVAC systems to improve their efficiency and minimize energy consumption. Here, we will discuss how AI can help boost the performance of HVAC systems.. ...
Other chapters in this book offer more technical discussions on some computational intelligence techniques including those that were not reviewed in this chapter. Computational intelligence is a collection of computational models and tools, whose classification, clusterization, optimization, prediction, reasoning, and approximation capabilities have been improved incrementally and continuously. There are already many computational intelligence techniques or combinations of the techniques. It is always possible to find alternative techniques to address a specific earth and environmental problem. Environ Manage 51:267-277 Riff MC, Alfaro T, Bonnaire X, Grandon C (2008) EA-MP: an evolutionary algorithm for a mine planning problem. In: Proceedings of IEEE congress on evolutionary computation, June 2008, pp 4011-4014 Rumelhart DE, Hinton GE, Williams RJ (1986) Learning internal representations by error propagation. In: Rumelhart DE, McClelland JL (eds) Parallel distributed processing: explorations in ...
The aim of this course is to build on Artificial Intelligence I, first by introducing more elaborate methods for planning within the symbolic tradition, but then by moving beyond the purely symbolic view of AI and presenting methods developed for dealing with the critical concept of uncertainty. The central tool used to achieve the latter is probability theory. The course continues to exploit the primarily algorithmic and computer science-centric perspective that informed Artificial Intelligence I. The course aims to provide further tools and algorithms required to produce AI systems able to exhibit limited human-like abilities, with an emphasis on the need to obtain better planning algorithms, and systems able to deal with the uncertainty inherent in the environments that most real agents might be expected to perform within. ...
A new study, published in Nature by German scientists from Jena and Hamburg, with lead author Prof. Markus Reichstein, managing director at the Max Planck Institute for Biogeochemistry (MPI-BGC) and co-author Prof. Bjorn Stevens, director and head of the department The Atmosphere in the Earth System at the Max Planck Institute for Meteorology (MPI-M), shows that artificial intelligence (AI) can help to better understand climate and the Earth system. The scientists show that specifically deep learning has thus far only partially exhausted its potential for understanding the Earth system. In particular, complex dynamic processes such as hurricanes, fire propagation, and vegetation dynamics can be better described with the help of AI. As a result, climate and Earth system models will be improved, with novel hybrid models combining artificial intelligence and physical modelling playing an important role. The scientists contend that detection and early warning of extreme events as well as seasonal ...
10 accredited schools offering Artificial Intelligence program in USA. Find complete list of Artificial Intelligence schools offers graduate and under graduate degree.
This book constitutes the refereed proceedings of the 16th Conference on Artificial Intelligence in Medicine, AIME 2017, held in Vienna, Austria, in June 2017.
The Artificial Intelligence Society is an independent and voluntary technological society formed in 2018 with the aim of promoting and disseminating Artificial Intelligence technology across the Kingdom. Main objectives of the society are as follows:. ...
Join Eminent Scientists, Entrepreneurs and Engineers from Europe, USA (America), Asia Pacific, Middle East to the Artificial Intelligence Conferences and Data Mining Conferences happening from April 16-17, 2018 Las Vegas,USA
In mathematics, casually speaking, a mixture of two functions. In machine learning, a convolution mixes the convolutional filter and the input matrix in order to train weights.. The term convolution in machine learning is often a shorthand way of referring to either convolutional operation or convolutional layer.. Without convolutions, a machine learning algorithm would have to learn a separate weight for every cell in a large tensor. For example, a machine learning algorithm training on 2K x 2K images would be forced to find 4M separate weights. Thanks to convolutions, a machine learning algorithm only has to find weights for every cell in the convolutional filter, dramatically reducing the memory needed to train the model. When the convolutional filter is applied, it is simply replicated across cells such that each is multiplied by the filter.. ...
TY - JOUR. T1 - Predicting diabetes mellitus using SMOTE and ensemble machine learning approach. T2 - The Henry Ford ExercIse Testing (FIT) project. AU - Alghamdi, Manal. AU - Al-Mallah, Mouaz. AU - Keteyian, Steven. AU - Brawner, Clinton. AU - Ehrman, Jonathan. AU - Sakr, Sherif. PY - 2017/7. Y1 - 2017/7. N2 - Machine learning is becoming a popular and important approach in the field of medical research. In this study, we investigate the relative performance of various machine learning methods such as Decision Tree, Naïve Bayes, Logistic Regression, Logistic Model Tree and Random Forests for predicting incident diabetes using medical records of cardiorespiratory fitness. In addition, we apply different techniques to uncover potential predictors of diabetes. This FIT project study used data of 32,555 patients who are free of any known coronary artery disease or heart failure who underwent clinician-referred exercise treadmill stress testing at Henry Ford Health Systems between 1991 and 2009 and ...
Abstract: In this study, we introduce a novel machine learning model hidden Markov support vector machine for protein binding site prediction. The model treats the protein binding site prediction as a sequential labelling task based on the maximum margin criterion. Common features derived from protein sequences and structures, including protein sequence profile and residue accessible surface area, are used to train hidden Markov support vector machine. When tested on six data sets, the method based on hidden Markov support vector machine shows better performance than some state-of-the-art methods, including artificial neural networks, support vector machines and conditional random field. Furthermore, its running time is several orders of magnitude shorter than that of the compared methods.The improved prediction performance and computational efficiency of the method based on hidden Markov support vector machine can be attributed to the following three factors. Firstly, the relation between ...
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Causality has been a subject of study for a long time. Often causality is confused with correlation. Human intuition has evolved such that it has learned to identify causality through correlation. In this book, four main themes are considered and these are causality, correlation, artificial intelligence and decision making. A correlation machine is defined and built using multi-layer perceptron network, principal component analysis, Gaussian Mixture models, genetic algorithms, expectation maximization technique, simulated annealing and particle swarm optimization. Furthermore, a causal machine is defined and built using multi-layer perceptron, radial basis function, Bayesian statistics and Hybrid Monte Carlo methods. Both these machines are used to build a Granger non-linear causality model. In addition, the Neyman-Rubin, Pearl and Granger causal models are studied and are unified. The automatic relevance determination is also applied to extend Granger causality framework to the non-linear domain. The
TY - JOUR. T1 - Predictive vaccinology. T2 - 6th International Conference on Intelligent Data Engineering and Automated Learning - IDEAL 2005. AU - Bozic, Ivana. AU - Zhang, Guang Lan. AU - Brusic, Vladimir. PY - 2005/1/1. Y1 - 2005/1/1. N2 - Promiscuous human leukocyte antigen (HLA) binding peptides are ideal targets for vaccine development. Existing computational models for prediction of promiscuous peptides used hidden Markov models and artificial neural networks as prediction algorithms. We report a system based on support vector machines that outperforms previously published methods. Preliminary testing showed that it can predict peptides binding to HLA-A2 and -A3 supertype molecules with excellent accuracy, even for molecules where no binding data are currently available.. AB - Promiscuous human leukocyte antigen (HLA) binding peptides are ideal targets for vaccine development. Existing computational models for prediction of promiscuous peptides used hidden Markov models and artificial ...
Model-based virtual screening plays an important role in the early drug discovery stage. The outcomes of high-throughput screenings are a valuable source for machine learning algorithms to infer such models. Besides a strong performance, the interpretability of a machine learning model is a desired property to guide the optimization of a compound in later drug discovery stages. Linear support vector machines showed to have a convincing performance on large-scale data sets. The goal of this study is to present a heat map molecule coloring technique to interpret linear support vector machine models. Based on the weights of a linear model, the visualization approach colors each atom and bond of a compound according to its importance for activity. We evaluated our approach on a toxicity data set, a chromosome aberration data set, and the maximum unbiased validation data sets. The experiments show that our method sensibly visualizes structure-property and structure-activity relationships of a linear support
Although supervised learning requires a labeled dataset, obtaining labels from experts is generally expensive. For this reason, crowdsourcing services are attracting attention in the field of machine learning as a way to collect labels at relatively low cost. However, the labels obtained by crowdsourcing, i.e., from non-expert workers, are often noisy. A number of methods have thus been devised for inferring true labels, and several methods have been proposed for learning classifiers directly from crowdsourced labels, referred to as learning from crowds. A more practical problem is learning from crowdsourced labeled data and unlabeled data, i.e., semi-supervised learning from crowds. This paper presents a novel generative model of the labeling process in crowdsourcing. It leverages unlabeled data effectively by introducing latent features and a data distribution. Because the data distribution can be complicated, we use a deep neural network for the data distribution. Therefore, our model can ...
Roy Labban is the director of computer modeling and simulation in the Information Systems Department at Consolidated Contractors Company (CCC), which is ranked among the top 20 international contractors in 2017 by ENR. Roy has 20+ years of experience in software engineering and database application development, business intelligence and analytics, and computer modeling and simulation. Roy is the cofounder and managing partner of a boutique consulting firm focused on delivering business intelligence and analytics for higher education enrollment management. Roy is also the founder and director of a postgraduate coding bootcamp diploma program focusing on new technologies such as the blockchain, artificial intelligence, machine learning, and mobile apps. Roy serves as a member of the Industry Advisory Board of the Computer Science Program (ABET Accredited) at the American University of Science and Technology. He is also a part-time university instructor teaching graduate level courses on computer
Eventbrite - Omni212 presents Colombo Prerequisites to Learning Artificial Intelligence | AI | Machine Learning | Deep Learning | IT Training | Disruptive Technologies - Saturday, December 16, 2017 | Sunday, January 14, 2018 at Instructor Led Online | Video Conference, Colombo, Colombo. Find event and ticket information.
TY - JOUR. T1 - Accuracy of an Artificial Intelligence Deep Learning Algorithm Implementing a Recurrent Neural Network with Long Short-term Memory for the Automated Detection of Calcified Plaques from Coronary Computed Tomography Angiography. AU - Fischer, Andreas M.. AU - Eid, Marwen. AU - De Cecco, Carlo N.. AU - Gulsun, Mehmet A.. AU - Van Assen, Marly. AU - Nance, John. AU - Sahbaee, Pooyan. AU - De Santis, Domenico. AU - Bauer, Maximilian J.. AU - Jacobs, Brian E.. AU - Varga-Szemes, Akos. AU - Kabakus, Ismail M.. AU - Sharma, Puneet. AU - Jackson, Logan J.. AU - Schoepf, U. Joseph. PY - 2020/1/1. Y1 - 2020/1/1. N2 - Purpose: The purpose of this study was to evaluate the accuracy of a novel fully automated deep learning (DL) algorithm implementing a recurrent neural network (RNN) with long short-term memory (LSTM) for the detection of coronary artery calcium (CAC) from coronary computed tomography angiography (CCTA) data. Materials and Methods: Under an IRB waiver and in HIPAA compliance, a ...
Researchers proving how machine learning can help detect dangerous polyps.The South Australian researchers are finding new ways to better pinpoint suspicious polyps using artificial intelligence in the fight against deadly bowel cancer.
Ensemble learning can improve the performance of individual classifiers by combining their decisions. The sparseness of ensemble learning has attracted much attention in recent years. In this paper, a novel multiobjective sparse ensemble learning (MOSEL) model is proposed. Firstly, to describe the ensemble classifiers more precisely the detection error trade-off (DET) curve is taken into consideration. The sparsity ratio (sr) is treated as the third objective to be minimized, in addition to false positive rate (fpr) and false negative rate (fnr) minimization. The MOSEL turns out to be augmented DET (ADET) convex hull maximization problem. Secondly, several evolutionary multiobjective algorithms are exploited to find sparse ensemble classifiers with strong performance. The relationship between the sparsity and the performance of ensemble classifiers on the ADET space is explained. Thirdly, an adaptive MOSEL classifiers selection method is designed to select the most suitable ensemble classifiers ...
Title:New Computational Tool Based on Machine-learning Algorithms for the Identification of Rhinovirus Infection-Related Genes. VOLUME: 22 ISSUE: 10. Author(s):Yan Xu, Yu-Hang Zhang, JiaRui Li, Xiao Y. Pan, Tao Huang* and Yu-Dong Cai*. Affiliation:School of Life Sciences, Shanghai University, Shanghai 200444, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, School of Life Sciences, Shanghai University, Shanghai 200444, BASF & IDLab, Ghent University, Ghent, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, School of Life Sciences, Shanghai University, Shanghai 200444. Keywords:Human Rhinovirus, maximum relevance minimum redundancy, support vector machine, incremental feature selection, OTOF, SOCS1.. Abstract:. Background: Human rhinovirus has different identified serotypes and is the most common cause of cold in humans. To ...
Projects in the REU in Computational Sensing for Human-aware AI [Alm, Bailey, Geigel, Huenerfauth, Ptucha, Shinohara]: The REU Site in Computational Sensing for Human-centered Artificial Intelligence recognizes that as the boundaries between HCI and AI blur, and AI grows increasingly agile and pervasive, the next generation of computational scientists must be capable of responsibly and effectively leveraging a spectrum of sensing data from data-generating humans. With this focus, the REU Site will expand its trajectory as an attractor for highly diverse students who will gain experience with sensing hardware and software towards transformative advances in intelligent systems focused on human behaviors and cognitive processes. Enabling diverse stakeholders early in their careers to discover how to collect, fuse, make inference with, and visualize multimodal human data can transform how humans and machines engage and collaborate. The research in the REU Site will address two limitations in AI: ...
Tumor classification and segmentation from brain computed tomography image data is an important but time consuming task performed manually by medical experts. Automating this process is challenging due to the high diversity in appearance of tumor tissue among different patients and in many cases, similarity between tumor and normal tissue. This paper deals with an efficient segmentation algorithm for extracting the brain tumors in computed tomography images using Support Vector Machine classifier. The objective of this work is to compare the dominant grey level run length feature extraction method with wavelet based texture feature extraction method and SGLDM method. A dominant gray level run length texture feature set is derived from the region of interest (ROI) of the image to be selected. The optimal texture features are selected using Genetic Algorithm. The selected optimal run length texture features are fed to the Support Vector Machine classifier (SVM) to classify and segment the tumor from brain
In the paper we present some guidelines for the application of nonparametric statistical tests and post-hoc procedures devised to perform multiple comparisons of machine learning algorithms. We emphasize that it is necessary to distinguish between pairwise and multiple comparison tests. We show that the pairwise Wilcoxon test, when employed to multiple comparisons, will lead to overoptimistic conclusions. We carry out intensive normality examination employing ten different tests showing that the output of machine learning algorithms for regression problems does not satisfy normality requirements. We conduct experiments on nonparametric statistical tests and post-hoc procedures designed for multiple 1 × N and N × N comparisons with six different neural regression algorithms over 29 benchmark regression data sets. Our investigation proves the usefulness and strength of multiple comparison statistical procedures to analyse and select machine learning algorithms ...
PhD thesis.. Dorian Šuc and Ivan Bratko (2005) Combining Learning Constraints and Numerical Regression. In: 19th Int. Joint Conf. on Artificial Intelligence, IJCAI-05, 30 July - 5 August 2005, Edinburgh, Scotland.. Nancy Van Driessche and Janez Demsar and Ezgi O Booth and Paul Hill and Peter Juvan and Blaz Zupan and Adam Kuspa and Gad Shaulsky (2005) Epistasis analysis with global transcriptional phenotypes. Nature Genetics, 37 (5). pp. 471-477.. Aleks Jakulin and Martin Možina and Janez Demšar and Ivan Bratko and Blaz Zupan (2005) Nomograms for Visualizing Support Vector Machines. In: SIGKDD05 Chicago, August 2005, Illinois, USA.. Gregor Leban and Minca Mramor and Ivan Bratko and Blaz Zupan (2005) Simple and Effective Visual Models for Gene Expression Cancer Diagnostics. In: ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, August 21-24, 2005, Chicago, IL, USA.. Aleks Jakulin (2004) Modelling Modelled.. Aleks Jakulin and Wray Buntine (2004) Analyzing the US Senate ...
Description:. Pulmonary embolism is a common cardiovascular emergency with approximately 600,000 incidents and 200,000 deaths occurring annually in the United States. CT pulmonary angiography (CTPA) has become the reference standard for pulmonary embolism diagnosis, but this technique has several issues with interpretation of the intricate branching structure of the pulmonary vessels, artifacts that may obscure or mimic embolisms, suboptimal contrast, and inhomogeneities. To overcome these shortcomings, researchers at Arizona State University have developed a machine learning-based approach for automatically detecting the pulmonary trunk. By using a cascaded Adaptive Boosting machine learning algorithm with a large number of digital image object recognition features, this method automatically identifies the pulmonary trunk by sequentially scanning the CTPA images and classifying each encountered sub-image with the trained classifier. This approach outperforms existing anatomy-based approaches. ...
JONESBORO - The AI (Artificial Intelligence) Group at Arkansas State University finished in third place in the Multiple Myeloma DREAM Challenge, a machine-learning competition.. The research group was very pleased with the third-place performance in competition with the 290 teams participating internationally; in fact, their submission was statistically tied with the first place awardees.. Members of the A-State AI group are computer science faculty members Dr. Xiuzhen Huang, Dr. Jason Causey and Dr. Jake Qualls, along with senior scientist Dr. Wei Dong. Huang was introduced in December as an Arkansas Research Alliance Fellow for 2019.. The DREAM Challenge was organized by Celgene, the Multiple Myeloma Research Foundation (MMRF), and Sage Bionetworks. The A-State AI group learned about the competition from professional collaborators.. We entered the competition to train our team and to keep up with the most advanced AI and machine learning technologies, Qualls said. We were also interested in ...
The effective application of current decision tree and influence diagram software requires a relatively high level of sophistication in the theory and practice of decision analysis. Research on intelligent decision systems aims to lower the cost and amount of training required to use these methods through the use of knowledge-based systems; however, application prototypes implemented to date have required time-consuming and tedious handcrafting of knowledge bases. This paper describes the development of DDUCKS, an ?open architecture? problem-modeling environment that integrates components from Axotl, a knowledge-based decision analysis workbench, with those of Aquinas, a knowledge acquisition workbench based on personal construct theory. The knowledge base tools in Axotl can be configured with knowledge to provide guidance and help in formulating, evaluating, and refining decision models represented in influence diagrams. Knowledge acquisition tools in DDUCKS will allow the knowledge to be ...
Building a Software Pipeline for Developing and Evaluating Time-Series Machine Learning Models Using Electronic Health Record Data ...
Artificial intelligence, naturally: Smart agents technology. Smart agents technology is the only solution that overcomes the limits of the legacy machine learning technologies to allow personalization, adaptability and self-learning. Simply put, a smart agent can hold entire conversations using natural language technology that understands the intent and meaning of customer questions. But there is more: It creates a virtual representation of every entity that learns and builds a profile from the entitys actions and activities. For payments, a smart agent is associated with each individual cardholder, merchant or terminal. The smart agents associated to an entity (such as a card or a merchant) learn in real time from every transaction and collect specific and unique behaviors over time. There are as many smart agents as active entities in the system. Decision making becomes specific to each entity and no longer relies on universally applied logic, regardless of their individual characteristics. ...
Detrital monazite geochronology has been used in provenance studies. However, there are complexities in the interpretation of age spectra due to their wide occurrence in both igneous and metamorphic rocks. We use the multinomial logistic regression (MLR) and cross-validation (CV) techniques to establish a geochemical discrimination of monazite source rocks. The elemental abundance-based geochemical discrimination was tested by selecting 16 elements from granitic and metamorphic rocks. The MLR technique revealed that light rare earth elements (REEs), Eu, and some heavy REEs are important discriminators that reflect elemental fractionation during magmatism and/or metamorphism. The best model yielded a discrimination rate of ~97%, and the CV method validated this approach. We applied the discrimination model to detrital monazites from African rivers. The detrital monazites were mostly classified as granitic and of garnet-bearing metamorphic origins; however, their proportion of metamorphic origin was
The immune system has evolved to sense invading pathogens, control infection, and restore tissue integrity. Despite symptomatic variability in patients, unequivocal evidence that an individuals immune system distinguishes between different organisms and mounts an appropriate response is lacking. We here used a systematic approach to characterize responses to microbiologically well-defined infection in a total of 83 peritoneal dialysis patients on the day of presentation with acute peritonitis. A broad range of cellular and soluble parameters was determined in peritoneal effluents, covering the majority of local immune cells, inflammatory and regulatory cytokines and chemokines as well as tissue damage-related factors. Our analyses, utilizing machine-learning algorithms, demonstrate that different groups of bacteria induce qualitatively distinct local immune fingerprints, with specific biomarker signatures associated with Gram-negative and Gram-positive organisms, and with culture-negative ...
Objective To investigate the discriminative capabilities of different machine learning-based classification models on the differentiation of small (< 4 cm) renal angiomyolipoma without visible fat...
Dermatology researchers in the US have developed an artificial intelligence program that uses histology samples to identify which patients with melanoma will respond to immunotherapy. They say the system offers a better performance than genomic biomarkers such as PD-L1, which may be modified during the course of immune checkpoint inhibitor therapy. Instead, their machine learning .... ...
IBM Research and the Department of Brain and Cognitive Sciences at the Massachusetts Institute of Technology have joined forces to further develop the scientific field of machine vision - a core aspect of artificial intelligence. Big Blue and MIT will build the IBM-MIT Laboratory for Brain-inspired Multimedia Machine Comprehension, or BM3C, in Cambridge, Mass. Together they plan to develop cognitive computing systems that mimic the human ability to understand and integrate input from multiple sources for use in a variety of computer applications in industries such as healthcare, education, and entertainment. MIT researchers will collaborate with IBM scientists and engineers who will provide technology expertise and advances from the IBM Watson platform. The BM3C will address technical challenges around both pattern recognition and prediction methods in the field of machine ...
Novel embryo development parameters analyzed with the use of time-lapse technology were used as input data for a predictive model of implantation potential based on artificial intelligence.
Lo and behold, the system began performing as advertised. The lucky break was a symptom of a troubling trend, according to Pineau. Neural networks, the technique thats given us Go-mastering bots and text generators that craft classical Chinese poetry, are often called black boxes because of the mysteries of how they work. Getting them to perform well can be like an art, involving subtle tweaks that go unreported in publications. The networks also are growing larger and more complex, with huge data sets and massive computing arrays that make replicating and studying those models expensive, if not impossible for all but the best-funded labs.. Is that even research anymore? asks Anna Rogers, a machine-learning researcher at the University of Massachusetts. Its not clear if youre demonstrating the superiority of your model or your budget.. Pineau is trying to change the standards. Shes the reproducibility chair for NeurIPS, a premier artificial intelligence conference. Under her watch, the ...
The field of computer-aided diagnosis has recently made progress in the diagnosing of Alzheimers disease (AD) from magnetic resonance images (MRI) of the brain. Lahmiri and Boukadoum (2013) have research this topic since 2011, and in 2013 they presented a system for automatic detection of AD based on machine learning classification. Their proposed system achieved a classification accuracy of 100% (2013, p. 1507) using support vector machines with quadratic kernel classifiers. The MRI scans were first translated to 1-dimensional signals, from which three features were extracted to measure the signals self-affinity. These three features were Hursts exponent, the total fluctuation energy of a detrended fluctuational analysis and the same analysis scaling exponent. The results of their study were validated using a dataset of 23 MRI scans from brains with AD and normal brains.. This report makes an attempt at implementing the method proposed by Lahmiri and Boukadoum in 2013 and evaluating its ...
Machine learning is being used more frequently across a wide range of social domains. These algorithms are already trusted to make impactful decisions on topics including loan grades, personalized medicine, hiring, and policing. Unfortunately, many of these models have recently been criticized for discrimination against individuals of different races or sexes. This is particularly problematic from a legal perspective and has led to challenges over the use of these algorithms. In this thesis, we consider what would be needed to make a machine learning model fair according to the law. Special emphasis is placed on the COMPAS algorithm, a black-box machine learning model used for criminal recidivism prediction that has recently been shown to have a discriminatory impact for defendants of different races. We test two algorithmic methods in adversarial examples and adversarial networks that show significant progress in meeting the proposed legal requirements of fairness. ...
... and universal artificial intelligence curriculum.[16] On the grounds, the Luce Memorial Chapel (designed by architects Chen Chi ...
Artificial intelligence[edit]. While approving of the increase in efficiency that humans reap by using resources such as expert ... Artificial Intelligence. Massachusetts: Massachusetts Institute of Technology. ISBN 0-262-08259-4 (reprint of 1981 publication ... his father was a covert counter-intelligence agent with the Office of Strategic Services posing as a cultural attaché to the ... and weighing of the considerations that do occur to the subject is a matter of intelligence making the difference. ...
"Artificial Intelligence in Healthcare" (PDF). Cerner.. *^ a b Joynson; Berg; Ahmed (May 2018). "Artificial intelligence (AI) in ... Applications of Artificial Intelligence[edit]. AI brings many benefits to the healthcare industry. AI helps to detect diseases ... Artificial Intelligence (AI) is a program that enables computers to sense, reason, act and adapt. AI is not new, but it is ... Artificial Intelligence and machine learning will be constantly improving and developing as it receives new data. Alerts will ...
Levels of analysis in artificial intelligence[edit]. In cognitive science and artificial intelligence, it is common to refer to ... At any given time, a researcher may be focusing on (1) what some aspect of intelligence needs to compute, (2) what algorithm it ...
Artificial intelligence[edit]. On 8 July 2017, the Chinese State Council announced plans to turn China into the world leader in ... "China sets out road map to lead world in artificial intelligence by 2030". South China Morning Post. Retrieved July 24, 2017.. ... artificial intelligence (AI) by 2030, seeking to make the industry worth 1 trillion yuan.[91] The State Council published a ... Intelligence agencies suspect that thousands of Western companies may have been affected by data breaches that can be traced ...
Artificial intelligence or life[edit]. If artificial intelligences, intelligent and self-aware system of hardware and software ... because of their apparent intelligence and intricate social rules. The idea of extending personhood to all animals has the ...
Artificial intelligence[edit]. Further information: Ablation (artificial intelligence). In artificial intelligence (AI), ...
Artificial intelligence[edit]. Some features of IDEs can benefit from advances in AI.[16] In particular, one can collect ... "IDE 2.0: collective intelligence in software development". doi:10.1145/1882362.1882374. S2CID 7637561.. Cite journal requires , ...
Planning and artificial intelligence[edit]. A novel approach to test suite generation, adapted from a CLI technique[4] involves ... Planning is a well-studied technique from the artificial intelligence (AI) domain that attempts to solve problems that involve ...
Split from artificial intelligence[edit]. Artificial intelligence (AI) was founded as a distinct discipline at the Dartmouth ... artificial intelligence was born at a conference at dartmouth in 1956 that was organized by McCarthy, Minsky, rochester, and ... Johnston, John (2008). The allure of machinic life : cybernetics, artificial life, and the new AI. Cambridge, MA: MIT Press. ... The first artificial automatic regulatory system was a water clock, invented by the mechanician Ktesibios; based on a tank ...
2 Artificial intelligence. *3 Cloud and database services. *4 Digital media. *5 Financial technology (Fintech) ...
In shared decision making and artificial intelligence[edit]. See also: Shared decision-making and Artificial intelligence in ... Artificial intelligence is being used more frequently in patient participatory healthcare. Role of entrepreneurship[edit]. ... Examples of artificial intelligence (AI) technology that is being used in healthcare include IBM's Watson Health, which is ... artificial intelligence in healthcare (AI), the role of entrepreneurs, the value of patient participation in precision medicine ...
Artificial Intelligence[edit]. IMEC performs advanced research on artificial intelligence[14] and was awarded 750.000 USD twice ...
... research[edit]. Artificial general intelligence[30] (AGI) describes research that aims to ... Shapiro, Stuart C. (1992). Artificial Intelligence In Stuart C. Shapiro (Ed.), Encyclopedia of Artificial Intelligence (Second ... Lighthill, Professor Sir James (1973), "Artificial Intelligence: A General Survey", Artificial Intelligence: a paper symposium ... For a discussion of some definitions of intelligence used by artificial intelligence researchers, see philosophy of artificial ...
Philosophy of artificial intelligence. Notes[edit]. *^ Dreyfus was one of the only non-computer scientists asked for a comment ... The grandiose promises of artificial intelligence[edit]. In Alchemy and AI (1965) and What Computers Can't Do (1972), Dreyfus ... Dreyfus' four assumptions of artificial intelligence research[edit]. In Alchemy and AI and What Computers Can't Do, Dreyfus ... Alchemy and Artificial Intelligence[edit]. In 1965, Dreyfus was hired (with his brother Stuart Dreyfus' help) by Paul Armer to ...
... proceedings of the 9th European Conference on Artificial Intelligence. Pitman. pp. 385-391. ISBN 978-0273088226. .. ...
... was a British researcher in artificial intelligence.[8] During World War II, Michie worked for the Government Code and Cypher ... The machine intelligence unit predated the university's computer science unit. He remained at Edinburgh until 1985,[13] when he ... 1923-7 July 2007), Professor of Machine Intelligence, Edinburgh University, 1967-84, Professor Emeritus, since 1984". Who Was ... Michie was director of the University of Edinburgh's Department of Machine Intelligence and Perception (previously the ...
Hubert Dreyfus: philosopher and critic of artificial intelligence. *Karen Elliott House: Chairman of the Board, 2009-present, ... Cliff Shaw: inventor of the linked list and co-author of the first artificial intelligence program ... in computing and in artificial intelligence. RAND researchers developed many of the principles that were used to build the ... Alex Roland and Philip Shiman, Strategic Computing: DARPA and the Quest for Machine Intelligence, 1983-1993, The MIT Press, ...
"Some philosophical problems from the standpoint of artificial intelligence" (PDF). Machine Intelligence. 4: 463-502.. ... Artificial Intelligence. 19: 17-37. doi:10.1016/0004-3702(82)90020-0. Archived from the original (PDF) on 2013-12-27. Retrieved ... One of the first applications to use the term artificial intelligence was the Logic Theorist system developed by Allen Newell, ... There has always been a strong influence from mathematical logic on the field of artificial intelligence (AI). From the ...
... (ILP) is a subfield of symbolic artificial intelligence which uses logic programming as a uniform ... Shapiro, Ehud Y. "The model inference system." Proceedings of the 7th international joint conference on Artificial intelligence ... Artificial Intelligence. 114 (1-2): 283-296. doi:10.1016/s0004-3702(99)00067-3.. ; here: Sect.2.1 ... Plotkin, Gordon D. (1970). Meltzer, B.; Michie, D. (eds.). "A Note on Inductive Generalization". Machine Intelligence. 5: 153- ...
In artificial intelligence, knowledge-based agents draw on a pool of logical sentences to infer conclusions about the world. At ...
IBM Watson: artificial intelligence arrives at the Museum of Anthropology. Aban Tech. October 31, 2017. Retrieved May 11, 2018 ... "Artificial Intelligence Course Creates AI Teaching Assistant". Georgia Tech News. Georgia Tech News. Retrieved 26 September ... Artificial intelligence computer system made by IBM. "IBM Watson" redirects here. For the IBM laboratory, see Thomas J. Watson ... Artificial Intelligence. 199: 93-105. doi:10.1016/j.artint.2012.06.009.. *^ a b Hale, Mike (February 8, 2011). "Actors and ...
Artificial Intelligence. *ASSIST. *BCSWomen (Women in IT). *British APL Association. *Business Change ...
Artificial intelligence. Hidden categories: *All articles with unsourced statements. *Articles with unsourced statements from ...
Rodney Brooks (1991). "Intelligence without representation". Artificial Intelligence. 47 (1-3): 139-159. CiteSeerX 10.1.1.308. ... At the same time, computer scientists working in the field of artificial intelligence have pursued the goal of creating digital ... The Turing test is commonly cited in discussions of artificial intelligence as a proposed criterion for machine consciousness; ... In the literature concerning artificial intelligence, Searle's essay has been second only to Turing's in the volume of debate ...
In 2007, he co-founded the DBpedia knowledge graph project.[2][3][4] He also works on Symbolic Artificial Intelligence, in ... Jens Lehmann is a computer scientist, most noted for his work on knowledge graphs and Artificial Intelligence. He is a full ... Jens Lehmann is coordinating the Fraunhofer IAIS Dresden lab with a main focus on Conversational Artificial Intelligence.[14] ...
Centre for Artificial Intelligence & Robotics (CAIR) Artificial Intelligence & Robotics Centre for Fire, Explosives & ... Communication-Centric Intelligence Satellite (CCI-Sat)[edit]. Communication-Centric Intelligence Satellite is an advanced ... Developed by DRDO's Centre for Artificial Intelligence & Robotics, the system comprises computers and intelligent terminals ... The DRDO is also developing an all new ESM project in cooperation with the Indian Air Force's Signals Intelligence Directorate ...
"Journal of Artificial Intelligence Research. 4: 237-285. arXiv:cs/9605103. doi:10.1613/jair.301. S2CID 1708582. Archived from ... Russell, Stuart J.; Norvig, Peter (2010). Artificial intelligence : a modern approach (Third ed.). Upper Saddle River, New ... Reinforcement Learning and Artificial Intelligence (RLAI, Rich Sutton's lab at the University of Alberta) ... Advances in Artificial Intelligence, Lecture Notes in Computer Science, 7006, Springer, pp. 335-346, ISBN 978-3-642-24455-1. ...
"Artificial Intelligence Review. 19 (4): 285-330. doi:10.1023/A:1022850703159. . *^ a b Adomavicius, G.; Tuzhilin, A. (June 2005 ... In Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence (UAI'98).. ... Proceedings of the Eighteenth National Conference on Artificial Intelligence (AAAI-2002), pp. 187-192, Edmonton, Canada, July ... and artificial neural networks in order to estimate the probability that the user is going to like the item.[45] ...
J. Hirschberg (1993). "Pitch Accent in Context: Predicting Intonational Prominence from Text". Artificial Intelligence. 63 (1-2 ...
... artificial neural networks, artificial intelligence and computational learning theory.[5][6][7][8][9][10][11][12] ... "Turing centenary: Is the brain a good model for machine intelligence?". Nature. 482 (7386): 462-463. 2012-02-22. doi:10.1038/ ... These connections are, unlike most artificial neural networks, sparse and usually specific. It is not known how information is ... This model is still popular today for artificial neural networks studies because of its simplicity (see a recent review[17]). ...
In Expert systems and artificial intelligence: the need for information about data. Library Association Report, London, March, ... Mackintosh, N. J. (1998). IQ and Human Intelligence. Oxford: Oxford University Press. pp. 30-31. ISBN 978-0-19-852367-3. . In ... Eysenck, Hans (1998). Intelligence: A New Look. New Brunswick (NJ): Transaction Publishers. pp. 24-25. ISBN 978-1-56000-360-1. ... Bartholomew, David J. (2004). Measuring Intelligence: Facts and Fallacies. Cambridge: Cambridge University Press. p. 50. ISBN ...
... after artificial general intelligence is invented in which progress is nearly infinite; hence the term. Estimates for the date ... the artificial intelligence epoch, and (6) the universal colonization epoch. Going from one epoch to the next is a Singularity ... "Machine Intelligence Research Institute. Retrieved November 11, 2016.. *^ Kurzweil, Ray (2005). "The Six Epochs". The ...
... a specialist in artificial intelligence, declared that "a new species, Robo sapiens, are emerging". ...
IEEE Transactions on Pattern Analysis and Machine Intelligence. 23 (11): 1209-21. doi:10.1109/34.969113.. ... Examples are Retinex, an artificial neural network[7] or a Bayesian method.[8] ...
Embodied Artificial Intelligence: International Seminar, Dagstuhl Castle, Germany, July 7-11, 2003, Revised Selected Papers. ... Artificial life Artificial neural networks Brain-computer interface CoDi Cybernetics Neural ensemble Neural engineering ... Other studies have attempted to imprint signal patterns onto the networks via artificial stimulation. This can be done by ... where the neuronal networks are able to interact with their environment and receive at least some artificial sensory feedback. ...
... frequent use of artificial tears while awake is recommended, along with ointment and a patch or taping the eye closed when ... This was investigated by physicians David Snydman and Allen Steere of the Epidemic Intelligence Service, and by others from ...
"Acmite Market Intelligence. 2014. Retrieved 15 June 2014.. *^ Sastri, Vinny (2013). Plastics in Medical Devices: Properties, ... For example, initial models of the artificial cardiac pacemaker were external support devices that transmits pulses of ... are not required to undergo the same level of testing that higher risk devices such as artificial pacemakers undergo. ...
Artificial. intelligence. *Natural language processing. *Knowledge representation and reasoning. *Computer vision. *Automated ...
Russell, Stuart J.; Norvig, Peter (2003), Artificial Intelligence: A Modern Approach (2nd ed.), Upper Saddle River, New Jersey ... It is used widely in artificial intelligence, for reaching a goal state from a starting node. Choice of next node and starting ...
Such wheelchairs typically employ techniques from artificial intelligence, such as path-planning. ...
Science of Artificial Neural Networks. Citeseer. 1710: 714-24. Bibcode:1992SPIE.1710..714G. doi:10.1117/12.140132. However, ... Cartesian dualism holds that the mind is a nonphysical substance, the seat of consciousness and intelligence, and is not ... 1992). "A Platform for Evolving Genetic Automata for Text Segmentation (GNATS)". Science of Artificial Neural Networks. ...
Artificial intelligence * sw:Akili bandia. ASEAN * sw:ASEAN. Ashoka * sw:Ashoka. Asia * sw:Asia. Association football * sw: ...
Synthetic intelligence / Artificial intelligence *Existential risk from artificial intelligence. *AI takeover. *Technological ...
... and weak artificial creativity. In: The Association for the Advancement of Artificial Intelligence (AAAI) ... natural or artificial. The concept is employed in work on artificial intelligence. The expression was introduced by Gerardo ... "Artificial intelligence turns $20 into $11,000 in Kentucky Derby bet". Newsweek. 2016-05-10. Retrieved 2017-01-20.. ... Bonabeau, Eric; Dorigo, Marco; Theraulaz, Guy (1999). Swarm Intelligence: From Natural to Artificial Systems. ISBN 0-19-513159- ...
Artificial Intelligence and Heuristic Methods in Bioinformatics. IOS Press. ISBN 1586032941.. *↑ Murray-Rust, P.; et al. (2005 ... "Proceedings of the Workshop on Software Engineering, Artificial Intelligence and Expert Systems for High Energy and Nuclear ... describen o uso de cromosomas artificiais de lévedo (YAC, Yeast Artificial Chromosome),[41] e Kulesh et al. sentan as bases dos ... intelixencia artificial,[8] química[9] e bioquímica[10] coas que o enxeñeiro informático soluciona problemas ao analizar datos ...
The Colt Car Company UK (who distribute Mitsubishi Motors) are in Cirencester, and Corin Group make artificial joints on the ... An aerial view of GCHQ's headquarters, 2004; the biggest employer in Gloucestershire is the intelligence agency GCHQ, who are ... Sir Arthur C. Clarke of Minehead invented the idea of artificial satellites; he sent a letter to Harry Wexler who then ... "artificial" construct. The large area of the region, stretching as it does from the Isles of Scilly to Gloucestershire, ...
Additional capabilities are expected to help drive this use of simulation to become common, such as Artificial Intelligence (AI ... artificial, human or a combination of the two, educational documents with detailed simulated animations, casualty assessment in ...
Russell, Stuart; Norvig, Peter (2002). Artificial Intelligence: A Modern Approach. Prentice Hall. p. 478. ISBN 0-13-790395-2. . ...
Artificial intelligence *Applications of artificial intelligence. *Progress in artificial intelligence. *Machine translation ...
Proceedings of the 20th Annual Conference of the Japanese Society for Artificial Intelligence.. ...
... traces its roots to the Pandemonium Architecture proposed by artificial intelligence pioneer Oliver ... Brooks, R.A., (1991). Intelligence without representation, Artificial Intelligence 47, 139-159 ... Not to be confused with collective intelligence or shared intelligence.. Collaborative intelligence characterizes multi-agent, ... "Artificial intelligence turns $20 into $11,000 in Kentucky Derby bet". Newsweek. 2016-05-10. Retrieved 2017-08-11.. ...
In psychological research on altruism, studies often observe altruism as demonstrated through prosocial behaviors such as helping, comforting, sharing, cooperation, philanthropy, and community service.[25] Research has found that people are most likely to help if they recognize that a person is in need and feel personal responsibility for reducing the person's distress. Research also suggests that the number of bystanders witnessing distress or suffering affects the likelihood of helping (the Bystander effect). Greater numbers of bystanders decrease individual feelings of responsibility.[23][29] However, a witness with a high level of empathic concern is likely to assume personal responsibility entirely regardless of the number of bystanders.[23] A feeling of personal responsibility or - moral norm - has also strongly been associated with other pro-social behaviors such as charitable giving.[30]. Many studies have observed the effects of volunteerism (as a form of altruism) on happiness and ...
... from artificial intelligence (AI) could be made useful on the World Wide Web. These included languages based on HTML (called ...
... and artificial intelligence.[4][5][6] Jordan was elected a member of the National Academy of Engineering in 2010 for ...
As the female manifestation of the supreme lord, she is also called Prakriti, the basic nature of intelligence by which the ... In this book, I break with past attempts in feminism and queer theory to dismiss femininity by characterizing it as "artificial ... with traits such as passivity and tenderness assigned to women and aggression and intelligence assigned to men.[21][22] Girls, ... "lesbian society destroys the artificial (social) fact constituting women as a 'natural group.' A lesbian society pragmatically ...
Gary Marcus, "Am I Human?: Researchers need new ways to distinguish artificial intelligence from the natural kind", Scientific ... The weaknesses of pure machine translation, unaided by human expertise, are those of artificial intelligence itself.[75] ... Gary Marcus, "Am I Human?: Researchers need new ways to distinguish artificial intelligence from the natural kind", Scientific ... Gary Marcus, "Am I Human?: Researchers need new ways to distinguish artificial intelligence from the natural kind", Scientific ...
Artificial general intelligence research[edit]. Artificial general intelligence[30] (AGI) describes research that aims to ... Shapiro, Stuart C. (1992). Artificial Intelligence In Stuart C. Shapiro (Ed.), Encyclopedia of Artificial Intelligence (Second ... Lighthill, Professor Sir James (1973), "Artificial Intelligence: A General Survey", Artificial Intelligence: a paper symposium ... For a discussion of some definitions of intelligence used by artificial intelligence researchers, see philosophy of artificial ...
Artificial Intelligence as a term implies that there is a "natural" intelligence we wish to replicate in the lab and then ... There is nothing in the term that implies that "intelligence" be human, but the implication is clear that such a thing as " ... "intelligence" exists and that we have some clue as to what it is. But it might not, and we dont. Read the rest here... ...
Various technologies under the general name of Artificial Intelligence (AI) can provide ways to organize this avalanche of ... The companys video intelligence API allows fining entities, content and moments, which can be broken down to the video shot or ... spoke about the value of combining data virtualization with metadata intelligence to improve performance, reduce costs and ...
... which collects all of our stories on artificial intelligence and filters them by sector, source data, end user, company, and ... Artificial Intelligence and the Gods Behind the Masks. In an excerpt from AI 2041: Ten Visions for Our Future, Kai-Fu Lee and ... A research paper that dubs some artificial intelligence models foundations is sparking a dispute over the future of the field ... Scientists taught an artificial neural network to imitate a biological neuron. The result offers a new way to think about the ...
"The Ethics of Artificial Intelligence" (PDF). Cambridge Handbook of Artificial Intelligence. Cambridge Press.. ... Hawking Warn of Artificial Intelligence Weapons". WSJ.. *^ GiveWell (2015). Potential risks from advanced artificial ... AI principles : recommendations on the ethical use of artificial intelligence by the Department of Defense. OCLC 1126650738.. ... The ethics of artificial intelligence is one of several core themes in BioWares Mass Effect series of games.[citation needed] ...
Are you thinking about adding artificial intelligence to your organization? Its certainly a hot topic and worth the attention ... Are you thinking about adding artificial intelligence to your organization? Its certainly a hot topic and worth the attention. ... SAS empowers and inspires customers around the world to transform data into intelligence. SAS gives you THE POWER TO KNOW®. ...
This book constitutes the refereed proceedings of the 4th International Conference on Artificial General Intelligence, AGI 2011 ... Artificial General Intelligence. 4th International Conference, AGI 2011, Mountain View, CA, USA, August 3-6, 2011. Proceedings ... Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 6830) ... computer vision computer-human interface mathematical logic neural networks universal artificial intelligence ...
Artifical intelligence can posivtivley impact how IT servies are delivered. Read more about how to start your organizations AI ... Artificial Intelligence *How IT leaders can prepare IT architectures for an AI future using Intel Xeon® with DL Boost ... Artificial intelligence (AI) has profound implications for how IT services will be delivered and managed, and organizations ...
AI - ARTIFICIAL INTELLIGENCE / (2001) ***1/2 (out of four). By Blake French:. AI - Artificial Intelligence is the hardest ... artificial intelligence , mother son relationship , synthetic human , artificially created boy , cyberpunk , See All (126) » ... A.I. Artificial Intelligence (2001) PG-13 , 2h 26min , Drama, Sci-Fi , 29 June 2001 (USA) ... AI - Artificial Intelligence is that kind of movie-one of the years best.. Critics and audiences alike have torn apart this ...
It also explains electroactive polymers, fuzzy logic, artificial life, and the ethical problems raised by artificial ... Artificial Intelligence looks at how advances in robotics, myoelectronics, and miniaturization have increased the ways in which ... Did you know that artificial intelligence uses computer programs to mimic the human brains? That there are robots being ... artificial intelligence can be used. It explains the growth of expert systems that help human professionals do their jobs more ...
This book constitutes the refereed proceedings of the 30th Canadian Conference on Artificial Intelligence, Canadian AI 2017, ... Advances in Artificial Intelligence. 30th Canadian Conference on Artificial Intelligence, Canadian AI 2017, Edmonton, AB, ... Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 10233) ... This book constitutes the refereed proceedings of the 30th Canadian Conference on Artificial Intelligence, Canadian AI 2017, ...
ISACA Tech Brief: Artificial Intelligence. Download (registration required, 260K) Provide feedback on this document. ... ISACA , Knowledge & Insights , Research , Research-Deliverables , Understanding Artificial Intelligence Understanding ... Artificial and augmented intelligence, machine learning and expert systems offer promise for remedying this situation. ... This free ISACA Tech Brief: Artificial Intelligence explores the advances driving this break-through innovation, with ...
Despite the public debate between Elon Musk and Mark Zuckerberg on whether or not artificial intelligence (AI) is good for ... smackdown over the possible threat of artificial intelligence. (AP Photo/Manu Fernandez, Stephan Savoia) ...
Artificial Intelligence with Susan Schneider Big Thinkers Series (Series tickets available) The new Big Thinkers series from ... Online Event: Artificial Intelligence with Susan Schneider. Big Thinkers Series (Series tickets available). The new Big ... In this talk, Susan Schneider urges that it is inevitable that AI will take intelligence in new directions, but it is up to us ... In her recent book, Artificial You: AI and the Future of the Mind, she discusses the philosophical implications of AI, and, in ...
Practically every industry has something to gain from artificial intelligence and machine learning. Explore how SAS solutions ... Latest features make it easier for you to innovate with artificial intelligence.. ...
suddenly you see through it like a pane of glass - ah the path. Then the coding. The debugging is enough to drive you insane. The slightest most subtle error can take days to find and then you feel so stupid for it was in plane sight all the time. All of that requires the concept of how to accomplish a task. But how do you create emotion? That is different. Now you are talking about the freedom to just act arbitrarily. Of I could mimic a random thought generator seeded with the timer taking the last digit of the second. But that only creates the appearance of randomness. In programming, it is IMPOSSIBLE to create a true random generator for you quickly discover, whatever the project, it will fall back into as cycle for pure randomness cannot be coded.. I do not even know where to begin to try to create REAL human emotion since it is impossible to create randomness. I can mimic human emotion. You will get to see some of that in the final launch of Socrates. He can even joke. If you want to buy ...
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... ligència artificial (ca); artificial intelligence researcher (en); باحث في مجال الذكاء الاصطناعي (ar); ερευνητής τεχνητής ... Media in category "Artificial intelligence researchers". The following 81 files are in this category, out of 81 total. ... investigadora de la inteligencia artificial, investigador de inteligencia artificial, investigadora de inteligencia artificial ... Meredith Whittaker at House Hearing on Artificial Intelligence.jpg 1,275 × 1,103; 164 KB. ...
... and advances in artificial intelligence will only increase the accuracy of this technique. ... What is artificial intelligence (AI)?. Artificial intelligence is an umbrella term encompassing both machine learning and ... Artificial Intelligence in Histopathology. News-Medical. https://www.news-medical.net/life-sciences/Artificial-Intelligence-in ... Artificial intelligence can be applied to detect and count cells, for example in mitotic events which may be relevant for ...
Advances in Artificial Intelligence is a peer-reviewed, Open Access journal that investigates the role of artificial ... intelligence in this rapidly progressing and challenging environment. It provides a rich, multidisciplinary platform for ... S. M. Potter, "What can artificial intelligence get from neuroscience?" in Artificial Intelligence Festschrift: The Next 50 ... M. A. Boden, "Creativity and artificial intelligence," Artificial Intelligence, vol. 103, no. 1-2, pp. 347-356, 1998. View at ...
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Industrial products executives view artificial intelligence (AI)/cognitive as market-ready, and well over half say the industry ... The artificial intelligence effect on industrial products: Profiting from an abundance of data ... By expanding digital intelligence adoption, AI technologies can help executives translate data into insights to drive greater ...
Call for Participation in AI KR (Artificial Intelligence Knowledge Representation) Community Group. W3C Team , Posted on: July ... The AI KR (Artificial Intelligence Knowledge Representation) Community Group has been launched:. The overall goal/mission of ... Should Explainable AI be applied to more general artificial intelligence - such as AGI but not restricted to - rather than just ... An open W3C community group called AIKR which stands for Artificial Intelligence Knowledge Representation was started around ...
... discuss Westworlds commentary on the state of artificial intelligence. ... Co-created by Jonathan Nolan and Lisa Joy, the genre-defying drama follows the dawn of artificial intelligence and the ... The minds behind the show get to thinking about artificial intelligence, and our own relationship to machines. ... Abrams and the cast of Westworld discuss what it means to be living in a society thats all-in on artificial intelligence. In ...
We have increasingly sophisticated narrow artificial intelligences, but only the first beginnings of systems ... EFF Related Content: Artificial Intelligence & Machine Learning. Filter by Type - Any -. Deeplinks Blog. Document. Event. Legal ... We have increasingly sophisticated "narrow" artificial intelligences, but only the first beginnings of systems that think in ... artificial intelligence may be. But regardless of whether you think general purpose AI is imminent or still in the distant ...
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artificial emotions. The failure of artificial intelligence. Cyberlife Research. Steve Grand. In defense of robot domination. ... Walterian Creatures: the next step in the Evolution of Intelligence?. The Birth of Artificial Intelligence. When It Changed. ... Emergent Artificial Intelligence. Instead, a holistic view can be argued- that the only example we have of intelligence ... Prelude: Knowledge-based Artificial Intelligence. As AI research began to organise into a coherent subject in the 1950s and 60s ...
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... We are pleased to present a new Special Issue on Artificial Intelligence in ... or artificial life. Proper image processing, appropriate selection of features and artificial intelligence method can support ... Artificial intelligence is increasingly used in various fields of life. One such area is medicine. Modern medical imaging ... Computer-aided detection in chest radiography based on artificial intelligence: a survey As the most common examination tool in ...
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  • Airbus has set itself an ambitious goal: the company intends to start a pilot program involving flying taxis powered by artificial intelligence before then end of 2017. (cebit.de)
  • China announced in 2017 its ambition to become the world leader in artificial intelligence (AI) by 2030. (singularityhub.com)
  • On June 7 2019 the exhibition "Artificial Intelligence and Intercultural Dialogue" dedicated to the creative capabilities of Artificial Intelligence (AI) will be open at the General Staff Building. (hermitagemuseum.org)
  • 22/05/2019 - OECD and partner countries formally adopted the first set of intergovernmental policy guidelines on Artificial Intelligence (AI) today, agreeing to uphold international standards that aim to ensure AI systems are designed to be robust, safe, fair and trustworthy. (oecd.org)
  • In early 2019 OpenAI, a startup co-founded by Elon Musk devoted to ensuring artificial general intelligence is safe for humanity, announced it had created a neural network for natural language processing called GPT-2. (singularityhub.com)
  • Retrieved on July 14, 2020 from https://www.news-medical.net/life-sciences/Artificial-Intelligence-in-Histopathology.aspx. (news-medical.net)
  • The Search for Extraterrestrial Intelligence (SETI) should focus on signals created by sentient machines rather than biological life forms, says Seth Shostak , senior astronomer at the SETI Institute in Mountain View, California. (newscientist.com)
  • In a recent paper published in the journal Acta Astronautica , entitled The Post Biological Universe , Dr. Steven Dick notes how every search for extraterrestrial intelligence assumes that life will be biological. (universetoday.com)
  • Many tools are used in AI, including versions of search and mathematical optimization, artificial neural networks, and methods based on statistics, probability and economics. (wikipedia.org)
  • [17] The first generation of AI researchers was convinced that artificial general intelligence was possible and that it would exist in just a few decades. (wikipedia.org)
  • Researchers at the University of California at Santa Barbara said this week they have created a circuit running about 100 artificial synapses that was able to perform a simple image classification. (computerworld.com)
  • A team of researchers has succeeded in creating an artificial intelligence (AI) algorithm that can identify changes in the earth's crust that occur up to three months before an earthquake. (moneycontrol.com)
  • Scientists are now wondering if devastation on this scale could be avoided using systems developed by artificial intelligence, among them a team of researchers from the French École Normale Supérieure (ENS), which recently announced the discovery of an AI algorithm to predict seismic events in the journal Nature Communications . (moneycontrol.com)
  • The annual AAAI National Conference and Innovative Applications of Artificial Intelligence Conference provide a forum for information exchange and interaction among researchers from all disciplines of AI. (mit.edu)
  • SAN FRANCISCO -- Artificial intelligence may hold the key to ruling out endocarditis related to cardiac rhythm devices without expensive, invasive transesophageal echocardiography, researchers reported here. (medpagetoday.com)
  • Google researchers last month reported progress in advancing the image classification and speech recognition capabilities of artificial neural networks. (technewsworld.com)
  • Finally, some researchers see intelligence as a quality that can only be acquired and demonstrated through relationship with other intelligent beings. (encyclopedia.com)
  • Science at the Edge: Artificial Intelligence looks at how advances in robotics, myoelectronics, and miniaturization have increased the ways in which artificial intelligence can be used. (google.com)
  • Abstract A general summary of Artificial Intelligence (AI) and Robotics is presented with the main stress on the how the present day robots and the future of Artificial Intelligence and Robotics would influence the society and the public life at large. (ipl.org)
  • Introduction With the rising importance in Artificial Intelligence and Robotics in the parts of medicine, manufacturing, military, and household applications, there is a push to increase the norm of robots and machine learning in these areas. (ipl.org)
  • Cognitive Robotics endows robots with artificial intelligence, providing them with perception, planning, memory and reasoning. (accenture.com)
  • The course provides theoretical and methodological knowledge and skills in classical AI (artificial intelligence) and robotics. (umu.se)
  • These sub-fields are based on technical considerations, such as particular goals (e.g. "robotics" or "machine learning"), the use of particular tools ("logic" or artificial neural networks), or deep philosophical differences. (wikipedia.org)
  • This free ISACA Tech Brief: Artificial Intelligence explores the advances driving this break-through innovation, with commentaries from leading experts in the field. (isaca.org)
  • It is the gold standard for disease diagnosis, and advances in artificial intelligence will only increase the accuracy of this technique. (news-medical.net)
  • To receive news and publication updates for Advances in Artificial Intelligence, enter your email address in the box below. (hindawi.com)
  • The journal of Artificial Intelligence (AIJ) welcomes papers on broad aspects of AI that constitute advances in the overall field including, but not limited to, cognition and AI, automated reasoning and inference, case-based reasoning, commonsense reasoning, computer vision, constraint processing, ethical. (elsevier.com)
  • These appearances also lead to heightened expectations - some technologists argue that the type of intelligence in these systems is "assisted" or "augmented" rather than "artificial", but recent advances in computing have certainly accelerated the potential of the technology. (deccanherald.com)
  • Scientists taught an artificial neural network to imitate a biological neuron. (wired.com)
  • This course will present advanced topics in Artificial Intelligence (AI), including inquiries into logic, artificial neural network and machine learning, and the Turing machine. (merlot.org)
  • A prediction model developed on an artificial neural network -- computer software designed to mimic the brain's ability to learn -- could exclude endocarditis with 99% confidence in half of patients, M. Rizwan Sohail, MD, of the Mayo Clinic in Rochester, Minn., and colleagues found. (medpagetoday.com)
  • So his group turned to artificial neural network software. (medpagetoday.com)
  • When the model was challenged with six additional patients of unknown diagnosis for external validation, the artificial neural network correctly excluded endocarditis in four and diagnosed one, but had one false negative. (medpagetoday.com)
  • Other conditions with complex diagnosis could potentially benefit from the same artificial neural network approach, he noted. (medpagetoday.com)
  • To help unravel the mystery, the team trained an artificial neural network by showing it millions of images - "training examples" - and gradually adjusting the parameters until the network was able to provide the desired classifications. (technewsworld.com)
  • Analysis and insight on the ever-evolving advancements in artificial intelligence. (singularityhub.com)
  • Finance teams lack the digital skillset to embrace the latest advancements in artificial intelligence, causing a negative impact on revenue growth, according to a new study from the Association of International Certified Professional Accountants (the Association) and Oracle (NYSE: ORCL) . (oracle.com)
  • The works of intelligence by advanced machinery or software is a common way to describe Artificial Intelligence which can make tasks less difficult for humans. (ipl.org)
  • Would artificial intelligence improve our communities in ways we humans cannot, or would they simply cause harm? (ipl.org)
  • Despite fears that machines will displace humans, most experts believe artificial and human intelligence will work synergistically. (scientificamerican.com)
  • These standard formulations duck the question of whether deeds which indicate intelligence when done by humans truly indicate it when done by machines: that's the philosophical question. (utm.edu)
  • While to many, the hype around AI may appear sudden, the concepts of modern artificial intelligence have been around for over a century and extending further, the concept of artificial intelligence and artificial beings have been in the minds of humans for thousands of years. (lifeboat.com)
  • artificial intelligence is the intelligent behavior by machines rather than the natural intelligence of humans and other animals. (designboom.com)
  • AI is a family of technologies that perform tasks that are thought to require intelligence if performed by humans,' explains Vasant Honavar , a professor and director of the Artificial Intelligence Research Laboratory at Penn State University. (howstuffworks.com)
  • Artificial intelligence (AI) is intelligence demonstrated by machines, unlike the natural intelligence displayed by humans and animals, which involves consciousness and emotionality. (wikipedia.org)
  • Jürgen Schmidhuber, the scientific director of SUPSI's Dalle Molle Institute for Artificial Intelligence (IDSIA), in Switzerland, has been a leading pioneer of artificial intelligence (AI) for three decades. (bcg.com)
  • Both Farhadi and Zettlemoyer work part-time at the Paul G. Allen Institute for Artificial Intelligence. (wjla.com)
  • There's very much a danger of killing the goose that lays the golden egg," says Oren Etzioni who left his professorship at the University of Washington in 2014 to become CEO of the Allen Institute for Artificial Intelligence. (wjla.com)
  • W. Dubitzky and F. Azuaje, "Preface," in Artificial Intelligence Methods and Tools for Systems Biology , W. Dubitzky and F. Azuaje, Eds. (hindawi.com)
  • What rules, if any, should constrain the use of machine learning methods when coupled to the large scale surveillance technologies operated by intelligence agencies? (eff.org)
  • I hope that this Special Issue will be for readers a valuable supplement to the knowledge of new artificial intelligence methods and its applications in new areas of medical imaging. (biomedcentral.com)
  • As difficult as it may seem to counter these methods, businesses should take comfort in the upsides of artificial intelligence . (pandasecurity.com)
  • rtificial intelligence methods are mostly mathematical solutions implemented in software, i.e. computer-implemented processes. (dpma.de)
  • In creating a business case for artificial intelligence projects, CIOs should focus on harnessing AI techniques that rely on quantitative methods to explore the links between specific business benefits and proposed solutions. (gartner.com)
  • This can include mechanical systems, electromagnetic systems, acoustic systems, thermal systems, photonic systems, chemical systems, biological systems, nanomachines and quantum mechanical systems where data or signals are processed according to artificial intelligence methods. (uspto.gov)
  • Approaches include statistical methods, computational intelligence, and traditional symbolic AI. (wikipedia.org)
  • It is a primary goal of some artificial intelligence research and a common topic in science fiction and future studies . (wikipedia.org)
  • A research paper that dubs some artificial intelligence models 'foundations' is sparking a dispute over the future of the field. (wired.com)
  • The development of Artificial Intelligence (AI) concerns the future of the whole society, all humankind, and the environment. (wired.com)
  • Telefónica's Maurice Conti roams widely through fields as diverse as artificial intelligence, virtual reality, synthetic biology, and the future of work. (bcg.com)
  • What does the European Union's new data strategy mean for the future of artificial intelligence in Europe? (bcg.com)
  • In her recent book, Artificial You: AI and the Future of the Mind , she discusses the philosophical implications of AI, and, in particular, the enterprise of "mind design. (newscientist.com)
  • As the NASA chair, Schneider has recently completed a two year project with NASA on the future of intelligence. (newscientist.com)
  • The future of corporate security lies in artificial intelligence. (pandasecurity.com)
  • Artificial Intelligence (AI) has enormous potential to shape India's future. (deccanherald.com)
  • artificial intelligence and computing power are the future, or even the present, for much of manufacturing. (yahoo.com)
  • Artificial intelligence has become a controversy among scientists within the past few years. (ipl.org)
  • Using powerful computers, scientists have scrutinized this bounty with some fine results, but it has become clear that we can learn much more with an assist from artificial intelligence. (scientificamerican.com)
  • Scientists are working on a circuit that mimics the human brain in an effort to dramatically boost artificial intelligence and machine learning. (computerworld.com)
  • Johns Hopkins scientists have used a form of artificial intelligence to create a map that compares types of cellular receptors, the chemical "antennas" on the surface of immune system T-cells. (news-medical.net)
  • In artificial general intelligence (AGI), which is a new field within AI, scientists try to create computer programs with a generalised type of intelligence, enabling them to solve problems in vastly different areas. (innovations-report.com)
  • The best example of general intelligence that we know of today is the human brain, and the scientists' strategy has been to imitate, at a very fundamental level, how children develop intelligence. (innovations-report.com)
  • [9] Many interdisciplinary approaches to intelligence (e.g. cognitive science , computational intelligence and decision making ) tend to emphasise the need to consider additional traits such as imagination (taken as the ability to form mental images and concepts that were not programmed in) [10] and autonomy . (wikipedia.org)
  • W. Duch and J. Mandziuk, "Quo vadis, computational intelligence? (hindawi.com)
  • Accordingly, the scientific discipline and engineering enterprise of AI has been characterized as "the attempt to discover and implement the computational means" to make machines "behave in ways that would be called intelligent if a human were so behaving" (John McCarthy), or to make them do things that "would require intelligence if done by men" (Marvin Minsky). (utm.edu)
  • Modeling Expectations with GENEFER - an Artificial Intelligence Approach ," Computational Economics , Springer;Society for Computational Economics, vol. 21(1), pages 173-194, February. (repec.org)
  • Modelling Expectations With Genefer- An Artificial Intelligence Approach ," Computing in Economics and Finance 2000 80, Society for Computational Economics. (repec.org)
  • Artificial intelligence (AI) is the field within computer science that seeks to explain and to emulate, through mechanical or computational processes, some or all aspects of human intelligence. (encyclopedia.com)
  • The AIML ( Artificial Intelligence and Machine Learning) team contributes to the vitality and growth of the organization through researching and building. (kdnuggets.com)
  • Primary Data, another speaker in the Rise of the Machines session, spoke about the value of combining data virtualization with metadata intelligence to improve performance, reduce costs and increase data protection across various storage systems including all flash arrays, NAS and cloud storage. (forbes.com)
  • The ethics of artificial intelligence is the part of the ethics of technology specific to artificially intelligent systems. (wikipedia.org)
  • Artificial and augmented intelligence, machine learning and expert systems offer promise for remedying this situation. (isaca.org)
  • The potential benefits of leveraging artificial intelligence (A) in the physical security industry have pros and cons on both sides, but the debate over the ethical ways to leverage AI and surveillance continues as more and more surveillance systems are getting the brains to match what they see. (forbes.com)
  • We have increasingly sophisticated "narrow" artificial intelligences, but only the first beginnings of systems that think in open ended and general ways like we do. (eff.org)
  • Rather, it concentrates on the less fantastical (but still far reaching) view of success in strong AI being dependant on holistic systems whose intelligence is a function of their perception of, and interaction with, the real world . (everything2.com)
  • So instead of artificial intelligence, I think we'll augment our intelligence" (Rometly, G.). Artificial intelligence are high-tech machines and computer systems that obtain the ability to learn human intelligence and characteristics with the imperfect data or information that people feed the computers and machines. (ipl.org)
  • Machine Learning is an artificial intelligence technology that provides systems with the ability to learn without being explicitly programmed. (accenture.com)
  • Biometrics is an artificial intelligence application that gives intelligent systems the ability to gather data on facial features and demographics. (accenture.com)
  • This document can be used to guide the development of accountable, de-risked, respectful, secure, honest, and usable artificial intelligence (AI) systems with a diverse team aligned on shared ethics. (cmu.edu)
  • Are language and understanding of the world important for intelligence or can systems without any knowledge of the world also be considered intelligent? (rug.nl)
  • Systems like IBM's Watson and Google's Alpha equip artificial neural networks with enormous computing power, and accomplish impressive feats. (scientificamerican.com)
  • Another possibility that's farther down the line is using evolution to influence the ethics of artificial intelligence systems. (scientificamerican.com)
  • In the same way, artificial intelligence is based upon the notion that there are general principles about how intelligent systems behave. (howstuffworks.com)
  • Asset Pricing Under Endogenous Expectations in an Artificial Stock Market ," Working papers 9625, Wisconsin Madison - Social Systems. (repec.org)
  • The next steps in the artificial intelligence revolution, as manifested most publicly through systems like Deep Blue, Watson and Siri, will revolutionize production in one sector after another. (yahoo.com)
  • and including systems for reasoning with uncertainty (e.g., fuzzy logic systems), adaptive systems, machine learning systems, and artificial neural networks. (uspto.gov)
  • The simpler, smarter interactions artificial intelligence makes possible are great for consumers and drive big wins for enterprise. (accenture.com)
  • Work smarter with artificial intelligence that's built right into Salesforce. (salesforce.com)
  • It also explains electroactive polymers, fuzzy logic, artificial life, and the ethical problems raised by artificial intelligence research. (google.com)
  • As AI research began to organise into a coherent subject in the 1950s and 60s it was (unsuprisingly) unclear as to what route offered the most promise in creating machine intelligence , or even what such intelligence would look like. (everything2.com)
  • and through research into biological intelligence, striving for greater understanding of the human brain. (everything2.com)
  • Today, Insilico Medicine, Inc., a Baltimore-based company specializing in the application of artificial intelligence for drug discovery, biomarker development and aging research, announced a publication of a research paper titled "Population-specific biomarkers of human aging: a big data study using South Korean, Canadian and Eastern-European patient populations" in The Journal of Gerontology. (news-medical.net)
  • More recently there has arisen a humbler seeming conception - "behavior-based" or "nouvelle" AI - according to which seeking to endow embodied machines , or robots, with so much as "insect level intelligence" (Brooks 1991) counts as AI research. (utm.edu)
  • The National Conference on Artificial Intelligence remains the bellwether for research in artificial intelligence. (mit.edu)
  • AAAI proceedings describe innovative concepts, techniques, perspectives, and observations that present promising research directions in artificial intelligence. (mit.edu)
  • India must also view machine intelligence as a critical element of its national security strategy and evaluate models of defence research in collaboration with the private sector and universities. (deccanherald.com)
  • Brain with chip, artificial intelligence and human science research. (istockphoto.com)
  • The most difficult problems for computers are informally known as "AI-complete" or "AI-hard", implying that solving them is equivalent to the general aptitude of human intelligence, or strong AI, beyond the capabilities of a purpose-specific algorithm. (wikipedia.org)
  • In the end, it will be the combined power of AI and human intelligence that will allow us to combat today's constantly changing threat landscape," said Ellenbogen. (forbes.com)
  • From there, it could quickly outpace human intelligence. (newscientist.com)
  • A more skeptical definition might be more narrow, for example: "the area of computer science that studies how machines can closely imitate human intelligence. (packtpub.com)
  • The next week is about human intelligence. (rug.nl)
  • but those results come from a new kind of collective human intelligence Agree with this. (darkreading.com)
  • but those results come from a new kind of collective human intelligence - nothing artificial about it. (darkreading.com)
  • that computers might match or even exceed human intelligence and capabilities on tasks such as complex decision-making, reasoning and learning, sophisticated analytics and pattern recognition, visual acuity, speech recognition and language translation. (pewinternet.org)
  • Traditional AI programs lack the versatility and adaptability of human intelligence. (innovations-report.com)
  • When asked about the series in a 2016 interview with online electronic music journal Resident Advisor, Sean Booth of Autechre said that, I dunno, I didn't come up with Artificial Intelligence. (wikipedia.org)
  • The experts predicted networked artificial intelligence will amplify human effectiveness but also threaten human autonomy, agency and capabilities. (pewinternet.org)
  • Building a trustworthy artificial intelligent system requires a team that coalesces around a shared set of ethics. (cmu.edu)
  • This raises philosophical arguments about the mind and the ethics of creating artificial beings endowed with human-like intelligence. (wikipedia.org)
  • Thought-capable artificial beings appeared as storytelling devices in antiquity, and have been common in fiction, as in Mary Shelley's Frankenstein or Karel Čapek's R.U.R. These characters and their fates raised many of the same issues now discussed in the ethics of artificial intelligence. (wikipedia.org)
  • Artificial Intelligence is a series of albums by Warp Records released from 1992-1994 to exhibit the capabilities and sounds of electronic music. (wikipedia.org)
  • The company's video intelligence API allows fining entities, content and moments, which can be broken down to the video shot or frame level-all available with a simple REST API call. (forbes.com)
  • looking in the directions that are maybe not the most attractive in terms of biological intelligence, but may be where sentient machines are hanging out. (newscientist.com)
  • Strong' AI is usually labelled as artificial general intelligence (AGI) while attempts to emulate 'natural' intelligence have been called artificial biological intelligence (ABI). (wikipedia.org)
  • Not only does it provide you an introduction to artificial intelligence, this new edition goes further by giving you the tools you need to explore the amazing world of intelligent apps and create your own applications. (packtpub.com)
  • David Kenny, the head of IBM's Watson, discusses smart ways for companies to use artificial intelligence. (bcg.com)
  • The field of artificial intelligence (AI) officially started in 1956, launched by a small but now-famous DARPA -sponsored summer conference at Dartmouth College, in Hanover, New Hampshire. (stanford.edu)
  • The field of Artificial Intelligence is very diverse, which this series of web classes will show you. (rug.nl)
  • The computer programs used in the field of artificial intelligence (AI) are highly specialised. (innovations-report.com)
  • Algorithms running on such hardware have the potential to address the growing demand for machine learning and artificial intelligence in areas such as medical diagnosis, telecommunications, and high-performance and scientific computing. (nature.com)
  • Finally, this new edition explores various real-world scenarios and teaches you how to apply relevant AI algorithms to a wide swath of problems, starting with the most basic AI concepts and progressively building from there to solve more difficult challenges so that by the end, you will have gained a solid understanding of, and when best to use, these many artificial intelligence techniques. (packtpub.com)
  • In both cases, the studies must include the course Fundamentals of Artificial Intelligence (5DV121), at least 7.5hp within Data Structures and Algorithms (e.g. 5DV149 or 5DV150) and at least 7.5 ECTS-credits within logic (e.g. 5DV102 or 5DV162). (umu.se)
  • In order to learn a Fuzzy Rule base from examples we introduce Genetic Algorithms and Artificial Neural Networks as learning operators. (repec.org)
  • The field of AI is considered to have its origin in the publication of British mathematician Alan Turing's (1912 - 1954) paper "Computing Machinery and Intelligence" (1950). (encyclopedia.com)
  • You were redirected to https://www.coe.int/sr_RS/web/human-rights-channel/-/artificial-intelligence-could-threaten-your-human-rights- . (coe.int)
  • A key benefit with such artificial technology is that it can be applied to whole slide imaging, where the AI can automatically identify patterns in a whole slide. (news-medical.net)
  • Some people call this artificial intelligence, but the reality is this technology will enhance us. (ipl.org)
  • Use of Artificial Intelligence in Software Development Life Cycle …A state of the art review Bhagyashree W. Sorte, Pooja P. Joshi, Prof. Vandana Jagtap Maharashtra Institute of Technology, Pune, India. (ipl.org)
  • What are the possible advantages and disadvantages of artificial intelligence, and to what extent is it ethically defensible to develop this technology? (ipl.org)
  • Applied Intelligence is intelligent technology and human ingenuity applied at the core of business - across every function and process - to address our clients' most complex challenges. (accenture.com)
  • Artificial intelligence is a transformative technology that will drive sustainable competitive advantage and business value. (gartner.com)
  • To better understand and appreciate this technology and those who brought it to us as well as to gain insight into where it will take us: sit back, relax and join me in an exploration on the history of artificial intelligence. (lifeboat.com)
  • A vehicle and person recognition system for use by law enforcement is demonstrated at last year's GPU Technology Conference in Washington, D.C., which highlights new uses for artificial intelligence and deep learning. (pewinternet.org)
  • Four of the world's best professional poker players will match wits with an artificial intelligence developed by Carnegie Mellon University and using PSC's Bridges system to formulate strategy. (psc.edu)
  • Here's a look at some Artificial Intelligence Applications Meetups happening near San Francisco. (meetup.com)
  • Still, to the extent that what is called "thinking" in us is paradigmatic for what thought is, the question of human level intelligence may arise anew at the foundations. (utm.edu)
  • Artificial general intelligence ( AGI ) is the intelligence of a machine that could successfully perform any intellectual task that a human being can. (wikipedia.org)
  • Various technologies under the general name of Artificial Intelligence (AI) can provide ways to organize this avalanche of unstructured data. (forbes.com)
  • Should Explainable AI be applied to more general artificial intelligence - such as AGI but not restricted to - rather than just machine learning, which is just one of many ways of implementing AI solutions? (w3.org)
  • There is a wide range of views about how urgent or profound the policy questions raised by general, "human level", artificial intelligence may be. (eff.org)
  • Last year, Microsoft announced a billion-dollar investment in OpenAI, an organization whose mission is to create artificial general intelligence and make it safe for humanity. (singularityhub.com)
  • But soon we will evolve machines that can execute more complex tasks and have much better general intelligence. (scientificamerican.com)
  • General intelligence , in contrast, is a more human-like ability to learn about anything and to talk about it. (howstuffworks.com)
  • Exciting developments in Artificial Intelligence are happening every day. (meetup.com)
  • This method, called ANNA-PALM, is based on recent developments in artificial intelligence and, more specifically, in much-talked-about deep learning. (pasteur.fr)
  • Machine Intelligence: Quo Vadis? (hindawi.com)
  • Follow that out further to, say, 2045, we will have multiplied the intelligence, the human biological machine intelligence of our civilization a billion-fold. (ipl.org)
  • Can machine intelligence approach or surpass the human level? (utm.edu)
  • The efficiencies and other economic advantages of code-based machine intelligence will continue to disrupt all aspects of human work. (pewinternet.org)
  • What's more, Shostak writes that machine intelligence will be more prolific and long-lived than its biological predecessors. (newscientist.com)
  • Given the rapid pace of progress in AI, many predict that AI could advance to human-level intelligence within the next several decades. (newscientist.com)
  • The ability to quantify the extent of kidney damage and predict the life remaining in the kidney, using an image obtained at the time when a patient visits the hospital for a kidney biopsy, now is possible using a computer model based on artificial intelligence. (news-medical.net)
  • Can Artificial Intelligence Predict Religious Violence? (theatlantic.com)
  • It's a noble idea: If leaders can use artificial intelligence to predict which policy will produce the best outcome, maybe we'll end up with a healthier and happier world. (theatlantic.com)
  • By expanding digital intelligence adoption, AI technologies can help executives translate data into insights to drive greater innovation, and better operational and financial decisions. (ibm.com)
  • Read how artificial intelligence (AI) can boost profitability and innovation. (accenture.com)
  • with a heavy emphasis on the internet of things and artificial intelligence , this year's CEATEC exhibition in japan showcased the world's latest innovation in technological advancements. (designboom.com)
  • In fact, most CMOs in five global markets believe artificial intelligence will surpass social media's influence in the industry. (dnb.com)
  • Up until now, they have been able to point to examples of tasks that computers cannot perform, and therefore claim that computers cannot yet "think" or exhibit artificial intelligence if they cannot satisfactorily perform such functions. (packtpub.com)
  • Artificial intelligence (AI) is an interdisciplinary science concerned with building smart machines capable of performing tasks that typically require human thought. (howstuffworks.com)
  • Artificial intelligence, commonly referred to as AI, gives machines the ability to learn from experience and perform cognitive tasks, the sort of stuff that once only the human brain seemed capable of doing. (howstuffworks.com)
  • Intelligence is also seen in the functions one performs, in actions or the ability to carry out certain tasks. (encyclopedia.com)
  • As machines become increasingly capable, tasks considered to require "intelligence" are often removed from the definition of AI, a phenomenon known as the AI effect. (wikipedia.org)
  • As an artificial intelligence researcher, I often come across the idea that many people are afraid of what AI might bring . (scientificamerican.com)
  • The approach they are using teaches computers to interpret the complex patterns seen in such images by "building multi-layer artificial neural networks," says Prof. Beck. (medicalnewstoday.com)
  • Each of these understandings of intelligence has been used as the basis of an approach to developing computer programs with intelligent characteristics. (encyclopedia.com)
  • This technique uses artificial neural networks ( see Christophe Zimmer interview ) to reconstruct super-resolution images from rapidly acquired low-resolution images. (pasteur.fr)
  • The major question that needs to be answered is: how will Artificial Intelligence impact the human race and the economy, human relations and work. (ipl.org)
  • The largest constraint on artificial intelligence may be the imagination of business leaders. (bcg.com)
  • Artificial intelligence (AI) was born in the 1950s, when the English polymath Alan Turing created a test to determine a machine's ability to mimic human cognitive functions, including perception, reasoning, learning, and problem solving. (mckinsey.com)
  • Did you know that artificial intelligence uses computer programs to mimic the human brains? (google.com)
  • We combine Artificial Intelligence with deep industry and analytics expertise to help our clients embrace intelligent technologies confidently and responsibly. (accenture.com)
  • Artificial Intelligence (referred to hereafter by its nickname, "AI") is the subfield of Computer Science devoted to developing programs that enable computers to display behavior that can (broadly) be characterized as intelligent. (stanford.edu)
  • But substantial interest remains in the long-range goal of building generally intelligent, autonomous agents, [ 2 ] even if the goal of fully human-like intelligence is elusive and is seldom pursued explicitly and as such. (stanford.edu)
  • For example, 86 percent of Digital Finance Leaders have a digital-first and cloud-first mindset, which gives them greater access to intelligent process automation and technologies such as artificial intelligence and Blockchain, which are commonly delivered via the cloud. (oracle.com)
  • Plenty of time to evolve into intelligent life, and then transition into artificial intelligence. (universetoday.com)
  • Through innovative software and services, SAS empowers and inspires customers around the world to transform data into intelligence. (sas.com)
  • To win the upcoming battle for supremacy in digital and artificial intelligence, companies must transform into butterflies rather than train to be faster caterpillars. (bcg.com)
  • These features are most often used for a variety of analyses including fuzzy logic, evolutionary calculations, neural networks, or artificial life. (biomedcentral.com)
  • If artificial or alien intelligence show evidence of being sentient , this philosophy holds that they should be shown compassion and granted rights. (wikipedia.org)
  • Just as Carl Sagan pointed out, the real intelligence [perception, imagination and creativity] was on Lowell's end of the telescope. (darkreading.com)
  • Artificial intelligence is increasingly used in various fields of life. (biomedcentral.com)
  • As artificial intelligence makes headway and gains the ability to analyze more and more data of the person it plans to impersonate, so-called CEO fraud will become increasingly sophisticated and difficult to combat. (pandasecurity.com)