Relevant bibliographies by topics / Artificial Intelligence technology

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Artificial Intelligence technology'

Author: Grafiati
Published: 4 June 2021
Last updated: 15 February 2022

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Journal articles on the topic "Artificial Intelligence technology"

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Majumdar, B., S. C. Sarode, G. S. Sarode, and S. Patil. "Technology: Artificial intelligence." British Dental Journal 224, no. 12 (June 2018): 916. http://dx.doi.org/10.1038/sj.bdj.2018.485.

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D. Revathi Pandian, D. Revathi Pandian. "Artificial Intelligence Technology An Overview." International Journal of Information Systems Management Research and Development 9, no. 1 (2019): 25–30. http://dx.doi.org/10.24247/ijismrdjun20192.

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Ennals, Richard. "Artificial Intelligence and Educational Technology." PLET: Programmed Learning & Educational Technology 24, no. 2 (May 1987): 90–93. http://dx.doi.org/10.1080/0033039870240202.

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Wong, Simon C. H. "Educational technology and artificial intelligence." ACM SIGCUE Outlook 23, no. 1-2 (January 11, 1995): 17–33. http://dx.doi.org/10.1145/209878.209882.

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Dasgupta, Prokar. "Science, technology and artificial intelligence." BJU International 122, no. 6 (November 20, 2018): 913. http://dx.doi.org/10.1111/bju.14595.

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Shenoy, R. P. "Artificial Intelligence-The Emerging Technology." Defence Science Journal 35, no. 2 (January 22, 1985): 135–49. http://dx.doi.org/10.14429/dsj.35.6004.

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Rajaram, N. S. "Artificial intelligence: A technology review." ISA Transactions 29, no. 1 (January 1990): 1–3. http://dx.doi.org/10.1016/0019-0578(90)90023-e.

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Saini, Abhedya. "Artificial Intelligence a Threat." IAES International Journal of Artificial Intelligence (IJ-AI) 5, no. 3 (August 20, 2016): 117. http://dx.doi.org/10.11591/ijai.v5.i3.pp117-118.

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<p>Research in AI has built upon the tools and techniques of many different disciplines.Study in the artificial intelligence has given rise to rapidly growing technology known as expert system. Rapid development in this field made human more dependent on this technology. More advancement will lead to side effects of that technology because after a certain point, everything is harmful.</p>
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Kim, Kwang-Soo. "Artificial intelligence-based technology and relief." Korean Public Land Law Association 85 (February 28, 2019): 231–58. http://dx.doi.org/10.30933/kpllr.2019.85.231.

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VAMOS, TIBOR. "ARTIFICIAL INTELLIGENCE: HUMAN FOCUS ON TECHNOLOGY." Applied Artificial Intelligence 5, no. 2 (January 1991): 163–70. http://dx.doi.org/10.1080/08839519108927923.

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Dissertations / Theses on the topic "Artificial Intelligence technology"

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Malmborn, Albin, and Linus Sjöberg. "Implementing Artificial intelligence." Thesis, Malmö universitet, Fakulteten för teknik och samhälle (TS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-20942.

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Den här uppsatsen har som syfte att undersöka huruvida det är möjligt att ta fram riktlinjer för vad privata verksamheter behöver ta i beaktande inför en planerad implementering av artificiell intelligens. Studien kommer belysa faktorer som hjälper företag att förstå vad som krävs inför en sådan omställning, men även de hinder som måste övervinnas för att lyckas. Studiens datainsamling har genomförts med två metoder, först en litteraturstudie sedan kvalitativa, semistrukturerade forskningsintervjuer. Dessa har sedan analyserats med vars en analysmetod som kompletterar varandra och därefter tolkats för att se mönster som kan besvara studiens frågeställning: Vad måste svenska organisationer inom den privata sektorn beakta för att lyckas implementera Artificiell intelligens i sin verksamhet? Resultatet har tagits fram genom att jämföra vetenskapliga texter och intervjuer, för att undersöka om den akademiska och praktiska synen skiljer sig åt. Studien resulterade i åtta faktorer som företag borde ta i beaktning inför en implementering av artificiell intelligens. Författarna hoppas att med den här studien kunna främja svensk utveckling inom artificiell intelligens och på så vis generera ett större nationellt mervärde och en starkare konkurrenskraft internationell.
The purpose of this paper is to investigate the possibilities to develop guidelines for businesses to take into account before an implementation of artificial intelligence. The study will highlight different factors that will help companies to understand what is required to make this kind of digital transition, it will also highlight the obstacles companies have to overcome in order to succeed. The data collection was conducted in two parts, first a literature study and then qualitative, semi-structured interviews. These were analyzed with their own analysis which supplement each other, and interpreted to identify patterns that could answer the study's main question: What must Swedish organizations in the private sector consider in order to successfully implement Artificial Intelligence in their operations?The result of the study has been produced by comparing scientific texts and interviews, to investigate whether the academic and practical views differ. The study resulted in eight factors that companies should consider before implementing artificial intelligence. The authors hope that the study will promote Swedish development in artificial intelligence and thus generate a greater national value and international competitiveness.
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Damerji, Hassan. "Technology Readiness Impact on Artificial Intelligence Technology Adoption by Accounting Students." Thesis, University of La Verne, 2020. http://pqdtopen.proquest.com/#viewpdf?dispub=27547476.

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Artificial Intelligence (AI) is the way forward in accounting and auditing. The purpose of this study was to examine the relationship between accounting students’ level of technology readiness (TR) and AI technology adoption (TA). This quantitative study examined the independent variables of TR, perceived ease of use (PEOU), and perceived usefulness (PU) and the dependent variable of TA. Moreover, the present study examined the mediating effect of PEOU and PU on the relationship between TR and TA. The present study was related to individual accounting students’ perceptions of TR and TA. Student participants (n = 101) recruited for this study were randomly sampled from 2 universities in Southern California, the United States. An online questionnaire consisting of 30 items regarding perceptions of TR, PEOU, PU, and TA was administered. The bivariate correlation and regression between variables showed that TR, PEOU, and PU positively influence TA; TR positively influences PEOU and PU; and PEOU positively influences PU. Mediation analysis showed that both PEOU and PU mediate the relationship between TR and TA. Because of the significant relationships among variables, the model met the criteria for technology readiness and acceptance model (TRAM) and Model 6 of process mediation. This study adds to the empirical research regarding the relationships between the constructs of TR and TA of AI within higher education, in which there is a gap in the literature. The study contributed by applying the TRAM construct to the use and adoption of AI. TR, PEOU, and PU are important constructs within higher education and predict AI TA by accounting students. Additionally, TR is a precursor to PEOU and PU of AI for this population. For practice, universities should enhance use perceptions by creating opportunities for accounting students to interact with AI. Effective adoption of AI in accounting curricula aimed at enhancing students’ perceptions is essential to increase their adoption of AI and overall career readiness. For research, replicating the study at other universities, examining other factors that influence students’ adoption of AI, and exploring other AI topics in higher education could expand the literature on technology readiness and TA of AI.
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McBrien, Andrew. "Artificial intelligence methods in process plant layout." Thesis, University of Nottingham, 1994. http://eprints.nottingham.ac.uk/14403/.

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The thesis describes "Plant Layout System" or PLS, an Expert System which automates all aspects of conceptual layout of chemical process plant, from sizing equipment using process data to deriving the equipment items' elevation and plan positions. PLS has been applied to a test process of typical size and complexity and which encompasses a wide range of layout issues and problems. The thesis presents the results of the tests to show that PLS generates layouts that are entirely satisfactory and conventional from an engineering viewpoint. The major advance made during this work is the approach to layout by Expert System of any kind of process plant. The thesis describes the approach in full, together with the engineering principles which it acknowledges. Plant layout problems are computationally complex. PLS decomposes layout into a sequence of formalised steps and uses a powerful and sophisticated technique to reduce plant complexity. PLS uses constraint propagation for spatial synthesis and includes propagation algorithms developed specifically for this domain. PLS includes a novel qualitative technique to select constraints to be relaxed. A conventional frame based representation was found to be appropriate, but with procedural knowledge recorded in complex forward chaining rules with novel features. Numerous examples of the layout engineer's knowledge are included to elucidate the epistemology of the domain.
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Fyrvald, Johanna. "Mitigating algorithmic bias in Artificial Intelligence systems." Thesis, Uppsala universitet, Matematiska institutionen, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-388627.

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Artificial Intelligence (AI) systems are increasingly used in society to make decisions that can have direct implications on human lives; credit risk assessments, employment decisions and criminal suspects predictions. As public attention has been drawn towards examples of discriminating and biased AI systems, concerns have been raised about the fairness of these systems. Face recognition systems, in particular, are often trained on non-diverse data sets where certain groups often are underrepresented in the data. The focus of this thesis is to provide insights regarding different aspects that are important to consider in order to mitigate algorithmic bias as well as to investigate the practical implications of bias in AI systems. To fulfil this objective, qualitative interviews with academics and practitioners with different roles in the field of AI and a quantitative online survey is conducted. A practical scenario covering face recognition and gender bias is also applied in order to understand how people reason about this issue in a practical context. The main conclusion of the study is that despite high levels of awareness and understanding about challenges and technical solutions, the academics and practitioners showed little or no awareness of legal aspects regarding bias in AI systems. The implication of this finding is that AI can be seen as a disruptive technology, where organizations tend to develop their own mitigation tools and frameworks as well as use their own moral judgement and understanding of the area instead of turning to legal authorities.
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Nilsson, Daniel. "Artificial Intelligence for detecting IoT data intrusions." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-424095.

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The importance of the Internet of Things (IoT) continues to grow in modern society,yet it remains relatively vulnerable to data intrusion attacks. These attacks can compromise both the IoT networks them selves and the services that rely on them.This work explores a number of artificial intelligence solutions for their viability in intrusion detection within the IoT. The Bayesian Network, Artificial Neural Networkand Support Vector Machine are judged to have the most potential. A traditional three-layer Artificial Neural Network is tested in practice, using roundtrip time and power consumption data to explore different parameters. An overall accuracy of 94%is achieved with only 1% false positive ratio, with a data window of 9 or morereadings and a data ratio of a few times more non-attack data than attack data. It is concluded that Neural Networks are viable for use in the field of IoT intrusiondetection.
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Güler, Dilvan, and Mohamed Mahdi. "A Systematic Mapping Study on APIs Utilizing Artificial Intelligence Technology." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-300093.

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This thesis covers the systematic mapping of established public Application Programming Interface (API)s that are employing the Artificial Intelligence (AI) technology. This due to the fact that the problem has been the lack of systematic maps of AI APIs in the present time, therefore this thesis has the purpose of increasing the insight in the area by creating the mapping study. The goal is to provide both a basis for research and to aid the general developer which uses the AI APIs. The systematic mapping of the AI APIs will be conducted by examining the information of the APIs and iterations classifying the AI APIs into categories and presented in tables. The analysis and discussion of the study was made based on the results from the study, namely the phases, the iterations, the result tables and the final systematic map. Additionally, an analysis was made on the validity threats of the study. The evaluation of each API in this study was done in cycles, by categorizing each AI API into a category that is included in the final result, which is a systematic map. The result has been proven to be useful for the target group of this study, the researchers and developers, by aiding them in finding the right API for them to use in their work. Therefore, this work will help future developers and researchers due to the fact that the thesis is providing relevant information in the development phases of employing AI in the web interfaces at the present time.
Detta examensarbete omfattar en systematisk kartläggning av etablerade publika API:er som använder sig utav AI- teknik. Eftersom bristen på systematiska kartor över AI API:er varit stor, har detta examensarbete syfte att öka insikten i området genom att skapa denna kartläggningsstudie. Målet med den systematiska kartläggningen är att bygga en grund för framtida forskning inom detta område, samt förenkla processen av att hitta AI API:erna för den allmänna utvecklaren som använder dessa. Den systematiska kartläggningen av AI API:er kommer att genomföras genom att undersöka tillgänglig dokumentation och information om API:erna. Dessutom klassificerades AI API:erna i kategorier, och presenterades sedan i tabeller. Analysen och diskussionen av studien gjordes baserat på resultaten från studien, nämligen faserna och iterationerna där AI API:erna kategoriseras, samt på resultat tabellerna och den slutliga systematiska kartan på AI API:erna. Dessutom gjordes en analys av hoten mot studiens giltighet. Utvärderingen av varje API i denna studie gjordes i cykler genom att kategorisera varje AI API i en kategori som sedan inkluderades i resultatet vilket är en systematiska karta. Resultatet från detta examensarbete har visat sig vara användbar för målgruppen, forskare och utvecklare, då det hjälper målgruppen att hitta rätt API att använda i arbetet.
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Kang, Johan, and Sebastian Westskytte. "Diffusion of Cybersecurity Technology - Next Generation, Powered by Artificial Intelligence." Thesis, KTH, Industriell ekonomi och organisation (Inst.), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-246027.

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The cyber world is growing as more information is converted from analogue to digital form. While convenience has been the main driver for this change little effort has been made on securing the data. Data breaches are growing in number and each breach is growing in severity. Combined with regulatory pressure organizations are starting to realize the importance of security. The increased threat level is also driving the security market for more potent solutions and artificial intelligence (AI) have in recent years been implemented to enhance the capabilities of security technologies.  The thesis aims to investigate the adoption of AI enabled cybersecurity technologies within the financial industry which is often perceived as the market leader regarding security. Using a qualitative method through a multiple case study, valuable insights were gained regarding how firms are working with security and what needs they have. To identify factors that influence the rate of diffusion of AI enabled security technologies the diffusion of innovation theory combined with the TOE framework was used in this study.  The thesis has contributed to the field of innovation management by enriching an area within IT innovation management by bridging the gap between security innovation and AI innovation. The study revealed that environmental factors, such as regulations and threat landscape, are forcing organizations to take action and control both how organizations work with security but also what technological attributes are perceived as advantageous. Detection and automation are two technological attributes that the companies are looking for to fill their needs. AI solutions are already being implemented to increase detection and automation we believe that the rate of adoption for AI enabled security innovation will only continue to grow. The results and findings contribute to an expanded understanding on the factors that affect adoption of AI security innovations within the financial industry.
Den digitala världen fortsätter att växa eftersom mer information omvandlas från analog till digital form. Medan bekvämlighet har varit den viktigaste drivkraften för denna förändring, så har lite ansträngning gjorts för att säkra upp den data som företagen besitter. Dataintrången växer i antal, och varje ny incident får allvarligare konsekvenser än den förra. Detta faktum kombinerat med strängare regelverk har fått företagen att inse vikten av att säkra sin miljö. Den förstärkta hotbilden driver också säkerhetsmarknaden framåt med nya lösningar, och artificiell intelligens (AI) har under de senaste åren i allt större utsträckning implementerats i säkerhetslösningar för att förstärka skyddet. Uppsatsens syfte är att undersöka spridningen av AI-säkerhetsinnovationer inom finansbranschen, som ofta uppfattas som marknadsledande när det gäller säkerhet. Med hjälp av en kvalitativ metod genom en fallstudie på tre företag erhölls värdefulla insikter om hur företagen arbetar med säkerhet och vilka behov de har. För att identifiera faktorer som påverkar spridningshastigheten för AI-säkerhetslösningar användes ”diffusion of innovation”-teorin i kombination med TOE-ramverket i denna studie. Uppsatsen har bidragit till innovation management-området genom att berika ett område inom IT-innovation genom att brygga mellan säkerhetsinnovation och AI-innovation. Studien visade att miljöfaktorer, såsom regelverk och hotbild, kontrollerar både hur organisationer arbetar med säkerhet och vilka tekniska egenskaper som uppfattas som fördelaktiga. Detektion och automatisering är två tekniska egenskaper som företagen har stora behov av. AI-lösningar implementeras redan för att öka de egenskaperna. Vi argumenterar för att, utifrån de behoven som företagen har kombinerat med miljöfaktorerna, kommer spridningstakten att öka för AI-säkerhetsinnovation.
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Kansu, Hazal Mine. "Artificial intelligence impact on occupations and workforce." Thesis, Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/124594.

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Thesis: S.M. in Technology and Policy, Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society, 2019
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 72-76).
Recent developments in machine learning (ML) have persuaded researchers that automated technologies without human intervention may transform occupations across the economy. My research seeks to assess how and where ML will affect the workforce. I extend the ideas of Brynjolfsson, Mitchell, and Rock (2018), who assess each task in the economy for its Suitability for Machine Learning (SML). This paper builds on their summary statistics to provide a more detailed analysis of where ML is likely to have its greatest impact in the economy. Combining their technological suitability data with labor market data, this paper suggests a policy model for better planning labor mobility and allocation of human resources in the face of upcoming technological changes.
by Hazal Mine Kansu.
S.M. in Technology and Policy
S.M.inTechnologyandPolicy Massachusetts Institute of Technology, School of Engineering, Institute for Data, Systems, and Society
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Incerti, Federica. "Preservice Teachers’ Perceptions of Artificial Intelligence Tutors for Learning." Ohio University / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1585088861453228.

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Luwes, Nicolaas Johannes. "Artificial intelligence machine vision grading system." Thesis, Bloemfontein : Central University of Technology, Free State, 2014. http://hdl.handle.net/11462/35.

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Books on the topic "Artificial Intelligence technology"

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AMERICAN, SCIENTIFIC. Understanding Artificial Intelligence. New York: Grand Central Publishing, 2002.

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Mittal, Vibhu O., Holly A. Yanco, John Aronis, and Richard Simpson, eds. Assistive Technology and Artificial Intelligence. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/bfb0055965.

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Dev, Amita, Arun Sharma, and S. S. Agarwal. Artificial Intelligence and Speech Technology. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781003150664.

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Girasa, Rosario. Artificial Intelligence as a Disruptive Technology. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-35975-1.

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1967-, Jiang Xia, ed. Contemporary artificial intelligence. Boca Raton, FL: Taylor & Francis, 2012.

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Li, Deyi. Artificial Intelligence with Uncertainty. London: Taylor and Francis, 2007.

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Li, Deyi. Artificial intelligence with uncertainty. Boca Raton, FL: C&H, Taylor & Francis Group, 2007.

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Affect and artificial intelligence. Seattle: University of Washington Press, 2010.

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Brewster, R. L. ISDN Technology. Dordrecht: Springer Netherlands, 1993.

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Andreychikov, Aleksandr, and Ol'ga Andreychikova. Intelligent information systems and artificial intelligence methods. ru: INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1009595.

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The textbook discusses the methods of artificial intelligence and their application to solve problems from various subject areas. Methods of acquisition, representation and processing of knowledge in intelligent systems, as well as technologies for designing and implementing intelligent systems, are described. Special attention is paid to the application of intelligent systems for the selection of collective solutions, the design of complex systems( objects), the analysis and forecasting of the enterprise. Meets the requirements of the federal state educational standards of higher education of the latest generation. For students enrolled in groups of training master's degree program "Management in technical systems", "Computer and information science", "computer science", "engineering and technology land transport", "engineering and construction technology", "Photonics, instrumentation, optical and biotechnical systems and technology", "aerospace engineering", "engineering and technologies of shipbuilding and water transport", and also in the areas of "automation of technological processes and productions", "mechatronics and robotics".
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Book chapters on the topic "Artificial Intelligence technology"

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Kubacki, Jens. "Artificial intelligence." In Technology Guide, 146–49. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-88546-7_28.

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Todd, D. J. "Robotics and Artificial Intelligence." In Fundamentals of Robot Technology, 215–26. Dordrecht: Springer Netherlands, 1986. http://dx.doi.org/10.1007/978-94-011-6768-0_11.

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Salem, Abdel-Badeeh M. "Artificial Intelligence Technology in Intelligent Health Informatics." In Advances in Intelligent Systems and Computing, 3. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-99981-4_1.

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Hallevy, Gabriel. "Punishibility of Artificial Intelligence Technology." In Liability for Crimes Involving Artificial Intelligence Systems, 185–227. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-10124-8_6.

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Subashini, P., and M. Krishnaveni. "Artificial Intelligence-Based Assistive Technology." In Artificial Intelligence Theory, Models, and Applications, 217–40. Boca Raton: Auerbach Publications, 2021. http://dx.doi.org/10.1201/9781003175865-13.

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Kamolov, Sergey, and Kirill Teteryatnikov. "Artificial Intelligence in Public Governance." In Technology and Business Strategy, 127–35. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-63974-7_9.

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Hodge, Lord. "Financial technology." In Artificial Intelligence and the Law, 31–48. Milton Park, Abingdon, Oxon ; New York, NY : Routledge, 2021.: Routledge, 2020. http://dx.doi.org/10.4324/9780429344015-2.

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Zhong, Yixin. "Knowledge Theory and Artificial Intelligence." In Rough Sets and Knowledge Technology, 50–56. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11795131_8.

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Jia, Xiangyun. "Mechatronics Intelligent Control Based on Artificial Intelligence Technology." In Application of Intelligent Systems in Multi-modal Information Analytics, 93–99. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-74814-2_13.

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Malik, Marium, Muhammad Imran Tariq, Maira Kamran, and Muhammad Raza Naqvi. "Artificial Intelligence in Medicine." In Advances in Smart Vehicular Technology, Transportation, Communication and Applications, 159–70. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-1209-1_15.

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Conference papers on the topic "Artificial Intelligence technology"

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Hosea, S. Pradeesh, V. Harikrishnan, and K. Rajkumar. "Artificial intelligence." In 2011 3rd International Conference on Electronics Computer Technology (ICECT). IEEE, 2011. http://dx.doi.org/10.1109/icectech.2011.5941871.

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Suleimenov, Ibragim E., Yelizaveta S. Vitulyova, Akhat S. Bakirov, and Oleg A. Gabrielyan. "Artificial Intelligence." In ICCTA '20: 2020 6th International Conference on Computer and Technology Applications. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3397125.3397141.

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Joshi, Akshar, and Gautam Mishra. "Artificial intelligence." In ICWET '10: International Conference and Workshop on Emerging Trends in Technology. New York, NY, USA: ACM, 2010. http://dx.doi.org/10.1145/1741906.1742236.

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Hu, Shuijing, and Tao Jiang. "Artificial Intelligence Technology Challenges Patent Laws." In 2019 International Conference on Intelligent Transportation, Big Data & Smart City (ICITBS). IEEE, 2019. http://dx.doi.org/10.1109/icitbs.2019.00064.

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Li, Bingzhen, Jiaojiao Gu, and Wenzhi Jiang. "Artificial Intelligence (AI) Chip Technology Review." In 2019 International Conference on Machine Learning, Big Data and Business Intelligence (MLBDBI). IEEE, 2019. http://dx.doi.org/10.1109/mlbdbi48998.2019.00028.

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Sánchez-Nielsen, Elena, and Stefan Klink. "Integrating google technology in artificial intelligence." In the 16th annual joint conference. New York, New York, USA: ACM Press, 2011. http://dx.doi.org/10.1145/1999747.1999780.

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Yuanmin, Shi. "Artificial intelligence based computer network technology." In 3rd International Conference on Green Communications and Networks. Southampton, UK: WIT Press, 2014. http://dx.doi.org/10.2495/gcn130701.

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Gao, Weilu, Cunxi Yu, and Ruiyang Chen. "Graphene Optoelectronic Artificial Intelligence Accelerators." In CLEO: Applications and Technology. Washington, D.C.: OSA, 2021. http://dx.doi.org/10.1364/cleo_at.2021.jtu3a.88.

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Li, Zhang, and Chen Weimin. "Key Technology of Artificial Intelligence in Hull Form Intelligent Optimization." In ICMAI 2020: 2020 5th International Conference on Mathematics and Artificial Intelligence. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3395260.3395296.

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Rongrong, Sun, Song Xin, Li Qing, Ning Baifeng, and Zhang Bing. "Application of Intelligent Safety Supervision Based on Artificial Intelligence Technology." In 2020 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS). IEEE, 2020. http://dx.doi.org/10.1109/tocs50858.2020.9339756.

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Reports on the topic "Artificial Intelligence technology"

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Pennock, K. A. Artificial intelligence technology assessment for the US Army Depot System Command. Office of Scientific and Technical Information (OSTI), July 1991. http://dx.doi.org/10.2172/5583473.

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Shields, Thomas E. Software Technology to Support Real-Time Embedded Artificial Intelligence-Based Applications. Phase 1. Fort Belvoir, VA: Defense Technical Information Center, May 1989. http://dx.doi.org/10.21236/ada209133.

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Hajek, B. K., and D. W. Miller. Installation and evaluation of a nuclear power plant operator advisor based on artificial intelligence technology. Office of Scientific and Technical Information (OSTI), June 1989. http://dx.doi.org/10.2172/7295840.

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Hajek, B. K., and D. W. Miller. Installation and evaluation of a nuclear power plant Operator Advisor based on artificial intelligence technology. Office of Scientific and Technical Information (OSTI), February 1993. http://dx.doi.org/10.2172/6657736.

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Szladow, A. J. Application of artificial intelligence technology to increase productivity, quality and energy efficiency in heavy industry. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1995. http://dx.doi.org/10.4095/315015.

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Nikiforov, Vladimir. Laser technology and integrated technical systems in devices and instruments for ophthalmology using elements of artificial intelligence associated with artificial neural networks. Intellectual Archive, May 2019. http://dx.doi.org/10.32370/iaj.2123.

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Browne, Josh. Efficient partnership models for energy technology startups enabled by artificial intelligence that hyper-targets ecosystem connectivity. Office of Scientific and Technical Information (OSTI), June 2021. http://dx.doi.org/10.2172/1804464.

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Hajek, B. K., and D. W. Miller. Installation and evaluation of a nuclear power plant Operator Advisor based on artificial intelligence technology. Final report. Office of Scientific and Technical Information (OSTI), February 1993. http://dx.doi.org/10.2172/10140777.

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Foster, Dakota, and Zachary Arnold. Antitrust and Artificial Intelligence: How Breaking Up Big Tech Could Affect the Pentagon’s Access to AI. Center for Security and Emerging Technology, May 2020. http://dx.doi.org/10.51593/20190025.

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Abstract:
While AI innovation would presumably continue in some form without Big Tech, the authors find that breaking up the largest technology companies could fundamentally change the broader AI innovation ecosystem, likely affecting the development of AI applications for national security.
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None, None. Opportunities and Challenges from Artificial Intelligence and Machine Learning for the Advancement of Science, Technology, and the Office of Science Missions. Office of Scientific and Technical Information (OSTI), September 2020. http://dx.doi.org/10.2172/1734848.

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