Literatura científica selecionada sobre o tema "Hardware for Artificial Intelligence"
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Artigos de revistas sobre o assunto "Hardware for Artificial Intelligence"
Burkert, Andreas. "Hardware for Artificial Intelligence". ATZ worldwide 121, n.º 5 (26 de abril de 2019): 8–13. http://dx.doi.org/10.1007/s38311-019-0060-0.
Texto completo da fonteBurkert, Andreas. "Hardware for Artificial Intelligence". ATZelectronics worldwide 14, n.º 3 (março de 2019): 8–13. http://dx.doi.org/10.1007/s38314-019-0026-4.
Texto completo da fontePopov, I. "SoC hardware supporting artificial intelligence". ELECTRONICS: Science, Technology, Business, n.º 7 (2018): 116–23. http://dx.doi.org/10.22184/1992-4178.2018.178.7.116.123.
Texto completo da fonteVerWey, John. "The Other Artificial Intelligence Hardware Problem". Computer 55, n.º 1 (janeiro de 2022): 34–42. http://dx.doi.org/10.1109/mc.2021.3113271.
Texto completo da fontePrati, Enrico. "Quantum neuromorphic hardware for quantum artificial intelligence". Journal of Physics: Conference Series 880 (agosto de 2017): 012018. http://dx.doi.org/10.1088/1742-6596/880/1/012018.
Texto completo da fonteYoon, Young Hyun, Dong Hyun Hwang, Jun Hyeok Yang e Seung Eun Lee. "Intellino: Processor for Embedded Artificial Intelligence". Electronics 9, n.º 7 (18 de julho de 2020): 1169. http://dx.doi.org/10.3390/electronics9071169.
Texto completo da fonteWang, Xiaoyin. "Artificial intelligence enhanced environmental detection system". Applied and Computational Engineering 66, n.º 1 (29 de maio de 2024): 156–59. http://dx.doi.org/10.54254/2755-2721/66/20240938.
Texto completo da fonteHNATCHUK, YELYZAVETA, YEVHENIY SIERHIEIEV e ALINA HNATCHUK. "USING ARTIFICIAL INTELLIGENCE ACCELERATORS TO TRAIN COMPUTER GAME CHARACTERS". Computer systems and information technologies, n.º 1 (21 de agosto de 2021): 63–70. http://dx.doi.org/10.31891/csit-2021-3-9.
Texto completo da fonteSmith, Adam Leon. "Artificial Intelligence". ITNOW 64, n.º 3 (19 de agosto de 2022): 47. http://dx.doi.org/10.1093/combul/bwac093.
Texto completo da fonteSmith, Adam Leon. "Artificial Intelligence". ITNOW 64, n.º 2 (12 de maio de 2022): 65. http://dx.doi.org/10.1093/itnow/bwac065.
Texto completo da fonteTeses / dissertações sobre o assunto "Hardware for Artificial Intelligence"
Orozco, Gabriel Mario. "Artificial intelligence opportunities and an end-do-end data-driven solution for predicting hardware failures". Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/104304.
Texto completo da fonteThesis: S.M. in Engineering Systems, Massachusetts Institute of Technology, Department of Mechanical Engineering, 2016. In conjunction with the Leaders for Global Operations Program at MIT.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 93-96).
Dell's target to provide quality products based on reliability, security, and manageability, has driven Dell Inc. to become one of the largest PC suppliers. The recent developments in Artificial Intelligence (AI) combined with a competitive market situation have encouraged Dell to research new opportunities. Al research and breakthroughs have risen in the last years, bringing along revolutionary technologies and companies that are disrupting all businesses. Over 30 potential concepts for Al integration at Dell Inc. were identified and evaluated to select the ones with the highest potential. The top-most concept consisted of preventing in real time the failure of hardware. This concept was investigated using a data science process. Currently, there exist a number of machine learning tools that automate the last stages of the proposed data science process to create predictive models. The utilized tools vary in functionality and evaluation standards, but also provide other services such as data and model storage and visualization options. The proposed solution utilizes the deep feature synthesis algorithm that automatically generates features from problem-specific data. These engineered features boosted predictive model accuracy by an average of 10% for the AUC and up to 250% in recall for test (out of sample) data. The proposed solution estimates an impact exceeding $407M in the first five years for Dell Inc. and all of the involved suppliers. Conservatively, the direct impact on Dell Inc. is particular to batteries under warranty and is expected to surpass $2.7M during the first five years. The conclusions show a high potential for implementation.
by Mario Orozco Gabriel.
M.B.A.
S.M. in Engineering Systems
Cheng, Chih Kang. "Hardware implementation of the complex Hopfield neural network". CSUSB ScholarWorks, 1995. https://scholarworks.lib.csusb.edu/etd-project/1016.
Texto completo da fonteGRIMALDI, MATTEO. "Hardware-Aware Compression Techniques for Embedded Deep Neural Networks". Doctoral thesis, Politecnico di Torino, 2021. http://hdl.handle.net/11583/2933756.
Texto completo da fonteBedi, Abhishek. "A generic platform for the evolution of hardware". Click here to access this resource online, 2009. http://hdl.handle.net/10292/651.
Texto completo da fonteMARRONE, FRANCESCO. "Memristor-based hardware accelerators: from device modeling to AI applications". Doctoral thesis, Politecnico di Torino, 2022. http://hdl.handle.net/11583/2972305.
Texto completo da fonteAl, Rawashdeh Khaled. "Toward a Hardware-assisted Online Intrusion Detection System Based on Deep Learning Algorithms for Resource-Limited Embedded Systems". University of Cincinnati / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1535464571843315.
Texto completo da fonteKumar, Sharad Kumar. "Analysis of Machine Learning Modeling Attacks on Ring Oscillator based Hardware Security". University of Toledo / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1541759752027838.
Texto completo da fonteCONTI, DANIELE. "Neuromorphic systems based on memristive devices - From the material science perspective to bio-inspired learning hardware". Doctoral thesis, Politecnico di Torino, 2018. http://hdl.handle.net/11583/2711511.
Texto completo da fonteImbulgoda, Liyangahawatte Gihan Janith Mendis. "Hardware Implementation and Applications of Deep Belief Networks". University of Akron / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=akron1476707730643462.
Texto completo da fonteBrink, Stephen Isaac. "Learning in silicon: a floating-gate based, biophysically inspired, neuromorphic hardware system with synaptic plasticity". Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/50143.
Texto completo da fonteLivros sobre o assunto "Hardware for Artificial Intelligence"
Mishra, Ashutosh, Jaekwang Cha, Hyunbin Park e Shiho Kim, eds. Artificial Intelligence and Hardware Accelerators. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-22170-5.
Texto completo da fonteAdamatzky, Andrew. Artificial life models in hardware. Dordrecht: Springer, 2009.
Encontre o texto completo da fonteKropf, Thomas. Introduction to Formal Hardware Verification. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999.
Encontre o texto completo da fonteBaofu, Peter. The future of post-human computing: A preface to a new theory of hardware, software and the mind. Great Abington, Cambridge, UK: Cambridge International Science Publishing, 2011.
Encontre o texto completo da fonteJovanović, Aleksandar S. Expert Systems in Structural Safety Assessment: Proceedings of an International Course October 2-4, 1989, Stuttgart, FRG. Berlin, Heidelberg: Springer Berlin Heidelberg, 1989.
Encontre o texto completo da fonteLee, Bang W. Hardware annealing in analog VLSI neurocomputing. Boston: Kluwer Academic Publishers, 1991.
Encontre o texto completo da fonteEder, Kerstin. Hardware and Software: Verification and Testing: 7th International Haifa Verification Conference, HVC 2011, Haifa, Israel, December 6-8, 2011, Revised Selected Papers. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.
Encontre o texto completo da fonteStrous, Leon. Internet of Things. Information Processing in an Increasingly Connected World: First IFIP International Cross-Domain Conference, IFIPIoT 2018, Held at the 24th IFIP World Computer Congress, WCC 2018, Poznan, Poland, September 18-19, 2018, Revised Selected Papers. Cham: Springer Nature, 2019.
Encontre o texto completo da fonteSood, A. K. Active Perception and Robot Vision. Berlin, Heidelberg: Springer Berlin Heidelberg, 1992.
Encontre o texto completo da fonteOman) ICC (Conference : Oman) (1st 2014 Muscat. Intelligent cloud computing: First International Conference, ICC 2014, Muscat, Oman, February 24-26, 2014, Revised selected papers. Cham: Springer, 2015.
Encontre o texto completo da fonteCapítulos de livros sobre o assunto "Hardware for Artificial Intelligence"
Mishra, Ashutosh, Pamul Yadav e Shiho Kim. "Artificial Intelligence Accelerators". In Artificial Intelligence and Hardware Accelerators, 1–52. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-22170-5_1.
Texto completo da fonteYadav, Pamul, Ashutosh Mishra e Shiho Kim. "Neuromorphic Hardware Accelerators". In Artificial Intelligence and Hardware Accelerators, 225–68. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-22170-5_8.
Texto completo da fonteLippmann, Bernhard, Matthias Ludwig e Horst Gieser. "Generating Trust in Hardware through Physical Inspection". In Embedded Artificial Intelligence, 45–59. New York: River Publishers, 2023. http://dx.doi.org/10.1201/9781003394440-5.
Texto completo da fonteLiu, Yanli, Bochen Guan, Weiyi Li, Qinwen Xu e Shuxue Quan. "SMOF: Squeezing More Out of Filters Yields Hardware-Friendly CNN Pruning". In Artificial Intelligence, 242–54. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-20497-5_20.
Texto completo da fonteBurns, Jeff. "The New Era of AI Hardware". In From Artificial Intelligence to Brain Intelligence, 55–65. New York: River Publishers, 2022. http://dx.doi.org/10.1201/9781003338215-4.
Texto completo da fonteJhung, Junekyo, Ho Suk, Hyungbin Park e Shiho Kim. "Hardware Accelerators for Autonomous Vehicles". In Artificial Intelligence and Hardware Accelerators, 269–317. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-22170-5_9.
Texto completo da fonteKim, Jinhyuk, e Shiho Kim. "Hardware Accelerators in Embedded Systems". In Artificial Intelligence and Hardware Accelerators, 167–81. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-22170-5_6.
Texto completo da fonteNedjah, Nadia, e Luiza de Macedo Mourelle. "Hardware Architecture for Genetic Algorithms". In Innovations in Applied Artificial Intelligence, 554–56. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11504894_76.
Texto completo da fonteDimopoulos, Alexandros, Christos Pavlatos, Ioannis Panagopoulos e George Papakonstantinou. "An Efficient Hardware Implementation for AI Applications". In Advances in Artificial Intelligence, 35–45. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11752912_6.
Texto completo da fonteAbidi, Taha Yassine, Iyad Dayoub, Elhadj Doguech e Ihsen Alouani. "Federated Learning: Privacy, Security and Hardware Perspectives". In Advancing Edge Artificial Intelligence, 65–86. New York: River Publishers, 2024. http://dx.doi.org/10.1201/9781003478713-3.
Texto completo da fonteTrabalhos de conferências sobre o assunto "Hardware for Artificial Intelligence"
Dally, William J., C. Thomas Gray, John Poulton, Brucek Khailany, John Wilson e Larry Dennison. "Hardware-Enabled Artificial Intelligence". In 2018 IEEE Symposium on VLSI Circuits. IEEE, 2018. http://dx.doi.org/10.1109/vlsic.2018.8502368.
Texto completo da fonte"Hardware for AI". In Emerging Topics in Artificial Intelligence (ETAI) 2021, editado por Giovanni Volpe, Joana B. Pereira, Daniel Brunner e Aydogan Ozcan. SPIE, 2021. http://dx.doi.org/10.1117/12.2606000.
Texto completo da fonteDinu, A., e P. L. Ogrutan. "Opportunities of using artificial intelligence in hardware verification". In 2019 IEEE 25th International Symposium for Design and Technology in Electronic Packaging (SIITME). IEEE, 2019. http://dx.doi.org/10.1109/siitme47687.2019.8990751.
Texto completo da fonteFojtik, Rostislav. "USING HARDWARE TO SUPPORT ARTIFICIAL INTELLIGENCE IN EDUCATION". In 18th International Technology, Education and Development Conference. IATED, 2024. http://dx.doi.org/10.21125/inted.2024.1170.
Texto completo da fonteLim, Kah Yee, Joan Hau e Yiqi Tew. "Computer Performance Evaluation for Virtual Classroom with Artificial Intelligence Features". In International Conference on Digital Transformation and Applications (ICDXA 2021). Tunku Abdul Rahman University College, 2021. http://dx.doi.org/10.56453/icdxa.2021.1008.
Texto completo da fonteAdamov, Andrey Anatolievich, e Leonid Konstantinovich Eisymont. "Variants of hardware architectural solutions for artificial intelligence systems". In 3rd International Conference “Futurity designing. Digital reality problems”. Keldysh Institute of Applied Mathematics, 2020. http://dx.doi.org/10.20948/future-2020-10.
Texto completo da fonteRomero, A., C. Heras, M. Vega, J. Naranjo, C. Vázquez e A. Preciado. "Intelligent Open-Hardware ECG Platform for the Heart Patients Control and Diagnosis". In Artificial Intelligence and Applications. Calgary,AB,Canada: ACTAPRESS, 2010. http://dx.doi.org/10.2316/p.2010.674-144.
Texto completo da fonteAttri, Anant, Sandhya Verma, Shweta Pandey, Yerrolla Chanti, Mansi Sahu e Rajat Balyan. "Exhilarating Growth in Education Through Artificial Intelligence". In 2023 International Conference on Quantum Technologies, Communications, Computing, Hardware and Embedded Systems Security (iQ-CCHESS). IEEE, 2023. http://dx.doi.org/10.1109/iq-cchess56596.2023.10391474.
Texto completo da fonteSingh, Vinayak, Abhiranjan Dixit, Shweta Pandey, Bura Vijay Kumar, Vikrant Pachouri e Mansi Sahu. "Role of Artificial Intelligence in Criminal Investigation". In 2023 International Conference on Quantum Technologies, Communications, Computing, Hardware and Embedded Systems Security (iQ-CCHESS). IEEE, 2023. http://dx.doi.org/10.1109/iq-cchess56596.2023.10391288.
Texto completo da fonteBurguete-Lopez, Arturo, Maksim Makarenko, Qizhou Wang, Fedor Getman e Andrea Fratalocchi. "Artificial-Intelligence Empowered Universal Metrology Optical Camera". In CLEO: Applications and Technology. Washington, D.C.: Optica Publishing Group, 2023. http://dx.doi.org/10.1364/cleo_at.2023.jtu2a.25.
Texto completo da fonteRelatórios de organizações sobre o assunto "Hardware for Artificial Intelligence"
Lohn, Andrew, e Micah Musser. AI and Compute: How Much Longer Can Computing Power Drive Artificial Intelligence Progress? Center for Security and Emerging Technology, janeiro de 2022. http://dx.doi.org/10.51593/2021ca009.
Texto completo da fonteMusser, Micah, Rebecca Gelles, Catherine Aiken e Andrew Lohn. “The Main Resource is the Human”. Center for Security and Emerging Technology, abril de 2023. http://dx.doi.org/10.51593/20210071.
Texto completo da fonteRuvinsky, Alicia, Timothy Garton, Daniel Chausse, Rajeev Agrawal, Harland Yu e Ernest Miller. Accelerating the tactical decision process with High-Performance Computing (HPC) on the edge : motivation, framework, and use cases. Engineer Research and Development Center (U.S.), setembro de 2021. http://dx.doi.org/10.21079/11681/42169.
Texto completo da fonteanis, sehab. Artificial Intelligence. ResearchHub Technologies, Inc., agosto de 2023. http://dx.doi.org/10.55277/researchhub.agwfnyrw.
Texto completo da fonteRoberts, Kamie. Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile. Gaithersburg, MD: National Institute of Standards and Technology, 2024. http://dx.doi.org/10.6028/nist.ai.600-1.
Texto completo da fonteNovak, Jr, Simmons Gordon S., Porter Robert F., Kumar Bruce W., Causey Vipin e Robert L. Artificial Intelligence Project. Fort Belvoir, VA: Defense Technical Information Center, janeiro de 1990. http://dx.doi.org/10.21236/ada230793.
Texto completo da fonteGuerreiro, Joao, Sergio Rebelo e Pedro Teles. Regulating Artificial Intelligence. Cambridge, MA: National Bureau of Economic Research, novembro de 2023. http://dx.doi.org/10.3386/w31921.
Texto completo da fonteCwik, Cynthia, Paul Grimm, Maura Grossman e Toby Walsh. Artificial Intelligence and the Courts: Artificial Intelligence Trustworthiness, and Litigation. American Association for the Advancement of Science, setembro de 2022. http://dx.doi.org/10.1126/aaas.adf0786.
Texto completo da fonteKaranicolas, Michael, e Mallory Knodel. Artificial Intelligence and the Courts: Artificial Intelligence and Bias - An Evaluation. American Association for the Advancement of Science, setembro de 2022. http://dx.doi.org/10.1126/aaas.adf0788.
Texto completo da fonteFirth-Butterfield, Kay, e Karen Silverman. Artificial Intelligence and the Courts: Artificial Intelligence - Foundational Issues and Glossary. American Association for the Advancement of Science, setembro de 2022. http://dx.doi.org/10.1126/aaas.adf0782.
Texto completo da fonte