Artificial Intelligence Applications and Reconfigurable Architectures 2023
DOI: 10.1002/9781119857891.ch2
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Review of Artificial Intelligence Applications and Architectures

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Cited by 4 publications
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“…In this case, the system draws direct inspiration from the human brain and its neurons, effectively carrying out tasks such as pattern recognition. Additional methodologies can be considered Quantum Computing (QC) which provides the potential for solving complex problems much faster than classical computers (Ladd et al, 2010;Shor, 1999), High Radix computing for reduced interconnect complexity and increased computing density (Miller & Thornton, 2022), and Reconfigurable computing akin to the case of Field-Programmable Gate Arrays (FPGAs), which offer post-manufacturing reconfigurability, thereby yielding certain performance and efficiency advantages in specific applications (Almomany et al, 2023;Compton & Hauck, 2002;Thakare & Bhandari, 2023).…”
Section: Introductionmentioning
confidence: 99%
“…In this case, the system draws direct inspiration from the human brain and its neurons, effectively carrying out tasks such as pattern recognition. Additional methodologies can be considered Quantum Computing (QC) which provides the potential for solving complex problems much faster than classical computers (Ladd et al, 2010;Shor, 1999), High Radix computing for reduced interconnect complexity and increased computing density (Miller & Thornton, 2022), and Reconfigurable computing akin to the case of Field-Programmable Gate Arrays (FPGAs), which offer post-manufacturing reconfigurability, thereby yielding certain performance and efficiency advantages in specific applications (Almomany et al, 2023;Compton & Hauck, 2002;Thakare & Bhandari, 2023).…”
Section: Introductionmentioning
confidence: 99%