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Asian Conference on Innovation in Technology (ASIANCON)

Unleashing the Power of Generative AI and Quantum Computing for Mutual Advancements

Sagar Pise, Aarti Amod Agarkar, Sachin Jain

Published Aug 25, 2023• 7 citations
Publisher

Abstract

The paper aims to explore the symbiotic relationship between Generative Artificial Intelligence (AI) and Quantum Computing. This cutting-edge event will delve into the potential synergies between these two transformative technologies and demonstrate how their collaboration can revolutionize various domains. The paper will commence with an insightful overview of Generative AI and Quantum Computing, shedding light on their fundamental concepts and applications, capabilities and challenges. The paper will emphasize how Generative AI can reciprocate and contribute to the advancement of Quantum Computing. It will inspire collaboration, spark new research directions, and pave the way for ground-breaking advancements at the intersection of Generative AI and Quantum Computing.

DOI
10.1109/asiancon58793.2023.10270193

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The paper aims to explore the symbiotic relationship between Generative Artificial Intelligence (AI) and Quantum Computing. This cutting-edge event will delve into the potential synergies between these two transformative technologies and demonstrate how their collaboration can revolutionize various domains. The paper will commence with an insightful overview of Generative AI and Quantum Computing, shedding light on their fundamental concepts and applications, capabilities and challenges. The paper will emphasize how Generative AI can reciprocate and contribute to the advancement of Quantum Computing. It will inspire collaboration, spark new research directions, and pave the way for ground-breaking advancements at the intersection of Generative AI and Quantum Computing.
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Quantum computing promises revolutionary advancements in computational power, offering potential breakthroughs for artificial intelligence (AI) applications. the intersection of quantum computing and AI, highlighting the transformative capabilities and challenges in leveraging quantum mechanics to enhance machine learning algorithms. Key areas of focus include quantum algorithms for optimization, machine learning models, and data analysis, emphasizing the potential to solve complex problems exponentially faster than classical computers. However, significant challenges such as quantum decoherence, error correction, and scalability hinder seamless integration. current research efforts, discusses theoretical frameworks, and proposes future directions to harness the full potential of quantum AI synergy while addressing technical obstacles.
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