Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

arXiv:quant-ph/0401124

Quantum Artificial Intelligence

Bachir Aoun, Mohamad Tarifi

Published Jan 20, 2004• 3 citations
arXivHTMLPDF

Abstract

This report introduces researchers in AI to some of the concepts in quantum heurisitics and quantum AI.
DOI
10.48550/arxiv.quant-ph/0401124

Related papers

Quantum AI: Achievements and Challenges in the Interplay of Quantum Computing and Artificial Intelligence

Iñaki Fernández Pérez, Fernando De la Prieta, Sara Rodrı́guez +2 more

Lecture notes in networks and systems•Jan 1, 2023•13 citations

Business Research Methods

Geetha Manoharan, Sanjeev Kumar

Data-driven selection changes corporate research. Quantum artificial intelligence (QAI) is changing business research. Quantum AI's processing power and ability to build sophisticated probabilistic models change hypothesis testing, data analysis, predictive modeling, and strategic vision. Quantum algorithms can increase quantitative and qualitative research accuracy, speed, and scalability. QAI on massive, unstructured data may reveal hidden styles, simulate complex market dynamics, and help researchers make faster, more informed business choices. QAI allows real-time optimization and multidimensional assessment in research, which conventional computer approaches cannot. The bankruptcy also investigates QAI's implications, morals, and organizational demands in academic and industry-led business research. It emphasizes transdisciplinary knowledge, virtual literacy, and agile study design to maximize growth. By combining quantum computers with business studies, this concept establishes a new paradigm for innovation and research.

Advances in computational intelligence and robotics book series•Mar 13, 2026•0 citations

Quantum Artificial Intelligence with Qiskit

Andreas Wichert

Quantum Artificial Intelligence (QAI) is a new interdisciplinary research field that combines quantum computing with Artificial Intelligence (AI), aiming to use the unique properties of quantum computers to enhance the capabilities of AI systems. Quantum Artificial Intelligence with Qiskit provides a cohesive overview of the field of QAI, providing the tools for readers to create and manipulate quantum programs on devices as accessible as a laptop computer. Introducing symbolical quantum algorithms, sub-symbolical quantum algorithms, and quantum Machine Learning (ML) algorithms, this book explains each process step by step with associated Qiskit listings. All examples are additionally available for download at https://github.com/andrzejwichert/qai. Allowing readers to learn the basic concepts of quantum computing on their home computers, this book is accessible to both the general readership as well as students and instructors of courses relating to computer science and AI.

Chapman & Hall/CRC eBooks•Nov 28, 2023•1 citation

Quantum AI: Exploring the Intersection of Quantum Computing and Artificial Intelligence

Sanniva Halder Bapon, Amandeep Kaur

•Jan 1, 2024•1 citation

Artificial intelligence (AI) for quantum and quantum for AI

Yingzhao Zhu, Kefeng Yu

Optical and Quantum Electronics•Jun 8, 2023•40 citations

Exploring the potential of Elon musk's proposed quantum AI: A comprehensive analysis and implications

Idoko Peter Idoko, Onuh Matthew Ijiga, Lawrence Anebi Enyejo +3 more

Elon Musk has recently introduced the concept of Quantum AI, suggesting a revolutionary integration of quantum computing capabilities with artificial intelligence. This research aims to delve into the theoretical foundations, technological aspects, and potential applications of Musk's proposed Quantum AI. By conducting an in-depth analysis, this study seeks to unravel the unique features and challenges associated with the fusion of quantum computing and artificial intelligence, offering insights into the transformative impact on computational power, machine learning, and problem-solving capabilities. Additionally, the research will explore the ethical considerations and societal implications of deploying Quantum AI, paving the way for a comprehensive understanding of its potential benefits and risks. This investigation aims to contribute to the evolving discourse on the convergence of quantum computing and artificial intelligence, shedding light on the path towards harnessing the full potential of Musk's visionary proposal.

Global Journal of Engineering and Technology Advances•Mar 13, 2024•33 citations
Data-driven selection changes corporate research. Quantum artificial intelligence (QAI) is changing business research. Quantum AI's processing power and ability to build sophisticated probabilistic models change hypothesis testing, data analysis, predictive modeling, and strategic vision. Quantum algorithms can increase quantitative and qualitative research accuracy, speed, and scalability. QAI on massive, unstructured data may reveal hidden styles, simulate complex market dynamics, and help researchers make faster, more informed business choices. QAI allows real-time optimization and multidimensional assessment in research, which conventional computer approaches cannot. The bankruptcy also investigates QAI's implications, morals, and organizational demands in academic and industry-led business research. It emphasizes transdisciplinary knowledge, virtual literacy, and agile study design to maximize growth. By combining quantum computers with business studies, this concept establishes a new paradigm for innovation and research.
Quantum Artificial Intelligence (QAI) is a new interdisciplinary research field that combines quantum computing with Artificial Intelligence (AI), aiming to use the unique properties of quantum computers to enhance the capabilities of AI systems. Quantum Artificial Intelligence with Qiskit provides a cohesive overview of the field of QAI, providing the tools for readers to create and manipulate quantum programs on devices as accessible as a laptop computer. Introducing symbolical quantum algorithms, sub-symbolical quantum algorithms, and quantum Machine Learning (ML) algorithms, this book explains each process step by step with associated Qiskit listings. All examples are additionally available for download at https://github.com/andrzejwichert/qai. Allowing readers to learn the basic concepts of quantum computing on their home computers, this book is accessible to both the general readership as well as students and instructors of courses relating to computer science and AI.
Elon Musk has recently introduced the concept of Quantum AI, suggesting a revolutionary integration of quantum computing capabilities with artificial intelligence. This research aims to delve into the theoretical foundations, technological aspects, and potential applications of Musk's proposed Quantum AI. By conducting an in-depth analysis, this study seeks to unravel the unique features and challenges associated with the fusion of quantum computing and artificial intelligence, offering insights into the transformative impact on computational power, machine learning, and problem-solving capabilities. Additionally, the research will explore the ethical considerations and societal implications of deploying Quantum AI, paving the way for a comprehensive understanding of its potential benefits and risks. This investigation aims to contribute to the evolving discourse on the convergence of quantum computing and artificial intelligence, shedding light on the path towards harnessing the full potential of Musk's visionary proposal.