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aimultiple.com
article
https://aimultiple.com/quantum-ai
## What is quantum AI? Quantum AI is the use of quantum computing to compute machine learning algorithms. Thanks to the computational advantages of quantum computing, quantum AI can achieve results that are not possible with classical computers. ## What is quantum computing? Quantum computing can be used for rapid training of machine learning models and for creating optimized algorithms. An optimized, stable AI enabled by quantum computing can complete years of analysis in a short time, advancing technology. ## Breakthroughs in Quantum AI. ## How does quantum AI work? ## What are the possibilities of applying quantum computing in AI? The contribution of quantum computing to classical machine learning can be achieved by quickly providing the optimal weight set for artificial neural networks. AI powered by quantum computing can be promising for near-term applications such as encryption. * Compelling AI applications that outperform classical computing with quantum computing. ## AI for Quantum Computing.
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en.wikipedia.org
article
https://en.wikipedia.org/wiki/Quantum_machine_learning
A number of quantum algorithms for machine learning are based on the idea of amplitude encoding, that is, to associate the [amplitudes](/wiki/Probability_amplitude "Probability amplitude") of a quantum state with the inputs and outputs of computations.[[30]](#cite_note-Patrick_Rebentrost_2014-30)[[31]](#cite_note-Nathan_Wiebe_2012-31)[[32]](#cite_note-Maria_Schuld_2016-32) Since a state of n {\displaystyle n}  qubits is described by 2 n {\displaystyle 2^{n}}  complex amplitudes, this information encoding can allow for an exponentially compact representation. One of these conditions is that a [Hamiltonian](/wiki/Hamiltonian_(quantum_mechanics) "Hamiltonian (quantum mechanics)") which entry-wise corresponds to the matrix can be simulated efficiently, which is known to be possible if the matrix is sparse[[34]](#cite_note-34) or low rank.[[35]](#cite_note-35) For reference, any known classical algorithm for [matrix inversion](/wiki/Matrix_inversion "Matrix inversion") requires a number of operations that grows [more than quadratically in the dimension of the matrix](/wiki/Computational_complexity_of_mathematical_operations#Matrix_algebra "Computational complexity of mathematical operations") (e.g. O ( n 2.373 ) {\displaystyle O{\mathord {\left(n^{2.373}\right)}}} ), but they are not restricted to sparse matrices. **[^](#cite_ref-118)** ["Can quantum machine learning move beyond its own hype?"](https://www.quantamagazine.org/job-one-for-quantum-computers-boost-artificial-intelligence-20180129/).
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medium.com
article
https://medium.com/@hassaanidrees7/quantum-machine-learning-the-next-frontier…
By leveraging the unique properties of quantum computing, QML has the potential to solve complex problems exponentially faster than classical methods, enabling breakthroughs in areas such as optimization, data analysis, and drug discovery. While classical machine learning relies on classical computers, QML leverages **quantum computers** to process and analyze data more efficiently, especially when dealing with large-scale or complex datasets. In Quantum Machine Learning, quantum computers are used to process data, train models, and optimize solutions, often enhancing the performance of classical machine learning algorithms. Quantum Machine Learning can improve the performance of AI models used for tasks like natural language processing (NLP), image recognition, and recommendation systems. Quantum and classical systems will likely work together for the foreseeable future, with QML accelerating specific parts of the machine learning pipeline, such as data preprocessing, optimization, or matrix operations. Quantum Machine Learning represents a bold new frontier in artificial intelligence, promising to accelerate machine learning tasks, optimize complex processes, and solve problems that are currently intractable for classical computers.
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pennylane.ai
article
https://pennylane.ai/qml/whatisqml
Quantum machine learning is a research area that explores the interplay of ideas from quantum computing and machine learning.
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sciencedirect.com
article
https://www.sciencedirect.com/science/article/pii/S2215016125001645
This review gives an overview of QML, from advancements in quantum-enhanced classical ML to native quantum algorithms and hybrid quantum-classical frameworks.
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research.ibm.com
research
https://research.ibm.com/topics/quantum-machine-learning
We now know that quantum computers have the potential to boost the performance of machine learning systems, and may eventually power efforts in fields from drug
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quantumai.google
article
https://quantumai.google/
# Google Quantum AI. [Skip to main content](https://quantumai.google/#main-content). [](https://quantumai.google/). [Discover](https://quantumai.google/discover/whatisqc). * [What is quantum computing?](https://quantumai.google/discover/whatisqc). * [Educational resources](https://quantumai.google/resources). [Our Work](https://quantumai.google/quantumcomputer). * [Roadmap](https://quantumai.google/roadmap). * [Quantum Computer](https://quantumai.google/quantumcomputer). * [Research Publications](https://quantumai.google/research). * [Open Source Tools](https://quantumai.google/software). * [Cirq Documentation](https://quantumai.google/cirq). [About](https://quantumai.google/team). * [Team](https://quantumai.google/team). * [Lab](https://quantumai.google/lab). [](https://quantumai.google/). * [Discover](https://quantumai.google/discover/whatisqc). * [Our Work](https://quantumai.google/quantumcomputer). * [About](https://quantumai.google/team). * [What is quantum computing?](https://quantumai.google/discover/whatisqc). * [Educational resources](https://quantumai.google/resources). * [Roadmap](https://quantumai.google/roadmap). * [Quantum Computer](https://quantumai.google/quantumcomputer). * [Research Publications](https://quantumai.google/research). * [Open Source Tools](https://quantumai.google/software). * [Cirq Documentation](https://quantumai.google/cirq). * [Team](https://quantumai.google/team). * [Lab](https://quantumai.google/lab). * [Google Quantum AI](https://quantumai.google/). [](https://quantumai.google/#mission). [open_in_new Blog post](https://blog.google/technology/research/quantum-echoes-willow-verifiable-quantum-advantage/)[open_in_new Paper](https://www.nature.com/articles/s41586-025-09526-6)[open_in_new Video](https://youtu.be/mEBCQidaNTQ) . [open_in_new Blog post](https://blog.google/technology/research/google-willow-quantum-chip/)[open_in_new Paper](https://www.nature.com/articles/s41586-024-08449-y)[open_in_new Video](https://www.youtube.com/watch?v=W7ppd_RY-UE)[open_in_new Spec Sheet](https://quantumai.google/static/site-assets/downloads/willow-spec-sheet.pdf) . . [arrow_forward](https://blog.google/technology/research/google-willow-quantum-chip/). . [arrow_forward](https://research.google/blog/making-quantum-error-correction-work/). . [arrow_forward](https://developers.googleblog.com/unlocking-the-potential-of-quantum-computing-a-developers-guide-to-error-correction/). . [arrow_forward](https://research.google/blog/validating-random-circuit-sampling-as-a-benchmark-for-measuring-quantum-progress/). . [arrow_forward](https://coursera.org/learn/quantum-error-correction). . [arrow_forward](https://services.google.com/fh/files/misc/google_quantum_ai_about.pdf). . [arrow_forward](https://quantumai.google/learn/map). . [arrow_forward](https://quantumai.google/learn/lab). [](https://developers.google.com/). * [About Google](https://about.google/). * [Privacy](https://policies.google.com/privacy). * [Terms](https://policies.google.com/terms). * [Terms](https://policies.google.com/terms). * [Privacy](https://policies.google.com/privacy). * [Manage cookies](https://quantumai.google/#).
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pasqal.com
article
https://www.pasqal.com/blog/quantum-ai-explained-the-essential-guide-for-busi…
By combining the parallel processing capabilities of quantum computing with the predictive power of AI, businesses can solve complex problems faster and more efficiently than ever before. By utilizing the computational superiority of quantum systems, Quantum AI can achieve results beyond the capability of classical computers, solving complex problems faster and more efficiently. The real game-changer comes when we integrate quantum computing, High-Performance Classical Computing (HPC), and AI into a unified approach to solving complex problems. In the short term, this synergy between Quantum Computing, HPC, and AI allows for hybrid problem-solving in several industries, to name a few:. Integrating quantum computing with classical systems and AI today offers a key advantage: each technology complements the other. As the trinity of quantum computing, AI, and HPC continues to evolve, those already integrating these technologies will be positioned to **lead their industries into the future**.