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In order to create novel algorithms and computational techniques for handling challenging problems, the area of study known as quantum artificial intelligence (QAI) combines ideas from quantum physics and machine learning.
Bits, which can only exist in one of two possible states (0 or 1), are used by conventional computers to store and analyse information. Qubits, which can exist in numerous states simultaneously and are used in quantum computers, enable for much more powerful and effective computation.
Quantum computing is used in QAI to accelerate specific machine learning methods, including clustering, classification, and optimisation. Additionally, it entails creating novel methods that benefit from the special features of quantum computing, including superposition, entanglement, and interference.
The creation of quantum neural networks, which use qubits to simulate neurons and synapses and may perform better on some tasks than classical neural networks, is one possible use for QAI.
Another possible application is in quantum chemistry, where quantum computers might be used to more effectively simulate molecule behaviour and create new drugs.
However, since quantum computing is still in its infancy, many technical and practical obstacles must be surmounted before QAI can be broadly adopted as a technology.
Global Quantum artificial intelligence market accounted for $XX Billion in 2022 and is anticipated to reach $XX Billion by 2030, registering a CAGR of XX% from 2023 to 2030.
In order to reduce the size of computation with quantum neural networks, Mitsubishi Electric Corporation has developed a quantum AI technology that automatically designs and optimises inference models.
Even with sparse data, the new quantum AI technology can overcome the drawbacks of conventional AI to achieve better performance while drastically reducing the scale of AI models.
By utilising quantum physics to manipulate qubit states in a highly parallel way, rapidly evolving quantum computers are anticipated to surpass classical computers.
Additionally, Nvidia revealed CUDA Quantum, a platform for creating quantum algorithms using the well-known C++ and Python programming languages. Depending on which system is most appropriate, the programme would assist in running the algorithm on both quantum and conventional computers.
Domain scientists will be able to utilise a new disruptive computing technology through CUDA Quantum and seamlessly incorporate quantum into their applications.
