Quantum computing is a field of computing that uses the principles of quantum mechanics to build computer systems that can perform certain types of computation much faster than classical computers. In a classical computer, information is processed using bits, which can represent either a 0 or a 1. In a quantum computer, information is processed using quantum bits, or qubits, which can represent both 0 and 1 simultaneously, a property known as superposition. Additionally, qubits can also become entangled, meaning that the state of one qubit can affect the state of another, even when they are separated by large distances.

Quantum computing has the potential to revolutionize AI by providing new algorithms and hardware that can solve problems that are intractable for classical computers. One of the most exciting applications of quantum computing for AI is in deep learning, where quantum algorithms can be used to train large neural networks much faster than classical algorithms. Additionally, quantum computers have the potential to accelerate other important AI tasks, such as reinforcement learning and unsupervised learning, by providing new algorithms and hardware that can process large amounts of data more efficiently.

However, it's important to note that quantum computing is still in its early stages and that many technical challenges still need to be overcome before it becomes a mainstream technology. Additionally, the development of quantum algorithms that can be used to solve real-world problems is still in its early stages, so it will be some time before we see the full potential of quantum computing for AI.