The Dawning of a New Era: ”Quantum computing is actually quite different while being quite similar to how quantum computing will revolutionize AI. ”

Introduction

Quantum computing is a method of computing that uses principles of quantum theory for inputs and outputs. Superposition and entanglement are two such quantum phenomena that make quantum computing a far more efficient way of processing data. It is expected that with the emergence of quantum computing AI, there will be a revolution in the industry.

Towards the end of the second world war, John von Neumann proposed a design based on a centralized control unit with fixed wiring and a series of interchangeable cabinets which made up what is commonly known today as classical computer architecture.

Classical computing uses basic bits that can only operate in one of two states, 0 or 1. Today the fastest computers are capable of doing trillions of calculations per second, yet the capabilities of such supercomputers are still defined by the use of binary bits. As the code and databases become more intricate, existing computers will not be able to handle the computations.

 Quantum computers have the potential of increasing computing capability, storage capacity as well as speed several notches higher than conventional computers. This means that they are best suited for the transformation of AI due to their unique architectural structure.

>>The Power of Qubits

Quantum computers are built from the most basic units named qubits or quantum bits. Superposition is one of the properties of qubit that allows for more than one state to be represented in the system at the same time. They can also be entangled meaning that two qubits are jointed in one global quantum state. Consequently, increasing the number of qubits results in an even more dramatic improvement in the performance of a quantum computer than it would in an ordinary one, because it rises exponentially. Just a few hundred qubits could have capabilities in terms of computational processing, beyond even all the classical computers in the world!

 Machine learning and artificial neural networks are very computation and data-driven. Quantum computing is capable of running through enormous amounts of data and finding correlations that can be difficult to discern.  

>>Technological advancements and the revolutionary applications of machine learning

Most researchers affirm that quantum computing will bring about radical transformations to artificial intelligence. Some of the most powerful algorithms, such as neural networks, are able to consider vast training datasets and extract intricate features from them. A problem that is inherent with classical computers is that the processing system they employ limits the volume and density of data that AI can currently handle. Quantum computers can handle data as big as the ones a classical computer cannot and often find more complex relations. This will drive deep learning and the most advanced AI that anyone can probably imagine.

 We are still in the early stages of what might be called the Model-T phase of leveraging quantum physics in developing AI. It should be noted that considerably more research into the phenomena remains to be carried out, but much potential for future development can be seen.

>>A promising specialty waiting to expand its sphere of activity

Quantum computing for AI is still in its infancy though widely discussed as a promising field. There are many ongoing research studies at such organizations as Google, IBM, and D-Wave to explore the opportunity of applying quantum computers for enhancing machine learning while cooperating with classical systems. Here we have to see far more significant improvements in algorithms, in software, in the design of processors, and in the construction of quantum systems themselves to really unlock those possibilities. However, it is important to understand that research in this field has only just begun, yet the potential is huge. Quantum technology augmented with artificial intelligence can take computing to its next level.

>>Conclusion

The quantum computing thus has the potential to disrupt artificial intelligence as we know it today. Quantum AI is still a budding field that has the potential to revolutionalize everything from the scales of computation to data analysis and the ability to find patterns that other, more familiar computer architectures cannot. Due to the vast future that quantum mechanics and learning algorithms have in store for each other, this new paradigm of computing could introduce the next level of AI capabilities. As we have seen, quantum AI is a field filled with prospects and opportunities, and the future of this technology is nothing short of thrilling.