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Quantum computing is one of the most intriguing areas of scientific and technological development of the last century. More recently, artificial intelligence (AI) is being used in tandem with quantum computing to unleash a wealth of new possibilities – all of which can benefit humankind in a big way.

But what exactly is quantum AI computing? And how are technologies like AI edge computing systems helping to pave the way for new applications? Find out in our article.

AI quantum computing is essentially the melding of artificial intelligence with quantum technology – an exciting area of development in the fields of computing, data processing, and data transmission.

The story of quantum computing begins over a century ago, with quantum theory and the work of physicist Max Planck. Planck theorized that energy is not in a continuous flow but is rather comprised of individual units, known as quanta. This theory has been used to explain the difference between particle behaviors on a macro level and a micro level.

• At a macro-level – i.e., the level we perceive in the world around us, the laws of physics dictate that nothing can travel faster than the speed of light and that objects must move across space to get from point A to point B.
• At the micro-level – i.e., the sub-atomic level, things seem to behave differently. An electron can seemingly disappear from one sub-atomic shell, for example, and then reappear in another instantaneously. This apparent violation of the laws of physics is explained by the observation that electrons need a quantum of energy to move between shells – an indivisible unit of energy.

This is a basic explanation of a revolutionary idea. Harnessing quantum theory in computing networks can change the way data is processed, handled, and transmitted. In fact, quantum computing is already paving the way for the technology of tomorrow.

We don't have the space to fully explain the complexities of quantum computing here, but we can provide a basic overview of its key aspects.

At its heart, quantum computing relies on two principles – quantum superposition and quantum entanglement.

• Quantum superposition is the ability of particles to exist in multiple states at the same time.
• Quantum entanglement is the ability of particles to become entangled together, "communicating" with one another instantaneously.

It all comes down to data. With normal computing networks, data exists in bits. A bit is either 0 or 1. Traditional computing data is made up of vast combinations of these 0s and 1s.

With quantum computing networks, data exists in qubits. Qubits can be both 0 and 1 at the same time, thanks to superposition.

Also, these qubits can be entangled. Once entangled, the state or movement of one qubit directly influences that of the other. Even when the qubits are separated, this communication still takes place, with no delay.

So how does this impact computing?

Well, thanks to superposition, quantum computing networks can handle a vast amount of processes simultaneously. There is no need to complete each process in series, dramatically accelerating network speed and enhancing capability.

Meanwhile, because of entanglement, data can be transmitted instantly, even over vast distances. This makes real-time communication between satellites and bases back on Earth possible, even though our observable laws of physics should make this impossible.

The role of AI in quantum computing lies in data management. Quantum networks require large amounts of data, and organizing these stores can be a challenge.

With AI components installed, the network can make sure data is delivered where it needs to be. This leaves the door open for new and exciting applications, bringing together two cutting-edge technologies in a manner that is immediately useful to humanity.

How are these technologies deployed together in practice? There is almost a whole world of possibility here, but below are a few key examples.

Quantum AI computing may help us to develop new and high-yielding drugs. The technology is already being used in the healthcare industry to engineer proteins that are designed with key medical objectives in mind.

This is simply not achievable with traditional computers. Modeling and engineering complex molecules in precise detail requires too much data. However, quantum computing, supported by AI, is certainly capable of this level of performance.

Risk is something that has always plagued the finance industry. Organizations are constantly on the lookout for ways to reduce risk and improve their market outlook.

This is where artificial intelligence and machine learning can take a more active role. AI and ML gather the data required to power the high-performance computing network's powerful modeling capabilities. Analysts are then able to predict further into the future with greater accuracy.

Entanglement enables qubits to influence one another's state, even when separated across vast distances. This means humans aboard a space station or another craft can communicate in real time with teams back on Earth by manipulating the state of one qubit and observing the change in its entangled partner.

Thanks to AI and ML, communication is not limited to human teams. Smart systems will also be able to use this technology to interact with no latency period.

Quantum AI edge computing devices can place the power of quantum technology within the supply chain itself. This essentially turns the entire supply chain – from loading bays and object recognition devices to the manufacturing machinery itself – into a smart system, ready to collect and process data. 

But as the global supply chain grows increasingly complex, more powerful systems will be needed to process the data produced by such a sophisticated Internet of Things (IoT) setup. As mentioned above, quantum superposition delivers the capacity required to support this change.

To find the components you need for your own high-performance computing system, or for another purpose, explore our product pages today. Or reach out directly to our team and find out more.