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Computing will take AI to the Next Level

Taking AI To The Next Level With Quantum Computing

Artificial intelligence shows excellent potential but is currently limited in its use to specialised machine learning algorithms. It can perform specific tasks in an automated way, but not much besides. Quantum developments will change this, and qubits will rise AI up to a new level. Qubits represent an upgraded version of bits in the binary system, providing greater computational power to tasks. This is achieved through superposition and entanglement, which allows multiplication of the computational scheme. Superposition is that qubits are able to exist and bear reference in multiple states of 1 and 0 at the same time. Meanwhile, entanglement processes mean that qubits can have an influence over other qubits even when they are not actually connected to one another physically.

The extra power delivered by qubits is considered by some to be very good for artificial intelligence development. IBM carried out an experiment showing that running a simple classification task first without entangling qubits delivered an error rate of 5%, but with the qubits entangled achieved an error rate of just 2.5%. Research by the National University of Singapore and mirrored by Futurism magazine demonstrates a new linear quantum algorithm which provides opportunities for a much more rapid analysis of bigger data sets using a quantum computer. Until now qubits have been somewhat delicate and their quantum state easily undone, but these findings change things.

The new linear algorithm produced by those at the National University of Singapore demonstrates how a classic algorithm procedure can run through quantum computing to add extra power through superposition and entanglement. This algorithm computes using a large data matrix, and utilizing a quantum computer is much more suitable to achieve this. One really important application of this could be using this formula in artificial intelligence to speed up machine learning through harnessing the power of quantum information processing.

It is worth considering that while these examples are very promising in these early days of quantum computing, work on AI neural networks is also showing considerable promise. When these operate on regular but powerful computers they do very well indeed in terms of the results achieved. Nonetheless, experts have expressed their confidence that machine learning capability can be advanced considerably through leveraging the power and abilities of quantum computers. This could lead to our being able to significantly surpass the limitations that we are currently experiencing utilising conventional computing systems. Find out more about how quantum computing will transform AI.

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