Predicting Cryptocurrency Performance with Quantum Neural Networks

Artificial intelligence, while new, has proven itself to be extremely effective in predicting trends and finding patterns that humans otherwise would not. With the emergence of quantum processors in the 21st century, quantum computers are slowly finding their way into more and more parts of our lives. Notably, quantum neural networks (QNNs) are becoming increasingly popular as a result of their potentially high computational speeds and higher scalability. Additionally, QNNs vary from their classical counterparts (CNN) in several areas, such as the physics that govern how they work. The fundamental differences between the two types of neural networks in conjunction with the potential of QNNs make us wonder whether this new type of AI may be able to outperform CNNs. As cryptocurrencies have been shown to be incredibly volatile and difficult to predict, the task of predicting cryptocurrency performance is one that challenges both classical and quantum neural networks.


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