Supervised machine learning, also called predictive analytics, uses algorithms to train a model to find patterns in a dataset with labels and features. It then uses the trained model to predict the labels on a new dataset’s features. Recommendation engines use machine learning algorithms to sift through large quantities of data to predict how likely a customer is to purchase an item or enjoy a piece of content, and then make customized suggestions to the user. The result is a more personalized, relevant experience that encourages better engagement and reduces churn. Today, machine learning enables data scientists to use clustering… Read More

Through entanglement, qubits can form connections with other qubits, which greatly enhances their computational power. However, when a quantum state is measured, its wave function collapses, revealing either a zero or a one. We have been familiar with it for quite some time through simulations of quantum computers using conventional CPUs. However, these simulations can only be performed for a small number of qubits. In practice, if you were to attempt using the IBM API for this purpose, you would consistently encounter ‘unclean readings.’ Resolving this issue is one of the many aspects that scientists are currently working on. Through… Read More

Obtaining gates for all pairs of qubits is especially challenging in this case, as well as being able to separately control each qubit. DiVincenzo has summarized the required properties of a physical system in order to build a quantum computer in five criteria (DiVincenzo, 2000). For convenience, they are given in Section 6 together with the specific schemes developed for rare earth-doped crystals. In this regard, Feynman extended the quantum-mechanical phenomena to the world of conventional computing. “Herbert’s erroneous paper was a spark that generated immense progress,” the physicist Asher Peres recalled, in 2003. Shor wears oval glasses, his belly… Read More