Quantum computing has enormous potential, but it faces a scalability problem. For such a machine to be useful in real terms, multiple quantum processors need to be assembled in a single location.

That is down to two main reasons – the first being that the qubits, or quantum bits, that make up today’s machines still struggle with noise, or errors, that we are only just learning to correct.

In November 2022, it started offering quantum computing over AWS via its 256-qubit computer (its first-generation machine). Boger said the service is mostly used for pilots and proof-of-concept ...

A Canadian startup called Xanadu has built a photon-based quantum computer it says should ... from drug discovery to more energy-efficient machine learning. Aurora is a “photonic” quantum ...

Without getting deep into the complex operations of quantum computing, the act of entangling qubits on two or more machines in different locations indicates that it is possible to build a quantum ...

Alphabet is limiting access to its quantum machines, but its latest technological breakthroughs and strong financial resources position it well for future growth in the sector. One of these ...

Key Partnerships & AI Integration – Collaborations with Amazon, Microsoft, Nvidia, and Quantum Machines support scaling and automation, improving calibration to 99.9% single-qubit fidelity.

Quantum computing may be the next sector to see share prices surge. Pure-play quantum computing company IonQ (NYSE: IONQ) is an example. Its shares skyrocketed 270% over the past 12 months through ...

Other companies using a similar technology to build machines — called neutral-atom quantum computers — are also making gains on industry leaders such as IBM. ‘A truly remarkable breakthrough ...

The third areas where quantum computing might be applied in financial services is machine learning. Finance companies typically have a huge amount of data to train artificial intelligence (AI ...

and quantum-centric supercomputers with thousands of qubits that may be capable of solving security, chemistry, machine learning, and optimization problems sometime after 2033. We're likely still ...