L E A D IN G E D GE
uantum computing could turn the technology world on its head. By harnessing properties beyond the grasp of traditional Newtonian physics, the potential is to transform the way that computers look at data and the
speed at which they can process and analyse it. The computers we are familiar with store
information in zero and one bits. A quantum computer uses zero and one bits as well as the subatomic particles both in between and simultaneously to perform operations quicker and with greater energy efficiency. At least, that’s the theory. Christophe Jurczak, chief executive of
Quantonation, a French early-stage venture fund says quantum technologies generally do things better—quicker computations, improved security and greater sensitivity. “Of course there are caveats, but that’s why these
technologies are so interesting,” Jurczak says. “This is now a time of exploration of use cases and of proofs of concept.”
MARKET PLAYERS Canadian firm D-Wave was the first to sell hardware with quantum effects and launched D-Wave Leap in late 2018 —a software tool that provides real-time access to their D-Wave 2000Q quantum computer. Microsoft has a Quantum Development Kit as part of its existing Microsoft Azure services, hailed as a full quantum stack of system, software and cloud. So far the technology is too new to be used by
family businesses in a commercial context, and investment is in its infancy (see page 77). South Korea’s Samsung and Japan’s Nagase Group are the closest family-controlled businesses to this cutting edge technology. Samsung is one of the founding partners of IBM’s Q Network alongside Daimler and Accenture, while Nagase is a member. The IBM Q Network is an industry-first initiative
to build universal quantum computers for business and science. The company has a cross-disciplinary team developing scalable quantum systems, and potential applications for the technology. Dr Stefan Woerner, global leader for quantum
finance and optimisation and a research staff member in the quantum technologies at IBM, says his team launched the first iteration in 2016 with 16 qubits, available on open source and basically for people to play with.
PHOTOGRAPHY: GETTY IMAGES, SHUTTERSTOCK, IBM
“The commercial version, meanwhile, has 20
qubits and greater computational capacity based on the total volume available,” Woerner says. “There are also several open source software
tools, including Qiskit Aqua, which offers quantum algorithms upon which applications for experimenting and building chemistry, artificial intelligence (AI) optimisation and finance applications using a real quantum computer. This is particularly important for engaging with clients to work out what can and cannot be done and where the best case uses are within their enterprise.”
DEVELOPMENT STAGES But just because quantum can, in theory, do something does not mean it should automatically be used and progress is at an early stage. Zao Wu, analyst at financial technology
Below: Dr Stefan Woerner at IBM is developing and analysing quantum algorithms for optimisation and machine learning, as well as their practical
applications, particularly in finance or supply chain management.
consultancy Celent, says quantum computing is no doubt capable of great things, but in its current iteration is still apt to get things wrong. “In technologynical terms this is known as
disintegration—basically that its computing power is still limited, so that limits things in terms of reliability and stability.” Nevertheless the potential for quantum
computingto make a real difference within a range of industries, including financial services, is tangible. Potential uses are building better models of financial markets to improve fraud and risk analytics, strengthening cryptography by inventingnew numbers, and improving operational efficiencies in messy and complicated areas, such as clearing and reconciliation of trades. Machine learning is
particularly set to benefit as quantum computers are able to analyse data to provide feedback much more efficiently than traditional computers. This significantly shortens the learning curve. “Something we are
working on is quantum algorithms that speed up the process because they need less data to come up with a risk
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