still work closely with universities
and national laboratories. There is
no consensus as to what is the best
technology or design. D-Wave led the
first generation but its computers
are technically limited and scientifically controversial. Although D-Wave
should survive as a niche player, IBM
and Google seem more likely to dominate the next generation, with Microsoft and maybe a startup or two close
on their heels. 12
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Michael A. Cusumano ( firstname.lastname@example.org) is a
professor at the MIT Sloan School of Management and
founding director of the Tokyo Entrepreneurship and
Innovation Center at Tokyo University of Science.
The author thanks Ganesh Vaidyanathan for his comments.
Copyright held by author.
used a D-Wave computer to do complex simulations of protein molecule
unfolding (useful in drug discovery).22 Since 2013, NASA and Google,
along with several universities, have
been using D-Wave computers in
their joint Quantum AI Lab. 7 The Lab
has explored Web search, speech recognition, planning and scheduling,
and operations management. 9 Since
2014, Northrup-Grumman has been
using D-Wave to simulate large-scale
software systems behavior (useful for
error detection). 4 Volkswagen, BMW,
and Google are relying on D-Wave to
analyze the huge amounts of data
needed for self-driving cars. In 2017,
Volkswagen used a $15-million D-Wave
computer accessed via the cloud to optimize the airport routes of 10,000 taxis in Beijing. The machine processed
GPS data in seconds that would normally take a computer 45 minutes. The
programming took six months, however, and some experts doubt the results, which have not been published
in a scientific journal. 6, 11
Perhaps the “killer app” will be
quantum encryption and secure communications. These applications utilize an algorithm discovered in 1994 by
Peter Shor, formerly of Bell Labs and
now at MIT. Shor demonstrated how to
use a quantum computer to factor very
large numbers. Entanglement also
makes it possible to have unbreakable
cryptographic keys across different locations. Governments (the U.S. and
China in particular) as well as companies (AT&T, Alibaba, BT, Fujitsu, HP,
Huawei, Mitsubishi, NEC, Raytheon,
and Toshiba, among others) have been
pursuing these applications.c China
seems especially advanced. 18
Do quantum computers represent a
new general-purpose computing “plat-
form?” No. Quantum computers are
special-purpose devices that exploit
quantum phenomena for massively
parallel computations. They are not
suited to everyday computing tasks
that require speed, precision, and
ease of use at low cost. The compet-
ing technologies also seem useful for
different applications, and so multi-
ple types of quantum computers may
persist, splitting potential applica-
tion ecosystems. D-Wave computers
tackle optimization and simulation
problems. They cannot run Shor’s
algorithm, and so may not be not
useful for cryptography or quantum
communications. IBM, Google, and
Microsoft, as well as several startups,
are designing more general-purpose
devices, but these are still theoreti-
cal, experimental, or small scale.
For the business to progress faster,
more people need access to bigger
quantum computers so they can build
better programming tools and test real-world applications. Toward this
end, IBM has made small quantum
computers available via the cloud and
is heading toward bigger devices; users have already run approximately
300,000 experiments. 12, 15 Google has
made its D-Wave computer available to
researchers as a cloud service. 8 Google is
also designing bigger machines with a
different technology. Microsoft announced in 2017 that it would offer up to
40 qubits via a simulator on the Azure
cloud. Microsoft has also created a
quantum programming language called
Q# and integrated this with Visual
Studio. 3,d However, Microsoft has not yet
built physical devices and the programming language may be completely specific to its architecture. 5
In short, quantum computing still
resembles conventional computing
circa the late 1940s and early 1950s.
We have laboratory devices and some
commercial products and services,
but mostly from one company. We
have incompatible architectures still
in the research stage, with different
strengths and weaknesses. All the
machines require specialized skills
to build and program. Companies
the “killer app”
will be quantum