Quantum Computing and AI

Introduction

Quantum computing is the area of study focused on developing computer technology based on the principles of “quantum mechanics”, which explains the nature and behaviour of energy and matter on the quantum (atomic and sub-atomic) scale.

Wikipedia describes “quantum computing” as

“use of quantum-mechanical phenomena such as superposition and entanglement to perform computation”.

While a standard computer handles data in an exclusive binary state of 0s and 1s, quantum computers use quantum bits or “qubits”, which can take any value between 0 and 1. And if you “entangle” the qubits, you can solve problems that classical computers cannot. A future quantum computer could, for example, crack any of today’s common security systems – such as 128-bit AES encryption – in seconds. Even the best supercomputer today would take millions of years to do the same job.

Entanglement is a property of qubits that allow them to be dependent of each other that a change in the state of one qubit can result and immediate change in others. more than one state during computation. Superposition states that qubits can hold both 0 and 1 state at the same time.

According to Shohini Ghose, Professor of Quantum Physics and Computer Science, at Wilfrid Laurier University in Waterloo, Canada

“Quantum computers are not just a faster version of our current computers. They operate on the laws of quantum physics. It’s just like a light bulb compared to a candle.”

Quantum computing and Artificial Intelligence (AI) are both transformational technologies. Today, AI using classical computing enables “Artificial Narrow Intelligence” (or ANI). Quantum computing will significantly accelerate the journey towards “Artificial General Intelligence” (or AGI) imitating how the human brain functions and, perhaps, pave the way towards “Artificial Super Intelligence” (or ASI) which may surpass the human brain and mimic levels of self-awareness and self-consciousness.

Quantum Computing Timeline

It was the unorthodox theories of quantum mechanics, born out of the 20th Century, which were later to spawn quantum computing. The concept of using quantum entities to process data and solve complex problems, much like a classical computer, can be traced back to the 1980s – the era of the “God Fathers” of Quantum Computing.

1980 – Paul Benioff described the first quantum mechanical model of a computer, showing that quantum computers are theoretically possible. His idea of a quantum computer was based on Alan Turing’s famous paper tape computer described in his 1936 paper.

1981 – The next year, physicist Richard Feynman, proved it was impossible to simulate quantum systems on a classical computer. His argument hinged on Bell’s theorem, written in 1964. Feynman did propose how a quantum computer might be able to simulate any quantum system, including the physical world in a 1984 lecture. His concept borrowed from Benioff’s quantum Turing computer.

1985 – David Deutsch, a physicist, published a paper describing the world’s first universal quantum computer: a way to mathematically understand what is possible on a quantum computer. He showed how such a quantum machine could reproduce any realisable physical system. What’s more it could do this by finite means and much faster than a classical computer. He was the first to set down the mathematical concepts of a quantum Turing machine, one which could model a quantum system.

1994 – Peter Shor developed “Shor’s algorithm”, which would allow a quantum computer to factor large numbers much faster than the best classical algorithm.

The timeline below summarises what has happened since and imagines the future.

No alt text provided for this image

Key Players

Quantum technology is still at an early stage of development. The first commercial devices have started to emerge in recent years, capable of performing a few hundred operations with tens of qubits. This early hardware was already sufficient to demonstrate quantum supremacy by solving a specific problem intangible for classical supercomputers.

Google, IBM, and a handful of start-ups are competing to create the next generation of supercomputers. The emergence of quantum computing might help solve problems, such as modelling complex chemical processes that the existing computers cannot handle.

D-Wave Systems Inc., a Canadian company, became the first to sell quantum computers in 2011, although the usefulness of quantum computers is limited to certain kinds of math problems. IBM, Google, Intel, and Rigetti Computing, a start-up in Berkeley, California, have collaboratively created working quantum computers for businesses and researchers.

Intel has started shipping a superconducting quantum chip to researchers. It has also created a much smaller, but so far, a less powerful quantum computer that runs on a silicon chip, which is not all that different from those found in normal computers.

Microsoft initiated a well-funded program to build a quantum computer using an unusual design that might make it more practical for commercial applications. Airbus Group also established a team in 2015 to tackle quantum computing at its site in Newport, Wales. Airbus’ Defense and Space unit’s main objectives was to study all technologies related to quantum mechanics, ranging from cryptography to computation.

The infographic below highlights the role of collaboration to support advancement of Quantum Computing technology.

No alt text provided for this image

UK-based Innovation

Whilst the US and China may be dominating, the UK and Europe are not far behind.

France can justifiably claim to be one of Europe’s leading lights in quantum computing with national plans building upon a January 2020 report entitled: « Quantique : le virage technologique que la France ne ratera pas » aiming to make France a global leader.

The German government set aside two billion euros in a stimulus package, and just recently a panel of experts from research and industry presented a roadmap to quantum computing. 

In the UK, £1bn has been set aside which includes a 10-year investment by the UK’s National Quantum Technologies Programme, which was launched by the UK government in 2013. This has resulted in more than 30 quantum start-ups including a national network of quantum technology hubs in quantum sensors and metrology (Birmingham), quantum communications (York), quantum enhanced imaging (Glasgow), and quantum IT (Oxford).

Thanks entirely to a £93m investment from UK Research and Innovation (UKRI), the new National Quantum Computing Centre (NQCC) is being built at the Harwell lab of the Science and Technology Facilities Council in Oxfordshire. When it opens in late 2022, the NQCC will bring together academia, business and government with the aim of delivering 100+ qubit user platforms by 2025, thereby allowing UK firms to tap fully into this technology’s potential.

Another major achievement is the launch of the world’s first cloud-based Quantum Random Number Generation (QRNG) service built using an IBM quantum computer envisioned by Cambridge Quantum Computing (CQC) – impossible with classical computing.

It’s great to see such a co-ordinated and visionary programmes in the UK right now.

Quantum AI

Quantum technology has an immense power. It will allow us to do computing tasks that are outside of the reach of even the best computers today. Artificial intelligence, which is designed to analyse huge amounts of data, could benefit from this, as could materials and pharmaceutical research.

The term “quantum AI” means the use of quantum computing for computation of machine learning algorithms, which takes advantage of computational superiority of quantum computing, to achieve results that are not possible to achieve with classical computers, the following are some of the applications of this super mix of quantum computing and AI.

This allows industrial and academic researchers to perform simulations for solving ever-more complex design and optimisation problems, and ultimately leads to the development of better products and services. Still, many economically, technologically, and scientifically relevant problems (e.g. computational chemistry, drug design, biological processes, route optimisation) remain out of reach for modern and even future supercomputers, assuming the computing power will continue to grow at the present rate. As a result, countless approximate methods have been developed over the years, characterised by various trade-offs between accuracy and computational cost.

Benefits of Quantum Computing

The following are some of the advantages of Quantum Computing that make it so desirable for our world.

  • Quantum Computers will deliver enormous speed for specific problems. Researchers are working to build algorithms to find out and solve the problems suitable for quantum speed-ups.
  • The speed of quantum computers will improve many of our technologies that need immense computation power like Machine Learning, 5G (and even faster internet speeds), bullet trains (and many other transport methods), and many more.
  • Quantum computing is important in the current age of Big Data. As we need efficient computers to process the huge amount of data we are producing daily.

Applications of Quantum Computing

The following are some of the fields of quantum online application benefits that can be applied to make them more efficient than ever.

Artificial Intelligence

Artificial Intelligence (AI) is a key and one of the best technologies of quantum computing. The base of AI is on the concept of learning from experience. it is becoming more accurate depending on the feedback until the computer program begins to show “intelligence.” This feedback is base on estimating the probabilities for many possible choices. Thus, AI is an ideal candidate for quantum computing. It aims to change many industries. From cars to medicine, and in the future, AI will be what electricity was in the twentieth and twenty-first centuries.

Machine Learning Algorithms

Machine Learning (ML) and AI technologies are the two key areas of research in the application of quantum computing algorithms, giving rise to a new discipline that’s been dubbed Quantum Machine Learning (QML).

Currently, most industrial applications of artificial intelligence come from the so-called “supervised learning”, used in tasks such as image recognition or consumption forecasting.  With quantum computing, we are likely to start seeing acceleration – which, in some cases, could be exponential.

Hardware and Software Error Simulation

Large software programs with millions of lines of code or hardware systems with billions of transistors can be difficult and expensive to verify for correctness. Billions or trillions of different states can exist and it is impracticable and impossible for a classical computer to check and simulate every single one. Not only do we need to understand what is happening when the system operates in a normal manner but we also want to know what happens if an error occurs. Can our device identify it and has a coping mechanism to reduce any potential problems? Through the use of quantum computing to assist with these simulations, one can hope to provide much better coverage of their simulations with an improved time.

Cryptography

Most online security systems nowadays depend on the complexity of factoring large numbers into primes. While this is possible by using digital computers to scan through every possible factor. The enormous amount of time needed makes it expensive and impractical to “crack the code.” Quantum computers can compute these factors are more efficient than digital computers. This means such methods of security will soon become obsolete. There are also innovative methods of quantum encryption that are base on the one-way nature of quantum interdependence. Networks across cities have already been deployed in various countries.

Data Analytics

Quantum computing has the ability to solve problems on impressive scales by engaging with complex material that might otherwise ignore. A particular field of study called “topological analysis” helps to identify how certain geometric shapes behave in specific ways. In doing so, it describes computations that are more or less impossible to conjure onto conventional computers.

With the introduction of a topological quantum computer, one can do simple calculations. Hence, making the process that much easier.

Nanotechnology

Through the introduction of quantum dots, researchers hope to further improve their standards of nanotechnology. The ultimate goal is to improve health conditions in developing nations, while also introducing purification processes for various industries.

While this is a field of research that scientists are into already, there still exists a wide gap that needs to look upon to quite by the introduction of quantum algorithms that can ease the research process and also speed up results.

Digital Security

In today’s digital world where almost every individual has massive amounts of personal data uploaded onto the cloud, there exists a growing need to improve security standards in an attempt to help make the data more secure.

According to Shohini Ghose,

Quantum offers a way to encrypt information that can never be hacked, no matter how good the hackers are.

Quantum Key Distribution (or QKD), which implements a cryptographic protocol involving components of quantum mechanics, is being put forward as a secure mechanism to tackle the issue of security by helping users encrypt data while also enabling them to share that with a limited number of resources. So not only can messages/data is secure but also distributed among personnel thus helping with secure distribution.

Future Applications of Quantum Computing

Quantum computing is a promising technology which will change our lives in many ways. As research gets more attention from government, industry, and academia, more uses are expected to be found.

No alt text provided for this image

Source: Futurebridge

Concluding Thoughts

Quantum computing is no longer just for physicists and computer scientists, but also for information system researchers.

According to a report published by Inside Quantum Technology (IQT), the quantum computing market will reach $2.2 Billion, and the number of installed quantum computers will reach around 180 in 2026, with about 45 machines produced in that year. These include both machines installed at the quantum computer companies themselves that are accessed by quantum services as well as customer premises machines. The report is available here.  

Cloud access revenues will likely dominate as a revenue source for quantum computing companies in the format of Quantum Computing as a Service (QCaaS) offering, that will be accounting for 75 percent of all quantum computing revenues in 2026. Although in the long run quantum computers may be more widely purchased, today potential end users are more inclined to do quantum computing over the cloud rather than make technologically risky and expensive investments in quantum computing equipment. 

Today, amongst the financial institutions using quantum computing, none have quantum computing as part of day-to-day operations. Some appear very close and are hiring staff at a level that makes one think they are on the verge. IQT Research expects that by 2026, revenues from cloud access to reach circa $410 million, making financial institutions the largest single end-user segment of the quantum access cloud market.

In a parallel track quantum software applications, developers’ tools and number of quantum engineers and experts will grow as the infrastructure developed over the next 5 years which will make it possible for more organisations to harvest the power of two transformational technologies quantum computing and AI and encourage many universities to add quantum computing as an essential part of their curriculum.

Artificial Intelligence (AI) and Machine Learning (ML) are today’s latest buzzwords, and when you mix that with ‘quantum’, these terms become a “mega-buzzword”. This lends itself to dystopian fears such as those previously raised by the late Stephen Hawking.

“The development of full artificial intelligence could spell the end of the human race. Once humans develop artificial intelligence, it will take off on its own and redesign itself at an ever-increasing rate. Humans, who are limited by slow biological evolution, couldn’t compete and would be superseded.” — Stephen Hawking (2014)

There’s little doubt that quantum computing could help develop revolutionary AI systems. However, there’s is much more that needs to be done before it becomes mainstream.

Switching to a more positive note, I’d like to quote Brian Solis, Global Innovation Evangelist at Salesforce and a world renowned keynote speaker. 

“Now is the time to start building the vision, the expertise, dedicating teams and resources” for quantum computing. The stepping stones to get there are building a Center of Excellence (CoE) around AI”.

This will help make AI the focal point of an organisation’s efforts to become more agile and innovative.

Additionally, Solis adds “it forces you to get better data, clean the data, and build expertise and key capabilities around the data. Complement that with a smaller set of resources and a Center of Excellence for quantum computing”.

Inspired by Solis, I will end with this empowering quote from F. Scott Fitzgerald.

No alt text provided for this image

Further Reading

Be sure to checkout this video “Quantum Computing Expert Explains One Concept in 5 Levels of Difficulty” hosted by IBM’s Dr. Talia Gershon who explains quantum computing to 5 different people; a child, teen, a college student, a grad student and a professional.

About the Author #aboutme

Over the past 25 years, Salim has built a career in consulting, working both client and supplier side as an interim CIO/CTO and a Business Change / Transformation Consultant.

Salim has engaged in, and led, digital and technology transformations and programmes involving rescue & recovery (“turnaround”), process optimisation & improvement and organisational change — globally across the UK, Central Europe, Nordics, Turkey, UAE, US, Asia and Australia.

Salim is an Oxford University alumni and an author in the field of Artificial Intelligence. Key interests include the role of AI for the betterment of people and society.