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Quantum Jump

Arvind Krishna     December 25, 2018

Many business leaders think quantum computing is a technology that is still years away from practical use. But not only does the technology exist, a practical quantum future is closer than we think.

The field, in fact, has more than 50 years of scientific advancements already behind it. Thousands of developers, scientists, and industry experts learn and conduct research using quantum computers.

Quantum computing is at a stage that artificial intelligence was at 20 years ago, but it has a major advantage on its side: we've seen how quickly this technology takes hold, giving an edge to early adopters. Like artificial intelligence (AI), quantum systems are on the cloud, available for anyone - from Fortune 500 companies, to academic institutions, to start-ups - to experiment with and work on new use cases. The path to adoption also involves addressing many of the same business issues as AI: How can I make quantum computing technology accessible to my organisation? How can it enhance my business? How can I ensure we are prepared to take advantage?

At their most basic, quantum computers process information very differently from classical computers. Instead of classical bits, binary zeros and ones that work one after another, the principles of quantum mechanics give quantum bits (or qubits) exponential compute power. Qubits can represent zeros and ones simultaneously, and they use this "superposition" capability to work together to solve problems. As they're able to exist in more than one state at a time, qubits supercharge the output that quantum computers can generate - enabling us to run experiments more efficiently. This can give a big boost to what can otherwise be long-drawn processes - quantum chemistry can drive drug discovery breakthroughs, and quantum algorithms could optimise global manufacturing supply chains.

Businesses are already using quantum computing to examine what were previously considered unsolvable problems. For instance, automotive manufacturers are designing new materials for batteries and electronics and financial institutions are trying to optimise risk analysis. While there is still much to be done to stabilise and develop quantum systems, each breakthrough gets us closer to applications with commercial, intellectual, and societal benefits.

But for that to happen, we need more people and organisations that understand - and have quantum computing skills in - hardware, physics, chemistry, and computer science to write algorithms and programmes that help us get to practical quantum applications over the next five years.

Get quantum ready

To get diverse disciplines, backgrounds, and industries quantum ready, IBM made its cloud-based IBM Q Experience systems free for all users. Since launching in 2016, more than 100,000 people have run almost seven million experiments on these quantum computers (India is among the top users), resulting in more than 100 published research papers.

Quantum computing must also be ubiquitous in the classroom. From computer science courses to chemistry and business classes, today's students need to understand the technology, and hopefully pursue career paths rooted in quantum computing.

Organisations, too, can get educated about the opportunities. Companies have commercial relationships with many universities around the world to integrate quantum education into classrooms and develop academic-industry partnerships. For example, our hub at Japan's Keio University has a mission to accelerate skills development, as well as collaborate on use cases with their members JSR (a chemical materials company), Mitsubishi UFJ Financial Group, Mizuho Financial Group, and Mitsubishi Chemical.

Now is the time to begin exploring what we can do with near-term quantum computers, how to make the most of these systems, and how to prepare for the more advanced systems to come. As with AI - a once emerging technology that is now widely adopted across businesses - there is work to be done to ensure early adopters reap the benefits of quantum computing.

The writer is Director of IBM Research


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