Quantum computing is next goal for business - Dave Caskie

In June 2021, Tesla unveiled Dojo, a supercomputer designed in-house and built to make self-driving cars mainstream. Dojo assimilates the massive amounts of driving and video data collected from existing Tesla cars to train the next generation of self-driving models.

David Caskie, Community and Corporate Citizenship Sponsor, Accenture in Scotland
David Caskie, Community and Corporate Citizenship Sponsor, Accenture in Scotland

Every industry and every business has its own grand challenges. For the financial services industry that holy grail is the accurate prediction of markets; for logistics companies the optimisation of the transport of goods could ensure that near-instantaneous delivery times are met, while reducing environmental impacts dramatically. For pharma companies the pre-emptive detection of diseases would be transformational.

And just as at Tesla, we are witnessing the emergence of a new class of machines which are stretching the boundaries of what computers can solve and which will make these core challenges achievable.

The reality is that more and more data is being created and collected every day and businesses want to leverage the insights that come from it – thus driving demands for greater computing capabilities.

HAMBURG, GERMANY - JUNE 07: An employee of the German Climate Computing Center (DKRZ, or Deutsches Klimarechenzentrum) poses next to the "Mistral" supercomputer, installed in 2016, at the German Climate Computing Center on June 7, 2017 in Hamburg, Germany. The DKRZ provides HPC (high performance computing) and associated services for climate research institutes in Germany. Its high performance computer and storage systems have been specifically selected with respect to climate and Earth system modeling. With a total of 100,000 processor cores, Mistral has a peak performance of 3.6 PetaFLOPS. With a capacity of 54 PBytes, its parallel file system is currently one of the largest in the world. The DKRZ's robot-operated tape archive has currently a capacity of 200 petabytes and allows for long-term archiving of climate simulations such as those carried out with respect to reports by the Intergovernmental Panel on Climate Change. (Photo by Morris MacMatzen/Getty Images)

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While quantum computing is the pinnacle of next generation problem solving, the current generation of high performance computers (HPC), with massive parallel processing capabilities like Dojo, can help businesses take advantage of the swathes of data that may be too expensive or inefficient for traditional computing to process.

Biology-inspired computing is another class of capabilities that draws inspiration from or relies directly on natural biological processes to store data, solve problems, or model complex systems in fundamentally different ways. Neuromorphic chips have introduced a brand-new design to computer architecture that’s modelled after the human brain. These chips use artificial neurons to transmit information and offer an alternative to powering today’s AI systems.

Applied in the field of robotics, these machines can execute a set of instructions, but also adapt, react and learn about their environment, all while allowing for more natural interaction in a more power efficient way. All of this has a transformational impact on the practical performance of real-world tools like drones.

But this is just the beginning. While they are immensely powerful, HPC machines are still ‘just’ classical computers, and bio-inspired computing is ‘just’ a new approach to similar problems. The single biggest watershed moment for computing will be when quantum computers solve the problems that were considered quite literally intractable – making the impossible possible.

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In our latest Technology Vision 2022 report, we found that 69% of global executives believe that quantum computing will have a breakthrough or transformational impact on their organisations in the future.

Many companies are racing to claim they have reached ‘quantum supremacy’ first, but quantum research undoubtedly still has a long way to go. Nonetheless, the potential to predict outcomes from highly uncertain variables has a wide range of applications including sales forecasting, robotics, drug discovery and of course financial markets, with some expecting huge advances to be made in the next two to four years. When these quantum computers do emerge, adoption is likely to scale up rapidly.

In this scenario, businesses must begin to evaluate how these technologies will shape their own enterprise. What problems are simply considered the cost of doing business? How would it reshape the business if you could start solving them? Can you forge a way ahead with partners or within a consortium? Organisations need to start to identify their knowledge gaps. And in a world where we are already experiencing a technology skills shortage, they need to plan to develop the necessary talent to implement bold new plans.

For decades, computers that could efficiently solve the world’s ‘grand challenges’ have been nothing more than theoretical concepts. But enterprises can’t afford to think about them in the abstract any longer. They are here and rapidly improving. Their impact on industries’ most fundamental problems can either be an industry-ending event or the biggest opportunity in generations. Enterprises that start to anticipate a future with these machines will have the best shot at the latter.

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David Caskie, Community and Corporate Citizenship Sponsor, Accenture in Scotland

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