Quantum computing may still be at an early stage, but BMW has been quietly ramping up plans for the moment when it reaches maturity.
Most recently, the company just launched a “quantum computing challenge” – a call for talent designed to encourage external organizations to come up with solutions that will help the car manufacturer make the best use of quantum technologies.
“It’s a search for hidden gems,” Oliver Wick, technology scout at BMW Research and Technology, tells ZDNet.
“It’s a clear message to the world that BMW is working on quantum, and if you have innovative algorithms or great hardware, then please come to us and we can check if we could use it for BMW.”
The challenge, which is run in partnership with Amazon’s quantum computing division AWS Braket, is targeting corporations as well as startups and academics with a simple pitch: come up with quantum solutions to the problems that BMW has identified.
Specifically, explains Wick, BMW wants to see four challenges addressed. In the pre-production stage, quantum algorithms could help optimize the configuration of features for the limited number of cars that can be assembled for various tests, so that as many tests as possible can be carried out with a minimal amount of resources.
Similarly, optimization algorithms could improve sensor placement on vehicles, to make sure that the final configurations of sensors can reliably detect obstacles in different driving scenarios – something that is becoming increasingly important as autonomous driving becomes more common.
Candidates have also been invited to submit ideas for the simulation of material deformation during production, to predict costly problems in advance, as well as for the use of quantum machine learning to classify imperfections, cracks and scratches during automated quality inspection.
Participants are required to submit a concept proposal for any of the four challenges, after which a panel of experts will shortlist the most promising ideas. The successful candidates will then have a few months to build out their solutions on Amazon Braket, before pitching them next December. Winning ideas will earn a contract with BMW to implement their projects in real-life pilots.
“We are using the power of the crowd to solve our own problems inside BMW,” says Wick.
The quantum challenge is only the latest development in a strategy that aims to aggressively push the company’s quantum readiness.
BMW’s high-performance computers are currently handling 2,000 tasks a day, ranging from high-end visualizations to crash simulations; but even today’s most sophisticated systems are fast reaching their computing limits.
Quantum computers, however, could one day carry out computations exponentially faster, meaning that they could resolve problems that classical computers find intractable. For example, the amount of compute power required to optimize vehicle sensor placement is proving to be increasingly challenging for classical algorithms to take on; quantum algorithms, on the other hand, could come up with solutions in minutes. At BMW’s production scale, this could mean huge business value.
Wick explains that the potential of quantum computers was identified by the company as early as 2017. A tech report promptly followed to acquire some knowledge about the technology and its key providers, before work started on proofs of concept.
At this stage, says Wick, the biggest challenge was to find out the business case for quantum computing. “We initiated proofs of concept in optimization or scheduling, but those were activities in which no business case was included,” says Wick. “Initially, everybody came to me asking why we even needed quantum computing.”
But now proof of concepts are slowly starting to emerge as business projects. One of the company’s first research proposals, for instance, looked at the use of quantum computers to calculate the optimum circuit to be followed by a robot sealing welding seams on a vehicle. More recently, BMW unveiled that it has been making progress in designing quantum algorithms for supply-chain management, which have been successfully tested on Honeywell’s 10-qubit system.
BMW says it has now identified over 50 challenges at various stages of the value chain where quantum computing could provide significant benefits – four of which have now been delegated to the crowd thanks to the quantum challenge.
In other words, from a blue-sky type of endeavor, quantum computing is now solidly implanted in BMW’s strategy. “We’ve now built two teams, one in the development department and one in the IT department,” says Wick. “From this perspective, we have integrated quantum computer in our strategy.”
Partnerships are central to this approach. Last June, BMW co-founded the Quantum Technology and Application Consortium (QUTAC), together with firms ranging from Bosch to Volkswagen. The objective, says Wick, is to come up with a set of problems shared across different industries, to join forces in finding solutions that can then be applied to each specific use case.
BMW is also providing a €5.1 million ($6 million) to the University of Munich to support a professorship, who will be expected to conduct research into applying quantum technologies to industry problems such as those faced by BMW.
But just because quantum computing has become part of BMW’s business strategy doesn’t mean that the technology is already generating value. Quantum computers are still small-scale experimental devices that are utterly incapable of running programs large enough to be useful. They are known as Noisy, Intermediate-Scale Quantum Computers (NISQ), a term of reflective of how emergent the technology remains.
“We are in the NISQ era and we will need better quantum computers,” says Wick. “Personally, I think we could start having business benefits in five years. But that doesn’t mean we should wait for five years, lay back, and let other companies do the work instead.”
Preparing for large-scale quantum computers means developing partnerships with the best talent, filing patents to secure IP, but also understanding company processes very well to know how to reform them.
“You need imagination to re-think your own processes,” says Wick. “I can imagine that in the next 20 years, BMW customers will sit in front of a screen and configure their own BMW in real time, for example. This is what quantum computing is for – to re-think processes and setups.”
The biggest challenge for now, according to Wick, is to fully understand the ever-expanding quantum ecosystem, to make sure that the right quantum algorithms are fitted with the right quantum hardware to solve the right company problem.
This is easier said than done in a field that is buzzing with activity, and where noise and reality can be hard to distinguish. Quantum computing is rapidly joining blockchain, AR, VR and others on the list of popular buzzwords, and Wick can only count on his experience as a technology scout to make sure that the company doesn’t fall to the quantum hype.
In the automotive industry, BMW’s competitors are getting ready for quantum computing to change business processes, too. Volkswagen, for one, was early in joining the bandwagon, and has been expanding its capabilities ever since. The pressure is on to not fall behind in the race for quantum technologies, or so it would seem – and BMW is making it clear that it wants to be in the lead.