Quantum Machine Learning exploits the benefits of two hot topics: Quantum Computing and Machine Learning. Although qML is still under development, it can already be used in hybrid approaches to accelerate computing and increase precision.
Digital, electrical and autonomous: Automotive manufacturers not only have to react to these requirements with innovative concepts, but also with efficient and economic solutions. We show how they can benefit here from quantum technologies.
The automotive industry is currently undergoing a profound transformation. Manufacturers have to further develop, indeed practically reinvent cars in many respects. Ambitious climate goals make alternative drive technologies necessary. At the same time, changed customer expectations demand a higher degree of digitalization, coupled also with autonomous driving.This multi-layered transformation involves a great deal of effort and high costs.
That's why manufacturers not only have to come up with innovative ideas on how the car of tomorrow should work. They must also come up with efficient concepts for the development and production of their vehicles that are as cost-effective as possible.
Quantum computing can play a key role in this in the future. Quantum-inspired algorithms already make it possible to simulate complex situations with current standard hardware, thereby solving associated optimization problems. The underlying approach is simple: You do not need to try out what you can calculate. Time and resources can be saved by using this technology. Quantum technologies hold great potential for the automotive industry. So-called QUBO models are particularly relevant here. In the whitepaper, we use three concrete examples to show how automotive manufacturers can benefit from this.
QUBO is the abbreviation for Quadratic Unconstrained Binary Optimization. This involves an approach to solving combinational optimization problems, with which, by contrast with traditional algorithms, the entire model fits into a matrix. This means QUBO models can very quickly master a high degree of complexity and offer a solution for optimization problems – also with the assistance of conventional computers. Another advantage: the model does not have to be translated for use on a quantum computer.
Take advantage of MegaQUBO. Our experts from Machine Learning Reply and Data Reply can provide you with extensive expertise and will be available to advise you on the use of our software.
The Quantum inspired accelerator MegaQUBO was developed to solve quantum problems faster. It‘s available both on Premises and in Cloud.
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Machine Learning Reply offers customized end-to-end Data Science solutions, covering the entire project life cycle – from initial strategy consulting, data architecture and infrastructure topics, to processing data with quality assurance using Machine Learning algorithms. Machine Learning Reply has extensive expertise in the field of Data Science in all key industries of German HDAX companies.Machine Learning Reply empowers clients to successfully introduce new data-driven business models and to optimize existing processes and products – with a focus on distributed open source and cloud technologies. With the Machine Learning Incubator, the company offers a program to train the next generation of decision-makers, data scientists and engineers.