Less than six minutes was enough to solve the problem with 3,854 variables. What happened exactly?
All because of the competition Car Sensor Mode Challenge From the organization of BMW, which is looking for a way to perfectly arrange the car’s sensors. Thanks to Entropy Quantum Computing, it was possible to achieve 70 times higher efficiency than last year, when D-Wave hybrid quantum implementation was used.
Read also: Will the butterfly effect improve quantum computers?
We believe this proves that innovative quantum computing technologies can solve today’s real business problems. What is more important is the complexity of the problem being solved. This was not just a fundamental problem to show that quantitative solutions would someday be feasible; It was a very real and important problem, the solution of which could help accelerate the development of the autonomous car industry.Commenting on Bob Lisowski, President of Quantum Computing Inc.
There is no need to tell anyone how difficult it is to arrange sensors in vehicles correctly. This is especially true for self-driving cars, where a lot of variables must be considered, including body design, wind resistance and proper vehicle balance.
Quantum computing has made it possible to arrange car sensors almost perfectly
Let’s imagine that a problem with 3,854 variables and 500 related constraints was solved in less than six minutes using quantum computing. It took a very short time to provide the best possible solution to the sensor placement issue. It turns out that 15 of them provide 96 percent vehicle coverage.
Despite these impressive results, the commercial and overall feasibility of a QCI solution for quantum computing is not yet known. The approach used by this company is quite unusual and different from the one used by industry giants, for example in the form of Microsoft.
Read also: 150,000 qubits in a single chip. Will revolutionize quantum computers
In this case, it seems that the key to success lies in including the environment itself in the calculation results. Time and costs are saved because you don’t have to control all the variables except for the quantum processor itself. The system, in turn, adapts to the changing environment by analyzing the reactions and changes in the quantum states of the qubit.