• BOHR∞’s CEO keynote speech at impact mobility '18 rEVolution

    Quantum Machine Learning Hackathon

    BOHR∞'s team wins 2 prizes at Quantum Machine Learning hackathon!

    quantum computing landscape

    find out how we fit in in the quantum industry

  • about

    BOHR∞ (Bohr Technology Inc.) is a company that works on quantum machine learning algorithms and software for solving complex optimization problems across various industries


    BOHR∞ was launched with the goal of mixing classical AI and state-of-the-art quantum algorithms to enable the use of Quantum Computers for solving complex optimisation problems in the mobility, transportation, energy, finance, insurance and manufacturing industry.


    It brings together a group of leading quantum programming, quantum physics and AI/Machine Learning specialists to work on industry altering quantum optimisation applications.

    the complexity of the future

    By 2020, current (super)computers will be overpowered by Quantum Computers. They will allow us to solve many currently unsolvable issues in the area of combinatorial optimisation where even smaller-scale problems are inherently complex..


    An effective solution to solve complex optimisation problems will be hard to achieve through classical computation. This is because classical (super)computers are currently reaching the limits of how much more powerful they can become.


    The answer lies in Quantum Computers – a new breed of computers relying on qubits instead of bits; atoms instead of transistors; and quantum mechanics instead of computer science.


    Quantum Computers come with the promise of offering exponential computing power and in the next 5 years they will start replacing classic computers for the purpose of solving optimisation problems.

    solving the unsolvable

    How complex can optimisation be? Let's look at some examples:


    Optimising route planning can be narrowed down to the Travelling Salesman Problem. The number of possible routes in the Travelling Salesman Problem is equal to [(n-1)!/2] where n is the number of cities. So if the travelling salesman has 12 cities to travel to, the number of possible combinations will be:


    (12-1)!/2 = (11 x 10 x 9 x 8 x 7 x 6 x 5 x 4 x 3 x 2 x 1)/2 = 19 958 400 routes.


    With 15 cities, the number of possible routes is already over 43 million.


    And if you wanted to optimise traffic lights & traffic flow in a city like Warsaw in Poland (which has approx. 2m inhabitants), this would have 120800 combinations.

    Quantum Computing power

    Quantum Computers process information with qubits instead of bits. This allows them to offer unprecedented computing power for solving optimisation problems:
    • information in n qubits = information in 2n bits
    • computing power doubles with every qubit
    • with just 60 qubits a Quantum Computer can deliver more power than any other current computer

    potential applications

    Quantum Computers offer a lot of potential for optimising numerous processes many industries, such as:

    • Transportation: route planning, scheduling, fleet management
    • Cities: traffic flow optimisation, city infrastructure optimisation
    • Automotive: improving car GPS', simulating autonomous car algorithms
    • Manufacturing: optimizing factory workflow
    • Energy: energy pricing optimization
    • Finance: portfolio optimization
    • Aeronautics: aircraft design procedures
All Posts