IBM has always been a leader in technology and recently with the introduction of its 433 qubit quantum computer Osprey has achieved a big milestone in the race. It packs three times more qubit than the previous version named Eagle. Their current roadmap involves achieving a 4000 qubit quantum system by 2025. Before reaching this milestone they have 2 more quantum systems in the pipeline 1212 qubit Condor and 1386 qubit flamingo in 2023 and 2024 respectively.
Understanding the processing power of QC
There are a lot of open problems in the management which require a lot of computation power. These problems range from forecasting to finding the optimal solution to the last-mile problem. Quantum computing exponentially raises the speed of computing. If we consider the current quantum computer its processing speed is way faster than the current supercomputer. Leaving aside the theoretical power of Quantum technologies, even the current practical problems can be solved using the processing power of quantum computers. Due to the presence of the probabilistic nature of an electron, we can generate a string of random bits which can be used for solving the pressing problem of security. Many cryptographic algorithms are vulnerable to various statistical attacks that quantum technology can provide. This provides a lot of applications in the field of management.
Let us first understand the concept of qubit
Imagine tossing a coin and assigning heads as 0 and tails as 1. An attacker can rig the coin to his advantage. Similar other ways to generate the classical bits can also be manipulated or interrupted. Now imagine an election passing through a sheet, there are two possible outcomes: either it will reflect or pass through the sheet. We can assign the respective phenomenon as 0 and 1. The bigger question is can we manipulate the process at any stage? The answer is a big No, even if we capture the electron midway it will collapse. This phenomenon makes sure that there is a 50% chance that we get either 0 or 1. The core of security lies in the probabilistic nature of qubit states which does not exist in classical cases.
Quantum Computers can handle complex data for decision-making models compared to their classical counterparts. The ability to work with different types of data types helps in optimizing Inventory management and logistics in the supply chain. Problems such as Newsvendor problem/Last mile delivery is difficult with conventional computers. Because of the entanglement property of electrons, we can exponentially increase the speed of computation. Because of something called the No Cloning Theorem, a qubit cannot be copied and data cannot be retrieved unlike in classical settings. Integrating it with IoT can simulate the process and can be used for the maintenance of the machine. If you can find a highly efficient route in record time, quantum computers can perform multiple models simultaneously with processing speed a million times faster than the classical computers which makes it suitable for optimizing a classical scenario.
Currently, It is not very feasible to implement QC in the supply chain industry due to high prices and impracticality. The error rate in QC is also high compared to classical computers due to the perturbation of electrons. Researchers all around the world are trying hard to restrict these errors. With Applications of QC, we can achieve great success with respect to the supply chain industry. Alongside AI & IoT, QC is one of the many digital tools that manufacturers can use to optimize and streamline their processes.
This is becoming increasingly important as the trend of personalization of consumer goods continues and orders become more complex. With a processing speed up to 100 million times faster than traditional computers, quantum computers can perform multiple models simultaneously, making this technology particularly suitable for optimizing the classic scenario if you find a highly efficient route in record time.
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