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Quantum Computers, AI, Big Data and Decision Support Systems

Posted on February 24, 2024July 3, 2025 by Edgar Khachatryan

Today’s computers are designed to perform accurate calculations and deliver precise results for relatively small problems. They excel at their tasks, but what if we introduced quantum computers into the equation? Unlike traditional computers, quantum computers are not always precise. They may produce results that deviate from the exact truth. So, why do we need quantum computers?

The answer is simple: not all problems require exact results or calculations. In many cases, estimations are sufficient.

In today’s world, numerous problems inherently lack precise solutions due to their complex nature. This includes weather predictions, traffic forecasting, air pollution modeling, financial modeling, machine learning, drug design, and many others. However, the more data we have, the better the results we can achieve. This is where quantum computers come into play.

Quantum computers are excellent tools for working with big data during the research stages of most projects. They are capable of testing different models and estimating potential results. They can be instrumental in predicting forest fires, tracking migrations of birds and animals, understanding the behavior of viruses and microbes, and aiding in the development of new materials, minerals, engine types, and energy sources.

The perfect combination of today’s advanced technologies involves quantum computers assisting in data collection and sorting. Specialized Artificial Intelligence (AI) software then analyzes this Big Data, returning results with various possible outcomes. Decision Support Systems (DSS), developed by industry scientists, provide suggestions to those seeking to improve their projects. These suggestions can also serve as improved input for Machine Learning programs or AI software.

In conclusion, the integration of quantum computers, AI, Big Data, and Decision Support Systems promises a future of technological advancement and improved problem-solving capabilities. Even it is hard to compare Quantum Computers, because of different types of engines they have, but here are some examples.

According to Google, in 2019, Google researchers used a quantum processor called Sycamore, containing 53 functioning qubits (today Google is testing 70 Qubit Quantum Computers), to solve a random sampling problem that would have taken the world’s best supercomputers 10,000 years to work out. It took Sycamore just three minutes and 20 seconds (https://www.wired.co.uk/article/google-quantum-computers-supremacy)

IBM released Condor, which, with 1,121 qubits, is the world’s largest quantum chip according to FastCompany (https://www.fastcompany.com/90992708/ibm-quantum-system-two), and according to new Scientist the quantum computer with the most qubits is developed by Atom Computing, a California-based start-up. Their quantum computer has 1180 qubits. This quantum computer uses neutral atoms trapped by lasers in a 2-dimensional grid (https://www.newscientist.com/article/2399246-record-breaking-quantum-computer-has-more-than-1000-qubits/). Also, D-Wave announces 1,200+ Qubit Advantage2™ Prototype in lower-noise fabrication stack.

“Author’s Note: The ideas and concepts presented in this blog post are my own. As the author, I have developed and articulated these insights based on my understanding and perspective. However, in the process of writing this post, I have utilized the assistance of Microsoft Copilot, an AI tool, to help with language refinement, fact-checking, and content enhancement. While Copilot has been instrumental in the writing process, the ownership and responsibility of the ideas and content rest solely with me.”

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