Despite the fact that Quantum Computing has not yet hit the mainstream, it is still an extremely important technology that can benefit many different industries. In fact, if you want to take advantage of it, here are five of the most important applications of Quantum Computing that you can use right away.
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Artificial Intelligence & Machine Learning
Using quantum computing for artificial intelligence & machine learning is a logical way to leverage the power of quantum computing. Quantum computers are better equipped to tackle exponentially complex problems than conventional computers. This makes them well-suited to modeling natural systems. However, it is important to understand that quantum computing does not solve all of the problems that classical computers can.
Artificial Intelligence and Machine Learning are among the most promising applications of quantum computing. Quantum computers are capable of performing complex numerical simulations of natural processes. This is important because they can reduce the time it takes to develop new drugs. The resulting simulations are accurate, meaning that they can be used to identify potential treatments. These models also account for patient characteristics. This means that clinicians may be able to select the best therapy for individual patients.
Drug Design & Development
Developing pharmaceuticals using quantum computing could be a life-changing step. Quantum computers have the power to perform computational tasks exponentially faster than conventional computers. That means they could potentially improve clinical development, accelerate data-rich R&D processes, and repurpose existing therapeutics.
However, the technology is still very new and not yet widely understood. As such, it will be important for pharmaceutical firms to evaluate how they are positioned to benefit from the technology, as well as their strategic stance toward quantum computing.
The earliest applications of quantum computing are likely to be in drug discovery at the early stages of development. This could include optimizing drug-candidate interactions with physiologically relevant proteins, as well as finding smaller molecules for improved delivery methods.
Quantum computers can also perform simple calculations that predict the behavior of medium-sized pharmacological molecules. This can take years. However, quantum computing is capable of performing accurate data projections. That means a researcher could evaluate computational libraries against a large number of target structures in parallel. This could shorten the time it takes to find a drug-candidate target, and eliminate research dead ends.
Cybersecurity & Cryptography
Having a robust cryptosystem has been a part of the security infrastructure since time immemorial. It has been used for confidentiality, integrity, non-repudiation, and more. It has also been targeted by various attacks, from brute force to side channel to quantum computation.
The US National Security Agency (NSA) has stated that cryptosystems are vulnerable to quantum computing. In 2015, the NSA recommended that businesses and government agencies replace their cryptosystems with more resilient solutions.
The White House has launched a committee to investigate quantum information science. The world’s cryptographers have tested and vetted methods for combating quantum attacks. It is not clear which ones will be most effective.
The US National Institute of Standards and Technology (NIST) has whittled down 65 candidate algorithms to 15. They will select the winners in a few months.
Using quantum computing to perform financial modelling could lead to a variety of positive results, including more efficient trading settlement processes, diversification of portfolios, and faster risk scenario simulations. Quantum computers are also expected to provide a new paradigm for combinatorial optimization problems. This could help financial institutions build sophisticated models that can handle the ever-growing complexity of trading environments.
Financial institutions are already running experiments with quantum computing providers. Those experiments include Deutsche Bank’s testing of IBM’s 16-qubit quantum computer and PennyLane quantum computing framework in machine learning. These tests show that quantum computers can perform a large number of calculations faster than conventional computers.
Quantum annealing is also a technique that can be used to solve real-world problems. Its results are better than the results of a classical algorithm.
Using quantum computers to optimize logistics has the potential to change the way we view supply chains and supply chain management. It can help manufacturers and distribution companies improve business outcomes, reduce carbon footprints, and increase customer satisfaction. It can also help logistics companies save time and money.
Today, logistics decision makers use complex data every day. The logistics industry faces scheduling, routing, and inventory issues. These problems are difficult to solve with traditional systems. They require a system that can handle large quantities of data. However, as the volume of data increases, classical computers hit a wall. Their algorithms cannot quickly uncover the optimal routes.
Quantum computers can help solve these logistical problems more quickly and efficiently. Quantum computers can also improve the accuracy of logistics models. Quantum computers can process multiple models at the same time. Quantum computers can process data and adjust routes in real-time. Quantum computers can also help logistics companies track packages more accurately.