Top 4 Quantum Computing Applications an AI Professional Needs to Know

The global quantum computing market is forecasted to grow by USD 7.35 billion through 2021 – 2025, says ResearchAndMarkets.

Despite being at the nascent stage, quantum technology did make quite an entry into the technology industry. From achieving quantum supremacy to taking the first step toward the quantum brain, technology is becoming the talk of the town.

The technology theory is still hypothetical in nature and there’s still a long road ahead, but who can stop predictions. Also, predictions by McKinsey claim that organizations may reap great benefits from quantum computing in the next five years. Therefore, this could be an ideal year to prepare for the next big wave.

Quantum computers encompass four different components that make them unique from today’s classical computers – quantum simulation, optimization, quantum artificial intelligence (AI), and prime factorization.

One of the major ways to see how this technology function is by simply understanding its capabilities by tackling a few cases. From finance to pharmaceutical and cybersecurity, these are certain ways quantum is making major advancements in the tech industry.

1.Secure data using quantum cryptography

Quantum cryptography is making recent advancements in cybersecurity by developing a highly-secured encryption system. It uses a method known as quantum key distribution. With the help of this method, the encrypted data needs to use a certain to generate and decode with the help of the quantum method. Now, this method makes it difficult for anybody to crack or decrypt, thus provides greater levels of data protection, better than any cybersecurity could offer. Businesses and organizations could cut a great deal by using quantum cryptography to secure the critical data of the government. This method also proves beneficial to digitize processes if they haven’t been processed yet. This could be a great innovation as we can see how IoT is expanding.

2.Help researchers build better scientific models

Scientific modeling is a method or process used in understanding natural processes or systems with the help of simulations and models. In this case, quantum computing can be used by scientists to perform an experiment and gain positive insights into subjects like medicine, astrophysics, chemistry, and other relevant fields. Although, researchers said that the technology is making great strides by using deep learning for drug discovery, yet it cannot confirm whether scientific computing has the capability of reproducing high complex systems. However, this doubt can be solved using scientific modeling wherein scientists get to analyze and construct complex systems.

3.AI systems to become faster and smarter

No doubt AI is becoming smarter with each passing day and is also becoming much more capable to perform complicated tasks even with limited training. But these systems can be versatile, they have limitations and can respond only to certain situations. However, to make these systems respond appropriately they would need a wide range of possible outcomes and situations. Quantum computing can easily enable AI systems to make better prediction outcomes even during situations with a high number of outcomes. This will also help machine learning learn faster to become more effective.

4.Weather prediction with better accuracy

We could say that a considerable portion of the planet’s economy depends on the weather. Transport, agriculture, retail, and other related industries have been highly impacted due to the unpredictable weather conditions.

Though weather forecasting methods have been used previously, it was not effective. But with the help of quantum computing, we can now have certainty in predicting weather conditions. This can further help entities whose operations are solely based upon the weather conditions. Doing so can make industries more reliant on technology and can become less prone to undergoing risks that are caused by uncertain weather conditions.