How will quantum computing change artificial intelligence?

When the terms "quantum" and "computing" are mentioned, it's easy to think of science fiction shows like "Star Trek." Quantum computing performs calculations quickly by exploiting the collective properties of superposition, interference, and entanglement. Fortunately, most people don’t need to care about the details; they just need to know this: Quantum computing means faster data access and more secure networks.

With every document saved, link clicked, and photo taken, people are both creators and consumers of data. The world generates at least 2.5 EB of data every day. Large amounts of data provide the basis for effective machine learning used by artificial intelligence; the more information an algorithm consumes, the more successful its predictions or decisions will be. However, exponential growth and increasing query complexity require the speed and stability that quantum computing provides.

Artificial intelligence is a general technology based on big data. By analyzing data sets, AI can identify patterns and predict events. In the past, the bottleneck to improving artificial intelligence was the cost of collecting and storing data. Today, the challenge is to consume, search, and deliver meaningful results within a reasonable time frame, and quantum computing can help.

Improve business decision-making process

As we move towards a future of quantum computing, improved productivity and faster decision-making will be the theme of its application. There are considerable advantages to analyzing data, predicting trends, and reaching your target audience.

How do quantum computing and artificial intelligence bring value to enterprises’ business decision-making processes? Consider the following possibilities identified by each industry sector:

(1) Financial

Enhance fraud detection, determine asset pricing, simulate trading activity and analyze historical data to improve market forecasts and limit financial risk.

(2) Utilities and Energy

• Process energy system data to assist in grid optimization.
• View customer analytics to predict usage, preferences and future needs.
• Expand the simulation to include weather data or market trends (such as an increase in the number of electric vehicles) to gain insight into the infrastructure upgrades that may be needed to maintain service.

(3) Aviation

• Use predictive analytics to assist airlines with schedules and staffing.
• Use sophisticated scenario modeling to recover from operational disruptions such as mechanical failures, weather events, and even COVID-19 issues.

(4) Insurance

• Perform weather simulations for disaster modeling to drive the development of policy limits and guide customer pricing.
• Attract and retain customers by finding ways to automate claims capabilities, predict preferences, and provide preemptive product and service recommendations.

(5) Retail

Track annual sales to help predict inventory needs and manage supply chain management issues.

(6) Healthcare

• Provide information from pharmaceutical companies outlining expected effects, potential side effects and contraindications.
• Predict the outcomes of treatment plan options, leveraging the power of quantum simulation and multivariate scenarios to describe age, gender, underlying conditions and geographic location.
• Provides instant access to all medical images while providing comparative analysis of anomalies and anomalies.
• Simplify and automate management processes, identify service bottlenecks, eliminate costly redundancies, and increase patient access to healthcare resources.

Security of Artificial Intelligence and Quantum Computing

Keeping up with the evolution of security threats and attacks has always been a challenge. By combining the data analysis capabilities of AI with the speed of quantum computing, businesses can better predict possible security risks and defend against potential cyberattacks.

As quantum computing and artificial intelligence advance, it is important to understand that validating data is just as important as analyzing it. Weaponizing data, disrupting analytics, and disrupting the experiential learning that AI systems are doing is an emerging form of cyberterrorism that should not be ignored.

Quantum computing and artificial intelligence complement DevOps

Quantum computing and artificial intelligence are powerful allies for DevOps teams as they work to determine business priorities and goals, design and develop new software solutions, as well as managing ongoing maintenance and testing of existing applications.

DevOps teams can view data provided by artificial intelligence to assist with regression testing, functional testing, and user acceptance testing. Because quantum computing provides AI with the ability to quickly and efficiently process data from numerous sources, such as various siled departments within a large organization, testing can be consistent and comprehensive.

Using Quantum Computing and Artificial Intelligence to Assist IT Operations

Where are enterprises’ IT systems vulnerable to attacks? When do you need to upgrade hardware or software? How can incidents be resolved faster? How much time is spent managing tasks that can be automated? These types of IT operations questions are best answered through big data analytics. With the speed provided by quantum computing, these AI queries can provide complete visibility into operational data and deliver real-time insights.

As companies leverage quantum computing and artificial intelligence, it will be even more exciting to see how these technologies can help develop disease treatments, alleviate traffic jams, or protect sensitive data to truly benefit humanity!

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