Artificial Intelligence, Quantum 3 MIN Read

The Next AI Wave: Quantum AI

May 21st, 2024


Prepare for the power of quantum.

Amid all of the (well-placed) excitement around artificial intelligence, quantum AI is an emerging field that combines the power of quantum computing with AI to create new and innovative solutions for an array of complex problems.

Here’s why: Quantum computing is a method of solving complex problems in ways that classical computing cannot. Similarly, quantum AI can perform certain types of machine learning tasks much more efficiently than classical AI. By combining them, we create new and powerful capabilities.

For instance, quantum AI can train neural networks for image and voice recognition using large datasets in a fraction of the time it would take for classical AI, leading to more accurate predictions and better performance. Quantum AI can also train machine learning models on large datasets, which allows for more efficient processing of large amounts of data, which is particularly useful in machine learning applications where large datasets are common.

Early Quantum AI Use Cases Hold Insights for Agencies

Though it is in its early stages, quantum AI has the potential to revolutionize many industries, and the learnings from early industry pilots hold tremendous insights for agencies.

In finance, quantum AI can be used to analyze financial data and identify trends, which leads to more accurate predictions and better investment decisions. One can imagine the impact on, perhaps, fraud detection within agencies such as the Securities and Exchange Commission, the Internal Revenue Service or Centers for Medicare and Medicaid Services, to name a few.

In cybersecurity, a significant concern is that quantum computers can break many of the encryption algorithms used to secure data. Quantum AI can create new and more secure encryption methods that are resistant to quantum computers. Quantum AI can also enhance network security where it can analyze large amounts of network traffic and detect anomalies that may indicate a security threat, improving the overall security of networks. Every agency has an interest in improving is cybersecurity posture and adding more dynamic detection capabilities, alongside the increasing adoption and maturation of new paradigms like zero trust.

In healthcare, quantum AI can be used to analyze medical images and identify patterns that may not be visible to the naked eye. This could lead to more accurate diagnoses and better treatment outcomes.

And in transportation, quantum AI can be used to optimize traffic flow and reduce congestion, leading to faster travel times and improved air quality. Alongside the recent multi-billion dollar investment in America’s infrastructure, implementing quantum AI to optimize that investment is a logical goal.

Preparing for Quantum AI Exploration and Adoption

No matter the agency or mission, it’s important to remember that quantum AI is not just about the technology itself. It also requires a skilled workforce capable of developing AI algorithms that can take advantage of the exponential increase in power that quantum computers bring. Already, companies and universities are increasing their focus on quantum computing and have programs directly related to quantum AI.

For example, today GDIT is actively working with universities and quantum technology companies on software skill development for developers and applying quantum AI techniques to solve real customer use cases. The most exciting part: Continued advances in quantum computing and in AI will generate progressively more sophisticated algorithms that will become more powerful and efficient, allowing for even greater performance on complex problems.