One of the key advantages of artificial intelligence (AI) in the networking arena is its ability to enable IT systems to self-correct for maximum uptime and provide prescriptive actions as to how to fix problems.
AI can be used to analyse network data from devices and make adjustments to routing and other settings, while identifying trends and patterns that may be affecting performance. This is able to reduce network latency, improve throughput and minimise congestion.
More importantly, AI can play an important role in the detection and prevention of cyber attacks by analysing network traffic and identifying unusual patterns or behaviours. And AI can also be used to automate an incident response, allowing IT teams to more successfully address security breaches.
However, as the datasets related to these and other analogous AI-related activities become ever-larger, new ways to improve AI algorithms are required to speed problem-solving and improve data integrity in the corporate network.
Quantum computing has the potential to achieve this goal. With the ability to significantly enhance AI algorithms, it’s no coincidence that the intersection of AI, quantum computing and corporate networks represents an area of active research and development in the IT arena.
According to accredited US-based data analyst Chisolm Ndukwu, the rise of quantum computing will change the way we interact with AI in the future. “This means we must stay informed so we can prepare for the changes and make the most of this exciting technology,” he says.
AI researchers are poised to make purposeful strides in corporate network security.
Undoubtedly, as AI and quantum computing technologies continue to evolve, they will have a significant impact on the corporate network by processing much larger and more complex datasets, allowing computational problems to be resolved considerably faster.
Acclaimed Indian author Amit Ray believes the primary aim of quantum computing and AI is to improve human freedom, dignity, equality, security and total well-being.
Extrapolating this line of thought, it’s likely that the combination of quantum computing and AI will fundamentally transform many functional areas of business management, including strategy, marketing, finance and human resources.
As we’ve noted, quantum computers possess tremendous potential for handling extremely large datasets. This enables users of the technology to deliver an accurate analysis of data in a much shorter period.
An unfortunate spin-off is quantum computers’ capability to break many of the currently used encryption methods, such as RSA and ECC, and facilitate data breaches. However, there is a more ethical side to the quantum coin which can outweigh the negative implications.
Quantum computers are able facilitate the development of new, more sophisticated encryption algorithms using cryptographic methods that are resistant to quantum attacks and thus successfully protect valuable data – and the internet’s unique structure.
According to Shohini Ghose, a quantum physicist and physics professor at Wilfrid Laurier University in Canada, the use of quantum uncertainty for encryption is one of the most interesting applications of quantum computing.
Ghose suggests that quantum uncertainty could create private keys for encrypting messages, so that hackers would have to break the laws of quantum physics to hack these keys.
Against this backdrop, AI researchers are poised to make purposeful strides in corporate network security. Without doubt, today’s networks are vulnerable. With frequent hacks, trust in the security of the internet has been waning for some time.
Quantum networks could change this perception by enabling the erection of security barriers that rely on quantum uncertainty, along with other quantum phenomena.
These include superposition in which it is impossible to know with certainty the outcome of a measurement on a particle as it can be in two or more places at the same time.
Security barriers could also rely on quantum entanglement, the phenomenon that unites two objects, no matter how far they are separated.
Quantum entanglement is a participant in the development of quantum cryptographic protocols which exploit quantum rules to provide ultra-secure communication across channels that, in terms of current thinking, are completely immune to unauthorised breaches.
As mentioned, quantum computers can accelerate the training of machine learning models by assisting machine learning algorithms to process increasingly large amounts of data. This is key to the models’ ability to learn and improve their accuracy. This is achieved by processing multiple data points simultaneously through quantum parallelism.
Computer scientist and author Viraj Kulkarni points out that quantum parallelism forms the heart of many quantum algorithms, including quantum annealing, which is a method used to find the optimal solution to problems of enormous complexity involving an unimaginably large number of solutions.
From a scientific perspective, quantum annealing leverages the principles of quantum mechanics and quantum variational algorithms that use parametrised quantum circuits to solve optimisation problems that are important in machine learning.
In short, these functions will allow businesses to automate more tasks, minimise costs, reduce waste, boost security and improve efficiency, while making more informed decisions and accurate predictions within the orbit of new, revolutionary networking technologies and astonishingly sophisticated corporate networks.