Quantum computing is a technology that is gaining press and inspiring increased discussion, but it is one that still gives rise to myths and misconceptions. At the intersection of quantum computing and machine learning is the emerging and likewise mysterious theoretical field of quantum machine learning.

As current quantum systems continue to develop, more is being discovered by those within the field of quantum computing and quantum machine learning about their potential capabilities and limitations. With the aim of helping to demystify quantum technology, here are a few of the common misconceptions around machine learning and quantum tech.

Machine Learning and Quantum Tech – Common Misconceptions

Misconception: Quantum computers will replace classical computers

Truth: Quantum computing is an entirely new way of processing data from classical computing — and each is suited to different tasks

Whereas classical computers operate on traditional laws of physics and use binary bits (1s or 0s) to encode and store information, quantum computing operates on the laws of quantum physics and quantum mechanics and uses subatomic particles called quantum bits (qubits) that can store much more data (in numerous states at the same time) and process far more complex computations.

The vastly improved computational processing power of quantum computing gives it the potential to drive unprecedented technological innovation — including in the area of machine learning — but it is still a number of years off before it will become reliable and economical enough to see broad application in everyday life.

Whereas machine learning models may require months for training on classical systems, future ML models will take longer given an exponential increase in parameters. Quantum computing will extend the capabilities of classical computing in this regard, not replacing but rather augmenting conventional computers to support their abilities while performing certain specialized tasks with greater accuracy and efficiency.

A common current belief is that the future will bring hybrid computing models, and an interconnected computational landscape.

Misconception: Quantum computing will enable perfect machine learning

Truth: Quantum machine learning will be far faster, but there are still hurdles in the way.

Quantum-powered machine learning is still an emerging field, but so far testing has demonstrated that machine learning would be supercharged by a viable quantum computer, vastly speeding up the processing and analyzing of data and the translating of it into actionable intelligence — perhaps even delivering new and innovative ways to solve problems.

Before this can happen though, obstacles remain that need to be overcome. Machine learning is computationally expensive in terms of bits/qubits, and so long as scalable quantum information processing remains yet to be achieved, there isn’t a large enough number of qubits available in any current quantum computer to perform the majority of practical machine learning processes.

At the same time, artificial intelligence and machine learning have come a long way in the last decade, and quantum computing may likewise progress in ways that lead to its ubiquity in the not-too-distant future.

Misconception: Quantum computing and quantum machine learning will destroy cybersecurity.

Truth: The threats are real and the concerns are valid — but post-quantum encryption solutions are already developing

The exponentially greater speed and power of quantum computing does indeed pose threats to cybersecurity, as does machine learning supercharged by the capabilities of a quantum computer. A viable quantum computer running Shor’s algorithm could break even the most robust current public-key cryptography (PKC) quickly and easily in comparison to the thousands of years it would take for a classical computer to do the same. As it is, machine learning and AI are already becoming capable attack tools for hackers — quantum machine learning would necessarily be an exponentially more capable one.

However, when it comes to quantum computing and cybersecurity, all is not lost. In July 2022, the National Institute of Standards and Technology (NIST) announced four quantum-resistant encryption algorithms that will be used to create a post-quantum cryptography standard by 2024, ensuring formidable and varied approaches are available to defend information security.

In addition, companies are already offering innovative quantum-resistant encryption solutions to protect sensitive data against future threats from quantum computers and quantum machine learning, as well as those present today.

There are certainly reasons for optimism around advances in quantum computing and its potential to enhance machine learning algorithms in ways that will benefit a number of industries — at the same time, there is still the very real potential for quantum machine learning to cause disruptions that businesses will need to prepare for. Either way, understanding these technologies better will go a long way in helping businesses to get ahead of any changes and challenges they may bring.

Fortifying Data Security Against Advances in Machine Learning and Quantum Tech

Companies today are gaining greater awareness around the implications of machine learning and quantum tech and using this knowledge to take steps toward crypto agility. This means beginning to implement new, quantum-resistant encryption solutions.

Theon Technology delivers the highest level of digital encryption that is practical for widespread enterprise deployment. The Theon approach to next-generation cryptography mitigates quantum and machine learning threats of today and tomorrow with products focused on providing viable, revolutionary quantum-resistant encryption for both data in flight and at rest.

Theon’s software utilizes patented algorithms to deliver on the promise of a truly scalable, commercially viable, enterprise ready One Time Pad — the gold standard in cybersecurity. Our cryptographically secure random number generator exploits the proven properties of large irrational numbers to produce higher entropy keys, with no hidden patterns, ever.

And because Theon is a software approach, there’s no need for specialized hardware, driving flexibility across deployment models for a wide range of solutions in almost every industry and use case.


Quantum-proof your data today — Contact a Theon expert to begin the journey towards a revolution in data security for your organization. We also have free eBooks available for download, including our latest, The Big Clock, which outlines the urgency for updated cryptography with a rundown of the best quantum-resistant encryption solutions available.