Staff Writer Advay Jain explores the rapidly evolving relationship between quantum computing and artificial intelligence, unpacking how their fusion could revolutionise the future.
The most powerful computer in the world is El Capitan, capable of performing one quintillion calculations per second. To compare, the average computer can perform around a few billion calculations per second.
But what if there exists a computer that is exponentially faster than the fastest one we already have?
What is Quantum Computing?
Quantum computing, like AI, has become a hot topic with world-changing potential.
Unlike the computers we are familiar with, a quantum computer operates within the principles of quantum mechanics.
A classical computer (everyday computers) processes information using binary digits, 1 and 0 (also called bits). A series of those bits represents everything stored in memory. Unless modified, they remain the same.
In comparison, quantum computers use quantum bits (known as qubits), which can represent a combination of 0 and 1 simultaneously thanks to the property of superposition. As a result of this property (and many more), it can process a significant amount of data in parallel, making it much faster than traditional computers.
However, qubits are very sensitive to noise (changes in their environment). This instability can render the system unreliable and make it harder to scale up.
Quantum computers can predict the behaviour of molecules, a problem so complex that it would take classical computers longer than the age of the universe.
Quantum computers will be able to crack the most sophisticated systems currently used, such as encryption methods. This puts personal data, such as passwords, bank accounts and even government secrets, at risk.
Artificial Intelligence in the Quantum Age
The artificial intelligence (AI) market is projected to reach $1.85 trillion by 2030. As worldwide usage drastically increases, the current computers used to train AI will reach their limitations. The sheer amount of data, requests, experiments and reliance would push classical computers to their limits, which can slow down the pace of progress.
Here’s where quantum computing steps in by processing data through more efficient methods, accelerating the arithmetic operations of AI, and enhancing optimisation, which would enable the deployment of new AI models quickly.
For example, drug discovery could become significantly faster, enabling life-saving treatments to reach patients sooner. Solutions to some of humanity’s most significant challenges, such as climate change and sustainable energy, could become more achievable with this combined power.
At the same time, AI will also enhance this system by helping to reduce errors, improving quantum architecture and fine-tuning systems to be more suitable for specific tasks.
Quantum computing and AI show a mutually beneficial relationship, where both evolve and complement each other—a true power couple.
Where are we now?
Google has developed its quantum chip, Willow, which has achieved two significant milestones. It can exponentially reduce errors as it scales up by using more qubits and has performed a standard benchmark computation in under five minutes, which would take today’s fastest supercomputer 10 septillion years.
Willow’s computational capacity is linked to its power efficiency. Unlike previous quantum chips, it operates at an energy efficiency level that makes it a viable solution for real-world applications, such as finance and medicine.
Microsoft has also developed its quantum chip, Majorana 1, which operates on topological qubits, different to Willow. Majorana 1 is currently in its prototype stage, whereas Willow is still in the experimental stage. Majorana 1 may have a theoretical edge over Willow in terms of scalability and eventual implementation in functional quantum computers.
Both chips provide solutions to the biggest issue—noise, paving the way forward for quantum computing.
Although this appears very promising, quantum computing is still in its early stages. McKinsey, a consulting firm, estimates that there will be 5,000 quantum computers operational by 2030, but the hardware and software necessary to make them useful won’t be available until 2035.
Advay Jain is a Natural Sciences student at King’s College London with a strong interest in quantum computing, artificial intelligence, and finance. An outspoken advocate for student engagement, he has represented peers at university level and partnered with the Financial Times to promote financial literacy in schools. His independent projects include AI-powered stock tracking tools and revision applications for A-Level students with grade prediction capabilities. With a clear voice and a sharp analytical lens, Advay explores how technology can shape the future in various sectors.
