Staff writer Advay Jain explores the rapidly evolving relationship between quantum computing and artificial intelligence, unlocking how their fusion will revolutionize the future.
The most powerful computer in the world is Elpitan, capable of performing 1.6 billion calculations per second. To compare, the average computer can perform hundreds of millions of calculations per second.
But what if there are computers that are exponentially faster than the fastest ones you already have?
What is quantum computing?
Like AI, quantum computing has become a hot topic with the potential to change the world.
Unlike computers we know well, quantum computers operate within the principles of quantum mechanics.
Classic computers (everyday computers) use binary digits, 1 and 0 (also known as bits) to process information. A series of these bits represent everything stored in memory. They will remain the same unless they are changed.
In comparison, quantum computers use qubits (called qubits). This allows the combination of 0 and 1 to be expressed simultaneously thanks to the properties of the superposition. As a result of this property (and more) it is possible to process a significant amount of data in parallel, making it much faster than traditional computers.
However, Qubits are very sensitive to noise (changes in the environment). This instability can make the system less reliable and make it difficult to scale up.
Quantum computers can predict the behavior of molecules. This is a complex problem that is so complicated that classical computers take longer than the age of the universe.
Quantum computers can crack the most sophisticated systems currently in use, such as encryption methods. This puts personal data at risk, such as passwords, bank accounts and even government secrets.
Artificial intelligence in the quantum era
The AI market is projected to reach $1.85 trillion by 2030. As global use increases dramatically, current computers used to train AI will reach limits. Huge amounts of data, requests, experiments, and trust can push classical computers to limits and slow the pace of progress.
Here, Quantum computing is step-by-step through optimizations that process data via more efficient methods, accelerate AI arithmetic operations, enhance optimization, and allow for faster deployment of new AI models.
For example, drug discovery can be significantly faster, allowing life-saving treatments to reach patients faster. Solutions to some of the most important human challenges, such as climate change and sustainable energy, could become more achievable due to the power of this combination.
At the same time, AI strengthens this system by reducing errors, improving quantum architecture and fine-tuning systems, and making them more suitable for specific tasks.
Quantum computing and AI show mutually beneficial relationships. Here we evolve and complement each other. A true power couple.
Where are we now?
Google has developed Willow, a quantum chip that has achieved two important milestones. Scale with more Qubits, allowing you to exponentially reduce errors and perform standard benchmark calculations within 5 minutes.
Willow's computing power is related to its power efficiency. Unlike previous quantum chips, they operate at energy efficiency levels and are viable solutions for real applications such as finance and medicine.
Microsoft also developed the Majorana 1, a quantum chip that runs on a different topological kibit than Willow. Majorana 1 is currently in the prototype stage, while Willow is still in the experimental stage. Majorana 1 may have a theoretical edge on Willow in terms of scalability and final implementation in functional quantum computers.
Both chips provide solutions to the biggest problem. Noise begins to advance quantum computing.
This looks very promising, but quantum computing is still in its early stages. Consulting company McKinsey estimates that 5,000 quantum computers will be operational by 2030, but the hardware and software needed to make them useful will not be available until 2035.
