Imagine a world where computer problems can be solved that are considered unsolvable today. A world where the limits of data processing are redefined and Artificial Intelligence (AI) masters challenges that were previously unimaginable. This vision is getting closer with the development of quantum computers and their connection with AI. Quantum AI could be the next big revolution in technology, comparable to the leap from conventional CPUs to GPUs by companies like NVIDIA. But what does this mean for companies, and how can they prepare?
What are Quantum Computers?
The Basics of Quantum Physics
Quantum computers are based on the principles of quantum mechanics, a branch of physics that describes the behavior of particles at the atomic and subatomic level. Unlike classical physics, where objects have a specific state, in the quantum world, particles can exist in multiple states simultaneously.
Qubits Instead of Bits
In classical computers, information is stored in bits that have either the value 0 or 1. Quantum computers, on the other hand, use Qubits (quantum bits), which, thanks to the principle of superposition, can take on both the state 0 and 1 simultaneously. This enables quantum computers to process an enormous number of states at once.
Superposition and Entanglement
Superposition allows qubits to occupy multiple states at the same time. This leads to an exponential increase in computing power for certain problems. Entanglement is another quantum physical phenomenon in which two or more qubits are connected in such a way that a change in the state of one qubit immediately affects the state of the other – regardless of the distance between them. These properties enable quantum computers to perform calculations that are unreachable for classical computers in this form.
Current State of Quantum Computers
First Successes with Few Qubits
Although quantum computers are still in their infancy, there are already functioning systems with a limited number of qubits. Companies like IBM (featured image), Google, and others have developed quantum computers that can perform simple calculations. These systems are not yet powerful enough for complex commercial applications but demonstrate the technology’s potential.
Python SDKs and First Steps
For developers and researchers, there is already the possibility to experiment with quantum computers. Tools like Qiskit from IBM allow programming quantum algorithms in Python and running them on real quantum computers or simulations. These SDKs (Software Development Kits) provide a platform to learn the basics of quantum computing and develop first applications.
Challenges
One of the biggest challenges with quantum computers is measuring the state of qubits without disturbing them. The quantum state is extremely fragile and can be changed by even the smallest external influences. This makes it difficult to build stable and reliable quantum computers. Additionally, qubits must be protected from external influences like temperature changes or electromagnetic fields, which often requires extreme conditions. Building a quantum computer powerful enough to solve practical problems requires scaling to many qubits. However, each additional qubit increases complexity and the potential for errors. The development of effective error correction procedures is therefore a central research area.
Example: The Traveling Salesman Problem
An illustrative example of quantum computer application is the Traveling Salesman Problem (TSP). This problem belongs to the class of NP problems (non-deterministic polynomial time), where the goal is to find the shortest route that visits a series of cities and returns to the starting point. Classical computers can only solve this problem through approximation methods, as the number of possible routes grows exponentially with the number of cities. Quantum computers, however, could be able to solve this problem efficiently by calculating all possible routes simultaneously and finding the optimal route. This could have significant impacts on areas like logistics and navigation systems, where currently there are often only suboptimal solutions.
Example: Cryptography and Quantum Computers (Post-Quantum Cryptography)
Another illustrative example of the impact of quantum computers is cryptography, the foundation of security on the Internet and in online banking. Today’s encryption methods like RSA, ECC (Elliptic Curve Cryptography), and AES (Advanced Encryption Standard) are based on mathematical problems that are difficult for classical computers to solve. These problems belong to the class of NP problems (non-deterministic polynomial time), which are difficult or impossible to solve efficiently by classical computers. Since most currently used encryption methods are not designed for the threats posed by quantum computers, the development of Post-Quantum Cryptography (PQC) is an urgent research field. PQC methods are based on mathematical problems that are also difficult for quantum computers to solve, such as lattice problems, code-based cryptography, and hash-based signatures.
What is Quantum AI?
The Connection of Quantum Computers and Artificial Intelligence
Quantum AI refers to the application of quantum computing to improve AI methods, especially machine learning. By using the quantum mechanical properties of qubits, algorithms could be developed that learn faster and recognize more complex patterns than their classical counterparts.
Potential Benefits
The ability of quantum computers to perform certain calculations faster opens doors to solutions that were previously beyond our reach. For example, optimization problems in logistics, such as optimal route planning for deliveries, could be solved more efficiently. In the financial industry, complex risk modeling could be performed faster and more accurately. In areas like materials science or drug development, quantum computers could enable the simulation of molecules that are too complex for classical computers. This could lead to new materials or medications that remained undiscovered before.
Quantum Computers for Enterprises
It will still be some time before market-ready quantum computers are available. Nevertheless, the research field is enormously exciting as it allows solving problems that are considered unsolvable today. One example is the security of the entire Internet: Quantum computers could crack existing encryption methods, making the development of Post-Quantum Cryptography a critical research area. In fact, research on quantum computers and Post-Quantum Cryptography is currently even more extensive than that on Quantum AI.
Realistically, entering quantum computing or developing Quantum AI is not yet possible or economically sensible for most companies. Nevertheless, the long-term potential should not be underestimated, and the topic should at least be monitored. Quantum computers are a huge research field and could be the high-performance computers of tomorrow. Companies that already want to experiment today can use Python SDKs like Qiskit and calculate their first qubits at hyperscalers like IBM, Google, Amazon Web Services, or Microsoft Azure. This allows gaining initial experience and preparing for the future.
Update December 13, 2024
Quantum Chip from Google Presented – What Can “Willow” Do?
Google recently presented its latest quantum chip named “Willow,” which achieves two essential milestones through its groundbreaking performance. First, Willow can reduce errors exponentially as the number of qubits is increased, solving a central problem in quantum error correction that researchers have been working on for almost three decades. Second, Willow completed a standard benchmark calculation in less than five minutes that would take about 10 septillion years on today’s supercomputers – a number that far exceeds the age of the universe. These advances underscore that Willow represents a significant step toward commercially relevant quantum applications and has the potential to advance scientific discoveries and address complex societal challenges. With 105 qubits and improved error correction, Willow shows that building useful, large-scale quantum computers is becoming reality and is approaching practical, superclassical algorithms that are unattainable on conventional computers.