Building an intelligent computer using only a few qubits is currently a significant challenge. The power of quantum computing primarily lies in its ability to perform complex calculations and solve certain problems faster than classical computers by harnessing the properties of qubits. However, the number of qubits required to achieve meaningful computational capabilities for general-purpose intelligence is not yet well-defined.
To understand why a few qubits are not sufficient for general-purpose intelligence, it's important to consider the concept of quantum superposition and entanglement. Quantum superposition allows qubits to exist in multiple states simultaneously, exponentially increasing the computational possibilities. Entanglement links the states of multiple qubits, enabling correlations and dependencies that can be exploited in computations.
In classical computing, the complexity of problems that can be solved is related to the number of bits available. Similarly, in quantum computing, the complexity of problems that can be solved is linked to the number of qubits available. However, due to the phenomenon of quantum decoherence, which causes qubits to lose their quantum properties when interacting with the environment, maintaining the coherence and stability of qubits becomes increasingly challenging as the number of qubits grows. This is known as the "quantum noise" problem.
For meaningful and robust general-purpose intelligence, it is widely believed that a large-scale quantum computer with a sufficient number of stable qubits, in the range of hundreds or even thousands, would be required. Such a system would provide the computational power necessary to perform complex calculations and simulate intelligence. Researchers are actively working on developing fault-tolerant quantum computing systems that can effectively address the challenges of quantum noise and decoherence.
However, it's worth noting that the concept of "intelligence" is multifaceted and not solely dependent on the number of qubits. Intelligence involves various aspects such as learning, reasoning, understanding, problem-solving, and adaptability, which require sophisticated algorithms and computational models. While quantum computing has the potential to enhance certain aspects of computation, it is not a guarantee of intelligence on its own.
In summary, building an intelligent computer using only a few qubits is currently impractical. Achieving general-purpose intelligence would likely require large-scale, fault-tolerant quantum computers with a significant number of stable qubits, coupled with advanced algorithms and computational models specifically designed for quantum systems. The field of quantum computing is still in its early stages, and there is ongoing research and development to overcome the challenges and unlock the potential of quantum intelligence.