The challenge in quantum computing lies in scaling; while achieving high fidelity with a small number of qubits is possible, creating a robust system that consistently performs well with a larger number of qubits is a significant engineering problem.

Superconducting qubits are the primary approach used by companies like Google, IBM, and Intel, each with its own strengths and weaknesses compared to other quantum computing methods.

To be genuinely useful, a quantum computer needs to exceed 50 qubits, as tasks requiring fewer qubits can still be efficiently simulated by classical computers, making them less impactful.

The ability to lay out qubits in a grid simplifies the design of quantum computers, as it aligns with the short-range interactions typical in quantum physics, making it easier to achieve reliable operations. Topological codes allow qubits to be arranged in a grid, enabling them to communicate with immediate neighbors without the need for extensive movement, which simplifies operations significantly.

The approach to scalability in quantum computing involves creating small, efficient quantum modules that can be linked together, rather than trying to scale up a single large quantum computer, which presents numerous challenges.

Qubits, the building blocks of quantum technology, are inherently unstable and tend to collapse to a single state, making them difficult to control compared to classical bits.

Network approaches to quantum computing enable any qubit to link with any other qubit, enhancing connectivity and power, despite the increased risk of errors if not managed correctly.

Topological codes, particularly the higher surface code, are promising approaches for building quantum computers due to their simpler architecture, allowing qubits to be arranged in a grid and only requiring local interactions.

The key to effective quantum computing is ensuring qubits interact as desired, rather than just focusing on increasing coherence times.