Quantum computers pose a risk to current encryption schemes, particularly public key cryptography, which relies on the difficulty of certain computational problems.

The idea that a quantum computer would be powerful was emphasized over 30 years ago by Richard Feynman, who believed that nature is quantum mechanical and that simulating nature should also be quantum mechanical.

The problems that quantum computers will solve are incredibly impactful, falling into two broad categories: quantum chemistry and machine learning.

Quantum computing has gained significant attention recently because it's starting to work in labs, reaching a point where it can perform tasks that classical computers cannot.

Quantum computers will likely excel in understanding and inventing new materials and chemical compounds, which are fundamentally quantum physics problems.

Grover's algorithm speeds up exhaustive searches through many possibilities, allowing quantum computers to handle larger problems more efficiently than classical computers.

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 gap between the theoretical usefulness of quantum computers at around 50 qubits and the practical requirements for tasks like code-breaking, which may need thousands of qubits, highlights the current limitations in quantum computing capabilities.

The practical impact of quantum computing will likely be seen in better methods for simulating quantum systems, which classical computers struggle to solve effectively.