What Is Quantum Machine Learning? | TensorFlow Quantum

The video tutorial introduces classical computing concepts, such as binary code, and contrasts them with quantum computing principles like superposition and entanglement. It discusses the challenges of quantum computing, including decoherence, and the potential for quantum supremacy. The tutorial then focuses on simulated quantum computing using TensorFlow, demonstrating how to build and train a neural network to calibrate qubits. The video concludes with practical examples of training models using quantum circuits.

What is the primary function of bits in classical computing?

• To simulate quantum states

• To provide explicit instructions to computers

• To store data in multiple states simultaneously

• To connect computers through entanglement

How does a qubit differ from a classical bit?

• A qubit cannot be entangled with another qubit

• A qubit is used only for classical computing

• A qubit can exist in multiple states simultaneously

• A qubit can only be 0 or 1 at a time

What is quantum supremacy?

• The ability of classical computers to outperform quantum computers

• The demonstration that quantum computers can solve problems faster than classical computers

• The phenomenon where qubits lose their quantum properties

• The process of converting qubits back into bits

What is decoherence in quantum computing?

• The loss of quantum properties when qubits are observed

• The connection between two qubits through entanglement

• The process of qubits maintaining their quantum properties

• The ability of qubits to exist in multiple states

Why is consumer quantum computing challenging to achieve?

• Quantum computers cannot solve complex problems

• Quantum computers are too expensive to produce

• Quantum computers require extremely cold and vibration-free environments

• Quantum computers are too large to fit in homes

What is the goal of the neural network in the simulated quantum computing tutorial?

• To create a new quantum algorithm

• To calibrate a simulated qubit to output the correct value

• To develop a classical computing model

• To simulate quantum entanglement

What tool is used in the tutorial to develop a quantum machine learning model?

• IBM Quantum Experience

• Amazon Web Services

• Google Collab and TensorFlow

• Microsoft Azure