Question 1

What is a neural network?

Accepted Answer

A neural network is a computing system inspired by biological brains. It consists of layers of interconnected nodes (neurons) that learn patterns from data by adjusting connection weights during training.

Question 2

What is a decision boundary?

Accepted Answer

A decision boundary is the line or surface that a trained model uses to separate different classes of data. In the AI Lab, you can watch this boundary form in real-time as the neural network trains.

Question 3

What does temperature do in an LLM?

Accepted Answer

Temperature controls the randomness of an LLM's output. Low temperature (e.g., 0.1) makes the model more focused and deterministic. High temperature (e.g., 1.5) makes it more creative and unpredictable.

Question 4

What is a loss function?

Accepted Answer

A loss function measures how wrong the model's predictions are. During training, the model tries to minimize this value. A decreasing loss curve means the model is learning and improving.

Question 5

How does linear regression work?

Accepted Answer

Linear regression finds the best straight line through data points by minimizing the sum of squared differences between predictions and actual values. It uses gradient descent to iteratively adjust the line's slope and intercept.

AI Lab

See how these models are being adopted in the real world