Exploring Artificial Intelligence Concepts

What is a neural network and how does it function?

• A neural network is a computational model that simulates the way human brains process information, consisting of interconnected layers of nodes that learn from data.

• A neural network is a simple algorithm that does not require data to learn.

• A neural network is a type of hardware used for data storage.

• A neural network is a biological structure found only in animals.

Explain the role of tokenization in natural language processing.

• Tokenization is a method for encrypting sensitive information.

• Tokenization helps in translating text into different languages.

• Tokenization is used to summarize text into a single word.

• Tokenization is essential in NLP as it converts text into manageable units for analysis.

What are some ethical concerns associated with AI bias?

• AI bias is solely a technical issue without ethical implications.

• AI bias has no impact on decision-making.

• AI bias raises ethical concerns related to discrimination, inequality, trust, and the impact on critical decision-making.

• AI bias promotes fairness and equality.

Describe a common technique used in computer vision for image classification.

• Convolutional Neural Networks (CNNs)

• K-Nearest Neighbors (KNN)

• Support Vector Machines (SVMs)

• Decision Trees

How do convolutional neural networks differ from traditional neural networks?

• Convolutional Neural Networks use convolutional layers and pooling, while traditional Neural Networks use fully connected layers.

• Convolutional Neural Networks only work with images, while traditional Neural Networks can handle any data type.

• Traditional Neural Networks use convolutional layers, while Convolutional Neural Networks use recurrent layers.

• Convolutional Neural Networks are slower than traditional Neural Networks in all cases.