Generative AI Focus and Comparison

Replicating human-like creativity in generating content (correct)

Emulating visual perception and recognition

Simulating natural language processing

Mimicking human behavior in decision-making

Generating random outcomes without a pattern

Creating new data from existing data (correct)

Producing a limited set of predefined outputs

Cloning existing information without modification

Generative AI focuses on supervised learning, while traditional AI uses unsupervised learning

Generative AI is capable of self-improvement, while traditional AI follows predefined rules

Generative AI can generate novel content, while traditional AI can only analyze existing data (correct)

Generative AI is designed for complex problem-solving, while traditional AI is limited to simple tasks

<p>GANs = Generative Adversarial Networks VAEs = Variational Autoencoders RNNs = Recurrent Neural Networks LSTMs = Long Short-Term Memory networks</p> Signup and view all the answers

<p>Inpainting = Filling in missing or corrupted parts of an image Text Generation = Generating human-like text based on a given prompt Style Transfer = Applying the artistic style of one image to another Data Augmentation = Expanding training data by creating variations of existing data</p> Signup and view all the answers

<p>Deepfakes = Creating realistic fake videos or audio recordings Drug Discovery = Generating new molecular structures with desired properties Music Composition = Creating original musical compositions using AI algorithms Image Synthesis = Generating realistic images from textual descriptions</p> Signup and view all the answers