a) Al>DL>ML>Gen AI
b) Al>ML>DL>Gen AI
c) DL>AL>ML>Gen AI
d) None of the above
None of the provided options accurately describes the main goal of Generative AI. The primary objective of Generative AI is to produce new, original content—such as text, images, or audio—based on patterns learned from existing data, rather than to establish a hierarchy of artificial intelligence concepts.
Generative AI involves models and techniques (e.g., GANs, VAEs, large language models) capable of creating new data similar to the input they were trained on, generating fresh textual content, images, and even realistic simulations.
Generative AI has a wide range of applications, including content creation, design prototyping, drug discovery, and more. For instance, it can help artists and designers rapidly produce multiple design variations, assist in generating realistic human-like text for chatbots, and aid in scientific research by proposing potential molecular structures.
Similar Questions
a) General Processing Technology
b) Generative Pre-trained Transformer
c) Global Pattern Tester
d) Graphical Programming Tool
GPT stands for "Generative Pre-trained Transformer," a type of language model developed by OpenAI. It is pre-trained on extensive text data to generate coherent and human-like responses based on given prompts.
a) Tacotron
b) Convolutional Neural Network (CNN)
c) Support Vector Machine (SVM)
d) Random Forest
Tacotron is a generative model designed for end-to-end speech synthesis. It can convert text into natural-sounding speech outputs without the need for complex, hand-engineered feature extraction processes.
a) To confuse the AI model
b) To optimize inputs for desired AI outputs
c) To increase the AI’s processing speed
d) To reduce the AI model’s size
Prompt engineering involves carefully constructing the input prompts given to an AI model. By optimizing how queries are presented, it helps guide the model toward generating more accurate, relevant, and context-appropriate responses.
a) AI with multiple personalities
b) AI that processes multiple types of data
c) AI for multi-player games
d) AI with multiple models
Multi-modal AI refers to systems capable of interpreting and integrating different types of data (e.g., text, images, audio) to make informed decisions or produce outputs. This allows for richer, more contextually aware interactions with diverse information sources.