Discover how GPT models excel in natural language processing and code generation. Learn why they are the preferred choice for creating human-like text and enhancing AI-driven applications.
Table of Contents
Question
Which of the following systems is recommended for generating natural language and completing code based on prompts written using natural language?
A. Microprocessor without Interlocked Pipelined Stages (MIPS)
B. GPT models
C. DALL-E models
D. Embedding models
Answer
B. GPT models
Explanation
The system capable of generating natural language and completing code based on prompts written in natural language is GPT models. GPT models are specifically designed for the following tasks:
- Natural language generation: Creating human-quality text in various styles and formats, such as poems, code, scripts, musical pieces, email, and letters.
- Code completion: Predicting and suggesting the most likely continuation of a code snippet based on the context.
DALL-E models are not the appropriate choice for this scenario. While DALL-E models are powerful for image generation based on textual descriptions, they are not designed for natural language or code generation.
Embedding models are not the appropriate choice for this scenario. These models convert text into numerical representations, making them useful for tasks such as text similarity analysis but not for generating text or code.
Microprocessor without Interlocked Pipelined Stages (MIPS) is a type of computer processor architecture and is completely unrelated to the functionalities of natural language or code generation.
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