Amazon technologies, inc. (20240202466). ADAPTING PROMPTS SELECTED FROM PROMPT TASK COLLECTIONS simplified abstract

ADAPTING PROMPTS SELECTED FROM PROMPT TASK COLLECTIONS

Organization Name

amazon technologies, inc.

Inventor(s)

Sheng Zha of New York NY (US)

Miguel Ballesteros Martinez of New York NY (US)

Yassine Benajiba of Briarcliff Manor NY (US)

Cole Hawkins of New York NY (US)

Aditya Rawal of Mountain View CA (US)

Dhananjay Ram of Kirkland WA (US)

Min Rong Samson Tan of Mountain View CA (US)

Vittorio Castelli of Croton-on-Hudson NY (US)

ADAPTING PROMPTS SELECTED FROM PROMPT TASK COLLECTIONS - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240202466 titled 'ADAPTING PROMPTS SELECTED FROM PROMPT TASK COLLECTIONS

• • Simplified Explanation:**

The patent application discusses techniques for tuning natural language processing machine learning models using selected prompts from a prompt task collection.

• • Key Features and Innovation:**
• Implementing prompt development techniques for tuning machine learning models.
• Adapting pre-trained models for use with selected prompts.
• Evaluating and providing results of the tuned machine learning models.

• • Potential Applications:**

This technology can be applied in various fields such as chatbots, sentiment analysis, and text classification.

• • Problems Solved:**
• Enhancing the performance of natural language processing models.
• Improving the adaptability of pre-trained models to specific prompts.

• • Benefits:**
• Increased accuracy and efficiency in natural language processing tasks.
• Customization of machine learning models for specific applications.

• • Commercial Applications:**
• "Enhancing Natural Language Processing Models for Industry-Specific Applications"

• • Prior Art:**

Researchers can explore existing literature on prompt-based tuning of machine learning models in the field of natural language processing.

• • Frequently Updated Research:**

Stay informed about the latest advancements in prompt-based tuning techniques for natural language processing models.

• • Questions about Prompt Development Techniques:**

1. How do prompt development techniques improve the performance of machine learning models? 2. What are the key benefits of adapting pre-trained models for specific prompts?

Original Abstract Submitted

prompt development techniques are implemented for tuning natural language processing machine learning models using selected prompts from a prompt task collection. a prompt development system may support requests to further adapt a pre-trained natural language processing machine learning model to tune the pre-trained natural language processing machine learning model for use with a selected prompt. evaluation of the tuned natural language processing machine learning model may be performed and provided as a result.