Intel corporation (20240338397). METHODS AND APPARATUS TO DETERMINE A NUMBER OF DENOISING ITERATIONS FOR MODEL OUTPUT GENERATION simplified abstract
Contents
METHODS AND APPARATUS TO DETERMINE A NUMBER OF DENOISING ITERATIONS FOR MODEL OUTPUT GENERATION
Organization Name
Inventor(s)
Haim Shmuel Barad of Zichron Yaakov (IL)
Harsha Gupta of Sunnyvale CA (US)
METHODS AND APPARATUS TO DETERMINE A NUMBER OF DENOISING ITERATIONS FOR MODEL OUTPUT GENERATION - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240338397 titled 'METHODS AND APPARATUS TO DETERMINE A NUMBER OF DENOISING ITERATIONS FOR MODEL OUTPUT GENERATION
Simplified Explanation: The patent application discloses methods, apparatus, systems, and articles of manufacture to determine the optimal number of denoising iterations for generating model outputs based on a text-based prompt.
- The apparatus includes programmable circuits to execute a model and generate multiple outputs with varying numbers of denoising iterations.
- It orders the outputs based on the number of denoising iterations and analyzes similarities between neighboring outputs.
- The apparatus then selects the most suitable number of denoising iterations based on these similarities.
Key Features and Innovation:
- Utilizes denoising iterations to enhance the quality of model outputs.
- Automates the process of determining the optimal number of denoising iterations.
- Improves the efficiency and accuracy of model output generation based on text prompts.
Potential Applications: This technology can be applied in natural language processing, machine learning, and artificial intelligence systems to improve the quality of generated outputs.
Problems Solved:
- Addresses the challenge of determining the optimal number of denoising iterations for model output generation.
- Enhances the accuracy and reliability of model outputs based on text prompts.
Benefits:
- Improves the overall performance of models in generating outputs.
- Reduces manual intervention in the selection of denoising iterations.
- Enhances the quality and relevance of generated outputs.
Commercial Applications: Potential commercial applications include chatbots, virtual assistants, automated content generation systems, and data analysis tools in various industries.
Questions about Denoising Iterations: 1. How do denoising iterations impact the quality of model outputs? 2. What are the key factors to consider when selecting the optimal number of denoising iterations?
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Original Abstract Submitted
methods, apparatus, systems, and articles of manufacture to determine a number of denoising iterations of model output generation are disclosed. an example apparatus includes at least one programmable circuit to execute a model to generate a plurality of outputs based on a text-based prompt, each of the plurality of outputs generated using different numbers of denoising iterations; generate an ordered set of the plurality of outputs based on the number of denoising iterations; determine a plurality of similarities between neighboring outputs in the ordered set of the plurality of outputs; and select a number of denoising iterations based on the plurality of similarities.
