Microsoft Technology Licensing, LLC (20240296314). GENERATIVE ARTIFICIAL INTELLIGENCE (AI) SYSTEM simplified abstract

GENERATIVE ARTIFICIAL INTELLIGENCE (AI) SYSTEM

Organization Name

Microsoft Technology Licensing, LLC

Inventor(s)

Nitant Singh of Sammamish WA (US)

Deepankar Shreegyan Dubey of Redmond WA (US)

Stephen Michael Kofsky of Seattle WA (US)

Qiang Du of Mercer Island WA (US)

GENERATIVE ARTIFICIAL INTELLIGENCE (AI) SYSTEM - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240296314 titled 'GENERATIVE ARTIFICIAL INTELLIGENCE (AI) SYSTEM

Simplified Explanation: The abstract describes a system where a generative artificial intelligence model API processes generative AI requests, determines if they are synchronous or asynchronous, estimates the length of generation needed, evaluates available computing resources, and routes the request to a suitable generative AI model.

• Key Features and Innovation:

   - Generative AI model API for processing generative AI requests
   - Ability to handle both synchronous and asynchronous requests
   - Capacity evaluation of generative AI models based on request type and length of generation
   - Efficient routing of requests to appropriate generative AI models

• Potential Applications:

   - Content generation for creative industries
   - Personalized recommendations in e-commerce
   - Automated design creation in graphic design

• Problems Solved:

   - Efficient allocation of computing resources for generative AI tasks
   - Streamlined processing of generative AI requests
   - Improved scalability of generative AI models

• Benefits:

   - Faster response times for generative AI requests
   - Optimal utilization of computing resources
   - Enhanced performance of generative AI models

• Commercial Applications:

   - "Optimizing Generative AI Model Routing for Efficient Resource Allocation in Content Generation"

• Prior Art:

   - Further research can be conducted on existing generative AI model APIs and their routing mechanisms.

• Frequently Updated Research:

   - Stay updated on advancements in generative AI model APIs and resource allocation strategies.

Questions about Generative AI Model API: 1. How does the generative AI model API determine the length of generation needed for a request? 2. What are the potential challenges in routing generative AI requests to suitable models based on available capacity?

Original Abstract Submitted

a generative artificial intelligence (ai) model application programming interface (api) receives a generative ai request and routes the generative ai request to a generative ai model. the generative ai model api identifies whether the generative ai request is an asynchronous or a synchronous request and identifies a likely length of generation requested by the generative ai request. the generative ai model api evaluates the available capacity of generative ai models in a shared pool of computing system resources based upon the generative ai model type requested by the generative ai request and based upon the length of the requested generation. the generative ai model api routes the generative ai request to a generative ai model based upon the available capacity, whether the generative ai request is synchronous or asynchronous, the generative ai model type, and the length of the requested generation.