View source for 18214716. OPTIMIZING BEHAVIOR AND DEPLOYMENT OF LARGE LANGUAGE MODELS simplified abstract (Microsoft Technology Licensing, LLC)

=OPTIMIZING BEHAVIOR AND DEPLOYMENT OF LARGE LANGUAGE MODELS=


==Organization Name==

[[:Category:Microsoft Technology Licensing, LLC|Microsoft Technology Licensing, LLC]]


[[Category:Microsoft Technology Licensing, LLC]]

==Inventor(s)==

[[:Category:David Herron Auld of Seattle WA (US)|David Herron Auld of Seattle WA (US)]][[Category:David Herron Auld of Seattle WA (US)]]

[[:Category:Kanio Georgiev Dimitrov of Redmond WA (US)|Kanio Georgiev Dimitrov of Redmond WA (US)]][[Category:Kanio Georgiev Dimitrov of Redmond WA (US)]]

[[:Category:Jafar Mahmoud Al-kofahi of Bothell WA (US)|Jafar Mahmoud Al-kofahi of Bothell WA (US)]][[Category:Jafar Mahmoud Al-kofahi of Bothell WA (US)]]

[[:Category:Jonathan Richard Malsan of Redmond WA (US)|Jonathan Richard Malsan of Redmond WA (US)]][[Category:Jonathan Richard Malsan of Redmond WA (US)]]

[[:Category:Diana Andrea Iftimie of Sammamish WA (US)|Diana Andrea Iftimie of Sammamish WA (US)]][[Category:Diana Andrea Iftimie of Sammamish WA (US)]]

[[:Category:Natasha Kohli of Bellevue WA (US)|Natasha Kohli of Bellevue WA (US)]][[Category:Natasha Kohli of Bellevue WA (US)]]

[[:Category:Chenmin Liu of Seattle WA (US)|Chenmin Liu of Seattle WA (US)]][[Category:Chenmin Liu of Seattle WA (US)]]

[[:Category:Christopher Diego Kinney of Redmond WA (US)|Christopher Diego Kinney of Redmond WA (US)]][[Category:Christopher Diego Kinney of Redmond WA (US)]]

[[:Category:Haizhen Zhang of Bothell WA (US)|Haizhen Zhang of Bothell WA (US)]][[Category:Haizhen Zhang of Bothell WA (US)]]

[[:Category:Daniel Akintola Fatade of Houston TX (US)|Daniel Akintola Fatade of Houston TX (US)]][[Category:Daniel Akintola Fatade of Houston TX (US)]]

[[:Category:Yousef Al-kofahi of Niskayuna NY (US)|Yousef Al-kofahi of Niskayuna NY (US)]][[Category:Yousef Al-kofahi of Niskayuna NY (US)]]

[[:Category:Charles David Williams of Seattle WA (US)|Charles David Williams of Seattle WA (US)]][[Category:Charles David Williams of Seattle WA (US)]]

==OPTIMIZING BEHAVIOR AND DEPLOYMENT OF LARGE LANGUAGE MODELS - A simplified explanation of the abstract==


This abstract first appeared for US patent application 18214716 titled 'OPTIMIZING BEHAVIOR AND DEPLOYMENT OF LARGE LANGUAGE MODELS

The present disclosure introduces methods and systems for accelerating the development of large language models (LLMs) solutions by providing a comprehensive cycle for developing, testing, deploying, and providing feedback on these solutions.

* Framework for accelerating the development of large language models (LLMs) solutions
* Complete cycle for developing, testing, deploying, and providing feedback on LLM solutions
* Methods and systems to support the entire process of LLM solution development
* Focus on improving efficiency and effectiveness in creating and implementing LLM solutions
* Integration of feedback mechanisms to enhance the performance of deployed LLM solutions

Potential Applications:
The technology can be applied in various industries such as natural language processing, machine learning, artificial intelligence, and data analytics.

Problems Solved:
This technology addresses the challenges of efficiently developing and deploying large language models, improving the accuracy and performance of language processing systems, and enhancing the overall effectiveness of language model solutions.

Benefits:
The benefits of this technology include faster development cycles, improved accuracy and performance of language models, enhanced efficiency in deploying solutions, and better feedback mechanisms for continuous improvement.

Commercial Applications:
This technology can be utilized in industries such as customer service, chatbots, virtual assistants, language translation services, and content generation platforms.

Questions about Large Language Models (LLMs):
1. How does this technology improve the development process of large language models?
2. What are the key benefits of using this framework for accelerating LLM solutions?

Frequently Updated Research:
Stay updated on the latest advancements in large language models, natural language processing, and machine learning to enhance the effectiveness of LLM solutions.


==Original Abstract Submitted==

The present disclosure relates to methods and systems that provide a framework for accelerating the development of large language models (LLM)s solutions. The present disclosure provides methods and systems that support a complete cycle for developing LLM solutions, testing the LLM solutions, deploying the LLM solutions, and providing feedback on the deployed LLM solutions.



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