Large Language Model Implementation

Generative Ecosystem

Government

2 min read

The project's main objective was to develop a customized implementation of the GPT-4 Large Language Model for a Government Agency. This AI chatbot was designed to provide information to Government officials and interact with citizens to offer support and assistance. The deployment aimed to improve efficiency and customer satisfaction while reducing the workload of the agency’s employees.

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The problem overview

Incorporating contextual knowledge into GPT-like models requires extensive fine-tuning and careful consideration of the type of knowledge being integrated. Balancing accuracy, efficiency, and relevance of the ingested documents presents a significant challenge.

Our solution

We began by ingesting contextual data in various formats such as PDFs, lists, and text files. This data was processed through an embedding layer to generate context for queries. Leveraging this contextual information, we deployed a chatbot model capable of handling inquiries from citizens, limited to a specific domain.

The results

Exceptional results were achieved through innovative solutions, turning the challenge at hand into measurable success.

Incorporating Contextual Knowledge:

The project underscored the challenge of integrating contextual knowledge into GPT-like models, requiring careful fine-tuning to balance accuracy, efficiency, and task relevance.

Personalized AI Solutions:

The project demonstrated the capability to provide customized AI solutions tailored to specific business needs, enabling organizations to leverage AI technology while maintaining data privacy and enhancing operational efficiency.

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