Introduction

In recent years, generative models have transformed the landscape of Artificial Intelligence (AI) and Natural Language Processing (NLP). One remarkable example is the GPT (Generative Pre-trained Transformer) series of models developed by OpenAI. These models have demonstrated the ability to generate coherent and contextually relevant text, enabling applications like ChatGPT, which engages in human-like conversations.

Building upon this technology, companies can harness the potential of an Internal GPT: a generative model trained on their own proprietary data and internal documents. This article delves into the concept of the Internal GPT and outlines the numerous benefits it can offer to organizations across various domains.

The Concept of Internal GPT

The concept of the Internal GPT is similar to the concept of the Intranet. In the same way that the Intranet was used to give access to information that is private (proprietary) to some company or organization, the Internal GPT can be used to ask questions about topics that are specific to some company or organization, and get answers that are based on existing internal documents, wikis and emails.

The Internal GPT concept revolves around training a generative model using an organization’s internal data. This data may include company reports, emails, internal wikis, presentations, customer support interactions, and any other proprietary textual content. The model learns from this data and becomes proficient in understanding the company’s language, context, and domain-specific knowledge.

Approach: How to build an Internal GPT

Large Language Models (LLMs) such as the famous ChatGPT were built using public information available on the Internet (including articles, blogs and books). The Internal GPT models can be built by extending existing LLMs with additional texts. These texts can be extracted from wikis or from platforms such as Confluence. A professional Data Scientist knows how to create a new model combining the previous (public) model with the new (private) texts.

Benefits of the Internal GPT

When an employee asks a question using the Internal GPT, the answer he/she will get will be based on both the public and the private information. In other words, the answers will be based on a combination of public knowledge and proprietary documentation.

Therefore these answers will be unique:

• The Internal GPT will generate answers that cannot be generated using ChatGPT.
• The Internal GPT will provide answers that cannot be found in internal documents only.

In other words, this Internal GPT, combining public and private information, will be smarter than ChatGPT and also smarter than any existing platform inside the corporation.

Potential Applications of the Internal GPT

1. Enhanced Document Generation: An Internal GPT can generate coherent and relevant text, which can be incredibly useful for creating internal reports, presentations, and other documents. It can summarize complex data and offer insights in a language consistent with the company’s style.

2. Efficient Customer Support: By training the model on historical customer support interactions, an organization can develop an AI-powered assistant that understands common queries and provides accurate responses, relieving the burden on human support agents.

3. Knowledge Management: Internal GPT can serve as a smart search tool, making it easier for employees to find information within the organization’s vast knowledge repositories. This can expedite decision-making and enhance collaboration.

4. Automated Content Creation: From blog posts to marketing materials, an Internal GPT can aid in generating content, saving time and effort for content creators while maintaining brand voice and consistency.

5. Strategic Planning: By analyzing large volumes of internal data, an organization can leverage its Internal GPT to identify patterns, trends, and insights, thus supporting strategic decision-making.

6. Training and Onboarding: The model can assist in creating training materials and onboarding guides for new employees, ensuring a smooth transition into the company’s processes and culture.

7. Risk Assessment and Compliance: Internal GPT can assist legal and compliance teams by analyzing contracts, regulations, and internal policies, thus mitigating risks and ensuring adherence to guidelines.

8. Innovation and Idea Generation: When employees need inspiration or brainstorming assistance, the model can provide novel ideas based on its analysis of the organization’s historical data.

9. Personalized Communications: Marketing and sales teams can use the Internal GPT to craft personalized messages for customers, tailored to individual preferences and behaviors.

Conclusion

The Internal GPT represents a transformative leap in harnessing proprietary data for enhanced productivity, innovation, and decision-making. By training a generative model on internal documents, companies can create a customized AI assistant that understands their unique language and context. From generating documents to optimizing operations, the applications are diverse and impactful across industries. As the technology advances, organizations that embrace the power of Internal GPT stand to gain a competitive edge by unlocking the hidden potential within their data.

Please contact me if you would like to learn more about how to build an Internal GPT.