Revolutionizing Email Processing: How GPT-3 and IBM Watson Discovery are Transforming Business Communication

Email processing is a critical task for many businesses, but it can also be a time-consuming and tedious process. Traditional methods of email processing involve manual sorting and responding, which can be error-prone and slow. However, with the recent advancements in natural language processing (NLP), it is now possible to automate this process using GPT-3, a state-of-the-art language model developed by OpenAI.

Research on automating email communication: https://arxiv.org/abs/2102.03062

One of the key benefits of using GPT-3 for email processing is its ability to understand the intent of incoming emails without the need for any training data. This is known as “zero-shot learning” and it allows businesses to start using GPT-3 to process their emails right away, without the need for any prior setup or training.

The first step in automating email processing with GPT-3 is to analyze the intent of the email. GPT-3 can be used to identify whether the email is an information request or a known intent. If the email is an information request, GPT-3 can define a search query for IBM Watson Discovery, a powerful AI-powered search and discovery tool, to search the organization’s internal information.

IBM Watson Discovery is an AI-powered search and discovery tool that can be used to index and search through large amounts of structured and unstructured data. It uses a combination of natural language processing (NLP) and machine learning (ML) to understand the meaning of the data and make it searchable. By indexing your organization’s internal information, IBM Watson Discovery can quickly and easily find the information you need, without the need for manual searching.

Once the search query has been defined, GPT-3 can use the search results from IBM Watson Discovery as input for the prompt. An example prompt for GPT-3 could be: “Based on the information found in IBM Watson Discovery, please provide an answer to the following question: How many units of product X were sold in the month of January?”. OpenAI’s “instruct language models” will thus be able to provide accurate information.

If the email is a known intent, then business logic can be performed. This could include tasks such as scheduling a meeting, approving a purchase order, or processing a refund. However, if the intent of the email is unclear, GPT-3 can be used to clarify the intent of the email. This can be done by asking additional questions or providing more information about the email’s context.

Once the intent of the email has been determined, all search results, results of business logic, and clarification requests can be taken as input for the prompt for GPT-3. This allows GPT-3 to formulate a response to the email that is tailored to the specific intent and context of the email.

By automating email processing with GPT-3, businesses can save time and resources while also improving the efficiency and accuracy of their email communication. Additionally, GPT-3’s ability to understand and generate natural language makes it an ideal solution for businesses of all sizes and industries.

It is worth noting that, GPT-3’s ability to understand the intent of an email can be improved by fine-tuning the model on your own email data. This can help GPT-3 to better understand the specific language, tone, and intent of your organization’s emails. Furthermore, IBM Watson Discovery, can be trained on your organization specific data and it can understand the context and concepts better.