Links

Jumbo Bot Chat (requires a Tufts network connection (aside from Tufts_Guest))

• Test

• Stage

• Prod

Repositories

• https://github.com/Tufts-Technology-Services/jumbo-bot

• https://github.com/Tufts-Technology-Services/cloud-infrastructure

Overview

As we seek to improve and streamline user experiences across departments of the University, chatbots have been proposed by various departments as a means to accomplish this goal. While there are many different chatbot offerings in the market today, TTS seeks to create a single, unified chatbot in-house to serve all departments, leveraging Generative AI and Tufts internal data and systems.

Benefits

• Unified experience: Users only have to engage with one chatbot, regardless of the department they seek to engage with.

• Centralized Design/Development: The chatbot will follow a singular design pattern and set of best practices.

• Fine-tuned for Tufts: Models can be fine tuned to Tufts data and provide a more reliable/accurate experience.

• Cost Savings: Chat bots in general can yield savings by making certains roles or systems obsolete. Additionally, in-house development can yield cost savings over off-the-shelf chatbots and models.

• Time savings: Staff can spend less time on mundane, repetitive tasks, and spend more time on meaningful, interesting projects.

Risks

• Data: “Garbage in, garbage out” The training of any model hinges on accurate, high quality data in an optimal format. If a department lacks this, it can hinder development and even worse, lead to unreliable model output. Data can broken down into the following aspects:

  • Accuracy: The data for a process is accurate and up-to-date

  • Volume: There’s an adequate amount of data to train, per model requirements

  • Format: Data is in an adequate format for training

• Hallucinations: If a model lacks adequate data on a particular topic it can potentially provide false information. Tuning of model parameters (e.g temperature) can help minimize hallucinations.

• Infrastucture Costs

Technical Details

Technical details such as design, code, testing, deployment and data ingestion can be found here: https://github.com/Tufts-Technology-Services/jumbo-bot/blob/stage/README.md