Hello there EchoPilot enthusiasts!

This week, our recent presentation at QRB2 shed light on the crucial role of user testing in refining our prototype. Alongside this, we’ve crafted a comprehensive pricing strategy and embarked on automation refactoring for increased efficiency.

QRB2 Feedback and User Testing Data

We recently had the opportunity to present our progress at QRB2, where we received invaluable feedback from experts. This feedback serves as a guiding light as we chart our course towards upcoming goals, ensuring that we stay on track and continually improve.

The feedback primarily focused on collecting user testing data to verify that the Large Language Model (LLM) utilized in our prototype delivers impartial, highly accurate responses and demonstrates robust generalization capabilities. Consequently, prioritizing interaction with our user community is essential, leading us to connect with both the Disability Resource Center (DRC) and students provided by coaches to gather user testing feedback. Their perspectives play a vital role in enhancing our prototype to meet the diverse needs of all users.

Pricing Strategy and Optimization

In parallel with our user testing initiatives, we’ve developed a comprehensive pricing breakdown for our most recent architecture. This breakdown serves as a crucial tool in our ongoing testing efforts, allowing us to strike a balance between accuracy and cost-effectiveness. We’re continuously fine-tuning our parameters and prompt configurations to optimize performance while keeping costs in check.

Refactoring into Automation

Looking ahead, we’ve initiated the refactoring process in preparation for automating our ingestion mechanism. By streamlining our processes and implementing automation where possible, we aim to improve efficiency and scalability, ultimately advancing the EchoPilot project to new heights.

Stay tuned for further updates as we continue our journey of innovation with EchoPilot!