I started off this week setting up the DeepSeek model I downloaded last week. While very interesting, after using the model and trying to find a way to prompt it to do text completion, I found that it is very much a chatbot with visible chain of thought. Therefore, we decided to stick with our original model.
I then pivoted to getting our UI set up on my computer, which required some debugging. I wanted to make sure the set up scripts were working because I plan to conduct some preliminary user testing next week. I quantified our metrics for usability, deciding on a setup time of at most 15 minutes and a benchmark of 100% success for users to reject or accept text completion suggestions, which is one of our system requirements. Finally, I worked on the design review presentation, making final block diagrams and quantifying technical design requirements.
The specified need our product will meet with consider of social factors is that it levels the playing field in terms of who has access to AI tools that support more efficient workflows for individuals. While many people can use text completion copilots to speed up their work, those working in data sensitive field cannot. This leads to a disparity across groups of who has more time to spend on more skilled aspects of their job, or more free time to spend doing other things. By enabling greater access to copilot tools, our product effectively enables greater access to better uses of time for a greater number of people.