As a society, it's often that we find ourselves distracted by the simplest of things. Whether its video games, Youtube, or anything in between, in this day and age, there is always something to distract you, regardless of where you look. Us personally, we're not strangers to being distracted. Even during this hackathon, we found some moments where we got distracted early on. That's why we made PrimeTime, to make sure that others can prioritize what's really necessary.
PrimeTime captures usage data and then stores all of that data into a database to categorize productivity into four separate categories. From there, PrimeTime shows you what categorizations each application you use on the daily falls under in order to help you recognize what might be productive and what might not be.
We used Python, Typescript, Javascript, Redis, Next.js, NPUs, Vectors, and LLMs, OpenVINO
The centralized timeline that showcases our data provided a challenge due to the fact that it was technically difficult to implement into a website. We also had a heavy reliance on the AI PC's where it was difficult to complete some work when we were working without them.
We are proud that we were able to find multimodal LLMs that could run efficiently on the NPU.
We learned how to utilize an NPU on an AI PC for the first time. On top of that, we learned the basics of how to implement OpenVINO.
We hope to provide more specific categorization besides just the four categories we already have established. On top of that, we want to be able to drill down into specifics, where we can gather data at a faster rate and from there, be able to different types of visualizations such as spreadsheets.