ERNIE

Ernie Logo

Inspiration

Misinformation and bias in the media is extremely prevalent in todays world, where anyone can post and publish anything on the internet. There are many individuals who listen to and cite sources that are dishonest and manipulative without realizing, and we want to guide them to better information in a polite, friendly, and informative manner.

What it does

Our web app allows the user to enter a URL to a news article, processes it and selects multiple divisive quotes using Gemini API from the article. We run them through our trained model to develop a bias score, verify and adjust the score using Gemini API, and return these to the user in an easily consumable format. Additionally, we provide them with 10 alternate, less-biased articles on similar topics for them to read instead.

How we built it

We incorporated our current knowledge base to develop a full stack web app. Individually worked on the frontend, backend, and model training for the first half of the hackathon, before collaborating to integrate it fully into a working product.

Challenges we ran into

Figuring out how to train a model was difficult, as none of us had done that before. Working with Google Cloud Services was also new for us. Figuring out a work around for uploading our model to Github as it was too large

Accomplishments that we're proud of

We managed to train our own model on a laptop using built-in GPUs. We have a product that surpasses our MVP goal. We set a viable scope for the project and completed it satisfactorily. This was the first hackathon for a few team members!

What we learned

How to train a model on pre-existing data using CUDA Learned to integrate Gemini API in unique ways other than just getting a prompt response.

What's next for ERNIE

Continue to train the model on a more extensive dataset that we weren't able to gain access to in this timeframe. Implement a google extension for this project, allowing for easier usability on the article page itself.