Our inspiration was the recent rise of machine learning models that have swept across the internet and manifested itself in various ways. Considering the rapid improvement in the quality of these machine learning models, we thought that it would be a good idea to try to create a model that provides a social good.

What it does

Our machine learning model would be trained on academic papers, professional articles, and other reputable sources on the important topics of our time. It would then use that information to provide direct and pointed explanations of these concepts to people willing to understand, as well as attempt to answer more complex questions that skeptics may have. This could consolidate information and arguments in a way that doesn't require an advanced degree to understand, better providing knowledge and information to the masses.

How we built it

Right now, our pitch is a proof of concept, but ideally we would try to keep the project as transparent and open-source as possible. With that in mind, it would be essential to attempt to incorporate open-source machine learning/artificial intelligence libraries where we can and attempt to create the specific parts that we might need. After that, we can learn how to specialize and have our model be used for business/commercial applications, as well as compiling the training resources that we used to train our model.

Challenges we ran into

Being out of our depth with regard to execution was a big challenge. We think that the project is possible, but it would require a lot of learning about how to properly utilize and train machine learning models.

Accomplishments that we're proud of

We are proud to have been able to go in depth with our concept and present it for the hackathon!

What we learned

We learned that it is critical to have a good game plan when creating a project. Although we don't have any concrete product to present, we learned a lot about brainstorming, fleshing out ideas, presenting, and thinking about what big difference we could make in the world!

What's next for Soc[ai]l

Only time will tell!

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