As ambitious high school students, we were pulled towards the idea of research papers and essays; however, we noticed that our peers were struggling to convey their projects and ideas through written research, even for professionals in advanced fields. We came to realize that this dire issue was not only targeting our communities but students and industry professionals on a tremendous scale. Evidently, we decided to develop a machine learning project that can autonomously develop essays with only input of key words, phrases, and topic. We also wanted to help generate ideas to help spark original ideas!

What it does

AI Essay Helper allows students, researchers, and professionals alike to EFFECTIVELY enhance their informative scientific research papers (academic papers in general) by utilizing the cutting edge gpt3 model along with an extensive knowledge graph extracted from a number of scientific papers. As a result of the knowledge graph containing relational data, the outputted text is easier to understand and allows the researcher to produce more quality content while limiting the amount of unnecessary information.

How we built it

In order to build this application with the limited time that we had, we split it up into numerous portions: gpt3 model training and output testing, knowledge graph creation and relational data extraction, and frontend UI for an interactive experience. To train the gpt3 model, we collected a number of research papers revolving around numerous topics within the field of deep learning (to show the model's ability to generalize) and ran a training script. In order for us to create the knowledge graph, we utilized the network and spacy library for graph visualization and part of speech extraction respectively. Once each of the individual portions was complete, we combined everything to make one smooth flowing pipeline. Everything was created using python (training gpt3, creating and extracting data from the knowledge graph).

Challenges we ran into

The main challenge we went through was connecting the backend with the frontend!

Accomplishments that we're proud of

We're proud of committing ourselves to prioritize and combating an issue that a large-scale community of researchers and students face on a daily basis. We're proud of developing a realistic solution for research and essays where instead of being succumbed to struggling to convey our findings through our own research papers and having to develop an idea, we can now efficiently allow AI and GPT-3 to develop the papers for us without killing the creativity.

What we learned

We have learned a lot during this project! This was the first time we were able to utilize the gpt3 model to create an application that benefits researchers and aspiring specialists. We also learned about integrating and transfer learning pre-trained models as well as improving our abilities to use knowledge graphs to effectively extract relational data. Finally, we learned about connecting both parts of the picture, the front end, and the backend, to create one beautiful and functional full-stack application.

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