The goal is to provide an interactive tool for visualizing research papers in a 2D map where the papers are placed on the map based on some vector embedding of the summary. The papers that are similar to each other will cluster together. This will allow researchers to identify papers that have similar concepts and even allow users to look at concepts from different fields that are applicable in their own field.
Transformers are context-learning neural networks. They learn by tracking relationships in sequential data, for example, words in sentences. You might know them as some of the best AI models in the market - OpenAI’s GPT-3 and Cohere In our 3-day Hackathon, organized along with the Swiss AI Association, you’ll use context-learning neural networks to build solutions with people from all around the globe and have an opportunity to pitch your AI Prototypes worldwide. Jump in to learn more about harnessing the power of Transformers!