Unveiling AI Trends: Topic Modeling with BERT

Project Overview

This project delves into the evolving landscape of Artificial Intelligence (AI) research by analyzing a collection of recent academic papers. The power of the Bidirectional Encoder Representations from Transformers (BERT) model has been leveraged to perform unsupervised topic modeling on a diverse collection of AI research papers.

Objectives

• Utilize BERT to extract meaningful topics from a corpus of AI research papers.
• Generate interpretable representations of the identified topics.
• Gain insights into the current direction and potential future of AI development.

Key Topics Found:

• Bayesian
• Reinforcement Learning
• Neural Networks
• Speech Recognition
• Clustering