Hybrid GraphRAG: Revolutionizing AI Responses with Knowledge Graphs and Retrieval-Augmented Generation

In the rapidly evolving fields of artificial intelligence and natural language processing, Retrieval-Augmented Generation (RAG) has emerged as a powerful paradigm. By combining the strengths of retrieval-based and generative models, RAG systems can leverage vast information repositories to generate highly relevant and contextually rich responses. However, as the complexity and volume of data grow, the need for more advanced techniques becomes clear. This is where knowledge graphs play a pivotal role.

April 10, 2017

AIAvengers: Harnessing Multi-Agent Networks for Intelligent Automation in Review Responses and Data Analysis

AI Avengers is an innovative project that uses multi-agent networks to automate two main tasks. It improves response generation by using Crew AI to quickly and effectively reply to customer reviews, making interactions more personal and efficient. It also boosts data analysis by turning user questions into clear, visual insights with LangGraph, helping businesses understand their data better and make smarter decisions. Response Generation: Streamlining customer review responses with Crew AI.

April 9, 2017

Face Mask Detection - ResNet, OpenCV

Many measurements have been taken to tackle the COVID-19 pandemic. Among which, wearing a face mask is one way to prevent spreading the virus. This work aims to detect if a person is wearing a mask or not. With this objective, a machine learning model is developed, which leverages transfer learning to detect mask. For collecting human faces with the mask, a subset (1000 images) of the MAFA dataset is used.