Summary of Work done the week (Attach supporting Documents): Learned Docker and Kubernetes Basics: Understood containerization concepts. Practiced creating and managing Docker containers. Learned Kubernetes architecture and its components. Deployed simple applications using Kubernetes. Gained Understanding of Company Product and Utility: Attended orientation sessions. Reviewed documentation and user guides. Familiarized with the key features and functionalities of the product.
Plans for next week: Experiment with advanced features of Docker and Kubernetes. Begin exploring Large Language Models (LLMs) and their applications.
Summary of Work done the week (Attach supporting Documents): Explored LLMs and Related Concepts: Studied the architecture and working of popular LLMs like GPT-3. Understood the significance of LLMs in natural language processing (NLP). Reviewed research papers on LLM advancements. Studied Vector Databases and Embeddings: Learned about vector databases and their use cases. Explored different types of embeddings and their importance in NLP. Implemented basic embedding techniques for text data.
Plans for next week: Gain a deeper understanding of Retrieval-Augmented Generation (RAG). Research real-world applications of RAG.
Summary of Work done the week (Attach supporting Documents): Understood and Explored RAG: Studied the principles and workflow of RAG. Analyzed the benefits of using RAG in NLP tasks. Reviewed case studies and research articles on RAG applications.
Plans for next week: Investigate OpenAI, HuggingFace, and Gemini platforms. Evaluate the relevance of these platforms to ongoing project.
Summary of Work done the week (Attach supporting Documents): Explored OpenAI, HuggingFace, and Gemini Platforms: Created accounts and set up environments for each platform. Reviewed the API documentation and tutorials. Conducted initial experiments with sample datasets and models.
Plans for next week: Plan the architecture and workflow for the interactive chatbot application.
Summary of Work done the week (Attach supporting Documents): Implemented PDF-based Chat App using PrivateGPT: Designed the application architecture. Integrated PrivateGPT for generating responses from PDFs. Tested the application with sample PDFs to ensure accuracy. Developed LocalRAG Application for PDF Chat: Created a local setup for RAG. Integrated the RAG model for querying PDFs.
Plans for next week: Plan the architecture and workflow for the interactive chatbot application. Explore more efficient ways for the application.
Summary of Work done the week (Attach supporting Documents): Implemented NVIDIA NIM Models: Integrated NIM models into the project. Tested the models with various datasets. Analyzed the performance and accuracy of the models. Explored Azure Question Answering: Reviewed Azure documentation and tutorials. Conducted initial experiments with Azure's question-answering service. Evaluated the potential benefits for the current project.
Plans for next week: Optimize the performance and accuracy of the implemented solutions. Prepare a detailed report on the effectiveness and potential improvements. Plan further enhancements and new features for the applications.