DREAM: Distributed RAG Experimentation Framework

A blueprint for distributed RAG experimentation using Ray, LlamaIndex, Ragas, MLFlow & MinIO on Kubernetes Contents 1. 🌟 What is DREAM? 2. 🚶 Code Walkthrough 3. 📍 Conclusion 1. 🌟 What is DREAM? a. 🤔 What is it, really? Given... View article

Why Do We Need A Purpose-Built Database For Multimodal Data?

Recently, data engineering and management have grown difficult for companies building modern applications. There is one leading reason—lack of multimodal data support. Today, application data—especially for AI-driven applications—includes text data, image data, audio data, video data, and sometimes complex hierarchical... View article

How Tecton Helps ML Teams Build Smarter Models, Faster

In the race to infuse intelligence into every product and application, the speed at which machine learning (ML) teams can innovate is not just a metric of efficiency. It’s what sets industry leaders apart, empowering them to constantly improve and... View article

Basics of Instruction Tuning with OLMo 1B

Large Language Models (LLMs) are trained on vast corpora of text, giving them impressive language comprehension and generation capabilities. However, this training does not inherently provide them with the ability to directly answer questions or follow instructions. To achieve this,... View article

MLflow on AWS with Pulumi: A Step-by-Step Guide

Many data science and machine learning teams grapple with the challenge of effectively tracking numerous experiments and their corresponding results. Often, they resort to using cumbersome methods such as Excel spreadsheets and manual record-keeping, leading to overwhelming data management and... View article