Optimizing RAG Systems: A Deep Dive into Chunking Strategies.

When it comes to today’s AI systems, especially in Generative AI, the main challenge isn’t just building a basic system with, say, 70% accuracy—it’s about pushing that system to over 90% and making it reliable for real-world production. Optimizing RAG (Retrieval-Augmented Generation) systems is essential for reaching this level. Effective chunking, one of the foundational … Continue reading Optimizing RAG Systems: A Deep Dive into Chunking Strategies. →

GPU vs CPU: Understanding Their Differences and Benefits for AI Processing

A lot of the buzz is around GEN AI from the last couple of years. The focus on GPU has increased significantly. Building a good understanding of why we need each and when is essentially to build our foundational understanding. So let's dive in. We will start by looking at the theory of both, then … Continue reading GPU vs CPU: Understanding Their Differences and Benefits for AI Processing →

RAG Components – 10,000 ft Level

When you look at GEN AI and specifically LLM's from a usage point of view, we have a few techniques to interact with LLM's. This depends on whether you need to interact with external data or just use LLMs for your different tasks. RAG is an important technique and widely adopted because it helps you … Continue reading RAG Components – 10,000 ft Level →

Evaluation and Experiment Tracking for LLM’s

Have you ever done text generation with an LLM and though: I wish I could track experiments and evaluate different LLM results in terms of cost, sample comparison and memory together like below? If yes this article for you. Experimentation tracking is one critical piece of model development which is very important as it helps … Continue reading Evaluation and Experiment Tracking for LLM’s →

AI COST IN PRODUCTION

Have you ever pictured AI in production to be like this below? AI system is not just ml code but a lot of other components. And the decision to either productionize of not productionize a system depends on a lot of factors outside model accuracy.Cost to build and maintain the entire system in production is … Continue reading AI COST IN PRODUCTION →

Big Data Engineer vs Machine Learning Engineer vs Data Scientist- Questions that helped me choose…

Well, this is actually something quite interesting. And I am sure a lot has been said about these roles on the web and this post is mostly for folks who just started out or are starting, and generally, there are three sorts of people:Geetha: Geetha is Someone who is already in the field looking to … Continue reading Big Data Engineer vs Machine Learning Engineer vs Data Scientist- Questions that helped me choose… →