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Click here to read part 1 of the post. Topics 5. Challenges with RAG 6. What can we do: Improving Data Quality 7. What can we do: Agents 5. Challenges with RAG Here are some challenges associated with implementing RAG (Retrieval-Augmented Generation). A basic RAG system tends to perform well when answering questions about specific …
The purpose of this blog is to delve into a hot topic in the world of generative AI: Retrieval-Augmented Generation (RAG). Many of you may have already built RAG systems, some of which might be in production. We’ll explore the fundamental principles behind RAG, revisiting some concepts you may already be familiar with. However, we’ll …
We will be attempting to build Neural Networks from the scratch without using any library. This being end-to-end consisting Neurons, the layers, activation functions, optimizations, back-propagations and such. The purpose is to actually learn how Neural Networks work at a very deep level so that when we go back to whatever framework we actually use, be …
Photo by Antoine Dautry on Unsplash Why Optimization? Optimization is the process of finding the best solution from a set of possible options, given certain constraints or limitations. Broadly speaking, it’s about making the most of available resources to achieve a specific goal. This goal could range from maximizing profits and minimizing costs to improving …