Three months into building our DevOps AI agent, I gave a demo of it to the team. Checked pods, read logs, suggested fixes. Everyone was impressed. Then one engineer asked it: “Remember that ingress issue we sorted on Tuesday?” The agent had no idea what she was talking about. I had spent weeks on tool […]
Introduction Every LLM you’ve ever used is stuck in the past. It knows everything up to its training cutoff and nothing after. It also does not know about your internal documents,your private codebase,or what just happened 5 mis ago. So if you want a model to actually be useful in a real time production environment,you […]
One Database, Infinite Context: Why Your Next RAG App Should Start in SQL: The biggest challenge in Generative AI is “hallucination.” Retrieval-Augmented Generation (RAG) solves this by giving an LLM access to your private data. While most RAG stacks require complex Python “glue code,” Google Cloud’s AlloyDB AI allows you to handle the entire retrieval […]
Introduction LLMs, such as ChatGPT, have made a significant impact on the way people use technology. However, technology is far more advanced in its fundamentals as artificial intelligence indeed transforms the world. These models perform admirably in accomplishing general purpose undertakings, but when it comes to domain-specific fields such as medicine, finance, law, and engineering, […]
Introduction The chemical industry is an important part of the economy as it produces and supplies raw materials for various ingredients and use cases. There are thousands of products on the market, all of which have different compositions, technical properties, and requirements for their usage. The correct selection of products is, therefore, complicated and very […]
Introduction Generative AI (Gen AI) has revolutionized how machines generate text, code, images, and more by leveraging deep learning models. However, one of its key limitations is its reliance on pre-trained knowledge, which may become outdated or lack domain-specific insights. This is where Retrieval-Augmented Generation(RAG) comes into play. RAG enhances Gen AI models capabilities by […]
In the evolving landscape of artificial intelligence, creating AI applications that provide accurate, contextual, and reliable responses has become increasingly crucial. Retrieval-augmented generation (RAG) emerges as a powerful framework that addresses this challenge by combining the strengths of information retrieval with generative AI models. In this comprehensive guide, we’ll explore how to build a robust […]
Introduction In today’s information-driven world, delivering precise and contextually relevant search results is a critical challenge. This is where RAG (Retrieval-Augmented Generation) systems shine, combining the power of retrieval-based approaches with advanced generation models to enhance search accuracy and relevance. In this blog, we’ll explore how to build a robust RAG-based search system using a […]
