Category Archives: AI Development

LangChain Building Intelligent and Adaptive AI Workflows

LangChain: Building Intelligent and Adaptive AI Workflows

  In today’s fast-changing era of Artificial Intelligence (AI), the need for solutions that facilitate end-to-end integration of language models and real-world applications is higher than ever before. Welcome LangChain, a powerful platform built with the aim of optimizing the use of Large Language Models (LLMs). By offering an architecture to build intelligent and adaptive Continue Reading »

Supervised Fine-Tuning (SFT) – Enhancing Model Performance

Supervised Fine-Tuning (SFT) – Enhancing Model Performance

Supervised Fine Tuning (SFT) – Improving Models for Particular Scenarios The painstaking process that is the evolution of Artificial Intelligence (AI) has yielded exceptionally complex models capable of a variety of tasks, each performed with astounding efficiency. Unfortunately, these models often lack one crucial element: versatility. This is where Supervised Fine Tuning (SFT) proves to Continue Reading »

Agentic Framework – Autonomous Decision-Making in LLMs

Agentic Framework – Autonomous Decision-Making in LLMs

  For years, Large Language Models (LLMs) have impressed us with their ability to generate human-like responses, but they’ve always had a major limitation—they react rather than act. They answer questions but don’t take the initiative, they don’t plan ahead, and they certainly don’t adapt to new information on their own. This is where the Continue Reading »

Understanding Retriev alAugmented Generation

Understanding Retrieval-Augmented Generation (RAG)

In the ever-evolving world of artificial intelligence (AI), large language models (LLMs) like ChatGPT have changed the way of interaction with technology. Their ability to generate human-like responses to a variety of questions made them revolutionary. This is where Retrieval-Augmented Generation (RAG) comes into play. RAG is a method designed to overcome these challenges and Continue Reading »