Sudhi Murthy

Current search solutions often don’t answer user questions. Instead, they return relevant links. It works well for the popular search engines, but not all data is accessible to these search engines. For example, enterprises have a lot of internal data and sometimes a poor search mechanism. We believe that search can be improved. Imagine a world where instead of using search hacks, users can frame their questions naturally like they’re talking to a system and get precise answers to their questions.

Welcome to the cutting-edge world, where artificial intelligence (AI) isn’t just a buzzword but a tangible reality shaping the future of technology. Today, we’re venturing into an exciting journey that marries the versatility of LangChain, a powerful library for building language model applications, with the robustness of Oracle Cloud Infrastructure (OCI) Data Science, a fully managed and serverless platform for data science teams to build, train, and manage machine learning (ML) models.

In the rapidly evolving field of Large language models, deploying large-scale language models effectively is crucial for harnessing their full potential. One such is the Falcon 7b model, with its extensive capabilities in natural language processing and representing a significant step forward. The Falcon 7b is a 7-billion-parameter foundational Large Language Model (LLM) that was trained on 1500 billion tokens using TII's RefinedWeb dataset.