Author: Pon Sudhir Sajan

Understanding the LLM Architecture for Space Mission Modern space missions generate a large amount of heterogeneous data, including orbital products, telemetry streams, fault logs, and operational context. This requires a robust LLM Architecture for Space Mission to interpret data under strict safety and certification guidelines. Orbital Brain is a proof-of-concept (POC) architecture that combines Large Language Models (LLMs) into…

The development of generic image enhancement to intelligent, task-sensitive processing of satellite imagery is a major change in the methodology of geo-spatial analysis. Satellite images with high resolution form a core of data in modern urban planning, precision agriculture, as well as disaster resiliency schemes. However, even with all the cumulative developments in super-resolution (SR)…

Introduction: Beyond the Limits of Supervised Learning Imagine a world where AI not only mimics human summaries but also exceeds them in quality. For years, Natural Language Processing (NLP) has relied on Supervised Fine-Tuning (SFT) to train language models to replicate human-written summaries. While this method works, it has flaws and treats all errors the…

Introduction: Achieving Accurate Summarization Imagine your AI assistant confidently summarizing a 50-page clinical trial report, but including a fabricated statistic that could influence a million-dollar drug approval decision. How would you know? AI Summary Using a Typical Setup Typical AI Agent Generating Summary Traditional metrics like ROUGE focus on word overlap but fail to answer…