Kasam Shaikh
Microsoft Azure AI Enthusiast
RAG enhances AI by retrieving external knowledge, but Agentic RAG goes further—adding decision-making and automation. Learn the key differences and why Agentic RAG is the future of AI-driven solutions.
AI Agents follow instructions, while Agentic AI operates autonomously. Discover their key differences, applications, and future impact in this insightful blog.
The rise of AI-generated content is changing how we write. But is it truly writing, or just prompting AI? Let’s explore the irony, ethics, and impact of AI-assisted content creation.
Agentic AI is revolutionizing the way AI interacts with the world. Unlike traditional AI, it autonomously plans, adapts, and collaborates to achieve goals. Learn how it works, its real-world applications, and what the future holds for this transformative technology.
Introduction Artificial Intelligence (AI) has become an essential part of our daily lives. However, with advancements in technology, newer terms…
AI agents are revolutionizing software architecture with intelligent problem-solving. Learn about ReACT, Compound AI, and dynamic automation for developers.
In today’s dynamic technological landscape, Solution Architects play a pivotal role in designing and implementing innovative solutions that drive business…
This article provides a comprehensive look at how Retrieval-Augmented Generation enhances the capabilities of Large Language Models, ensuring they remain accurate, relevant, and trustworthy in their responses.
What is RAG, Fine Tuning and RAFT (Retrieval Augmented Fine-Tuning) ?
The cloud is changing how solutions and applications are designed and secured. When building solutions for Azure it is critical…
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