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Agent AI, AI, Machine Learning

Introduction to AI Agents: Architecture, Types, and How They’re Shaping the Future of Artificial Intelligence

AI Agents are intelligent systems capable of perceiving their environment, reasoning, learning, and taking actions autonomously to achieve specific goals. From personal assistants to autonomous vehicles, they mark a major shift from static AI to adaptive, goal-driven intelligence. This guide explores the architecture, types, and real-world impact of AI agents — revealing how they’re transforming industries and paving the way for the next era of human-AI collaboration.

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Azure Data Engineering, Data Analysis, Data Science, Spark SQL

Spark SQL Explained: Architecture, Catalyst Optimizer, and Key Differences from Traditional Databases

Apache Spark SQL bridges the gap between traditional SQL processing and big data analytics. Built on a distributed architecture, Spark SQL combines the familiarity of SQL syntax with the scalability of Spark’s in-memory engine. This article explores how Spark SQL works, its Catalyst Optimizer and Tungsten execution engine, and how it differs from conventional RDBMS systems. You’ll also learn about its integration with machine learning, unified data access, and use in large-scale ETL and analytics workflows.

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AI, LLM

Understanding Transformers and LLMs: The Backbone of Modern AI

Transformer Models revolutionized artificial intelligence by replacing recurrent architectures with self-attention, enabling parallel processing and long-range context understanding. These innovations laid the foundation for today’s Large Language Models (LLMs) such as GPT, BERT, and T5, which power chatbots, translation systems, and code assistants. This article explores how Transformers work, how LLMs are trained, and how they’re transforming industries through advanced natural language processing, generation, and reasoning while also addressing their challenges in bias, alignment, and energy efficiency.

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Azure, Azure Data Security

Azure Cloud Data Security: Multi-Layered Protection Explained (IAM, Encryption, and Compliance)

Learn how Microsoft Azure secures data using its multi-layered “defense-in-depth” strategy. This comprehensive guide covers identity management (Azure AD, RBAC, MFA), encryption at rest and in transit, network security, backup, threat detection, and compliance best practices for protecting cloud data.

Azure Cloud Data Security: Multi-Layered Protection Explained (IAM, Encryption, and Compliance) Read Post »

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Technology with Vivek Johari

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