Category: AI Models
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by Abhishek Kumar | #FirstCrazyDeveloper Back in the early 2000s, web applications faced a nightmare: SQL Injection.A hacker could type something as small as: …into a login form, and suddenly your entire user database was gone.One tiny string of text brought down million-dollar systems. 🔄 Fast forward to today… and history is repeating itself. We now…
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By Abhishek Kumar — #FirstCrazyDeveloper Artificial Intelligence is moving fast. But building an AI prototype and building a production-grade AI platform are two very different challenges. In this blog, I’ll break down how developers can architect such a system using Azure with step-by-step real-world examples. 🔑 1. Cloud Infrastructure — The Foundation Every reliable AI…
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by Abhishek Kumar | FirstCrazyDeveloper Artificial Intelligence is moving beyond static models. We are now in the Agentic AI era, where systems are not just predicting text or images but acting as autonomous problem solvers. These AI agents combine reasoning, planning, memory, and adaptability to tackle complex, real-world workflows. But what makes these agents truly agentic?The…
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by Abhishek Kumar | FirstCrazyDeveloper Building an AI Agent is not just about coding a model—it’s about creating an intelligent system that is purposeful, ethical, and continuously improving. To achieve this, the development process must follow a structured path that blends business strategy, technical design, testing rigor, and user-centered feedback loops. Let’s break down the six…
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by Abhishek Kumar | FirstCrazyDeveloper AI isn’t a one-size-fits-all solution. Different types of AI systems operate at different levels of intelligence and autonomy. Some are great at sparking creativity, some act as diligent project coordinators, and some go even further — managing the entire workflow on their own. Let’s break it down with a familiar scenario:…
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by Abhishek Kumar | FirstCrazyDeveloper In the rapidly evolving world of Artificial Intelligence, memory plays a crucial role in making AI agents more human-like, context-aware, and efficient. Just like humans, AI systems rely on different types of memory to process, store, and recall information. Each memory type serves a unique purpose, enabling AI to perform anything…
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by Abhishek Kumar | FirstCrazyDeveloper Artificial Intelligence has become a core enabler for solving real-world challenges, but the way we adapt AI models to meet our needs can vary greatly. Three of the most common strategies today are RAG (Retrieval-Augmented Generation), Fine-Tuning, and Prompt Engineering. Each approach offers unique benefits and trade-offs depending on the use…
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by Abhishek Kumar | FirstCrazyDeveloper The release of GPT-5 within Microsoft’s Azure AI Foundry marks a transformative step in enterprise AI — bringing model unification, advanced reasoning, multimodal capabilities, and real-time intelligent routing into a single cohesive ecosystem. This blog explores how organizations can strategically deploy GPT-5, GPT-5 Mini, GPT-5 Nano, and GPT-5 Chat for various…
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by Abhishek Kumar | FirstCrazyDeveloper Generative AI (GenAI) has been evolving rapidly. What started as simple text generators is now becoming intelligent, task-oriented systems that can collaborate, plan, and act. But how exactly did we get here? Let’s break it down step by step, looking at the progression from LLMs to Agentic AI—and why AI Agents…
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by Abhishek Kumar | FirstCrazyDeveloper In the rapidly evolving world of Artificial Intelligence, vector databases are emerging as the backbone of modern AI memory. From semantic search to recommendation engines, and from conversational AI to generative systems, these specialized databases are reshaping how machines store, retrieve, and make sense of information. This Vector Database Ecosystem…
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