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CSS is going to become a programming language? 😮 Not exactly! But something very interesting is coming: There is already conditional logic available in CSS. You can apply different styling based on the viewport dimensions or other media criteria. But the syntax tends to be complex and split across multiple sections. ✨ A new if() function is coming to CSS to make this syntax more concise 🔥 within the same rule, you can apply different values based on media queries and style queries. ⚠️ This is still very much an experimental feature, supported only in Chrome and Edge. Will share more details on this in upcoming posts!

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AI Fundamentals You Should Know: 🤖📚 1. Artificial Intelligence (AI) → Technology that allows machines to mimic human intelligence like learning, reasoning, problem-solving, and decision-making. AI powers tools like Chat, recommendation systems, voice assistants, and self-driving technologies. 2. Machine Learning (ML) → A subset of AI where systems learn patterns from data instead of being manually programmed. The more quality data ML models receive, the better they become at predictions and analysis. 3. Deep Learning → An advanced form of machine learning that uses neural networks with multiple layers to process complex tasks like image recognition, speech understanding, and generative AI. 4. AI Agent → An autonomous AI system capable of performing tasks, making decisions, interacting with tools, and completing workflows with minimal human input. AI agents are becoming the foundation of next-generation automation. 5. AI Model → A trained computational system that processes inputs and generates outputs such as predictions, text, images, or recommendations based on learned patterns. 6. Training → The process where AI models learn from massive datasets by identifying patterns, adjusting internal parameters, and improving accuracy over time. 7. Inference → The operational stage where a trained AI model generates responses, predictions, or decisions for real-world use. Every Chat response is an example of inference. 8. Prompt → Instructions, commands, or questions provided to an AI system. The clarity and detail of prompts directly impact the quality of AI outputs. 9. Prompt Engineering → The skill of designing structured and optimized prompts to guide AI systems toward more accurate, useful, and context-aware responses. 10. Generative AI → AI systems capable of creating original content such as text, images, music, videos, designs, and code instead of only analyzing existing information. 11. Token → Small units of text processed by AI models. Tokens may represent words, parts of words, or symbols that help AI understand and generate language. 12. Hallucination → A phenomenon where AI generates false, misleading, or fabricated information confidently due to prediction errors or lack of verified context. 13. Fine-Tuning → The process of customizing a pre-trained AI model using specialized datasets so it performs better on specific tasks or industries. 14. Multimodal AI → AI systems capable of processing and understanding multiple data formats together, including text, images, audio, and video. 15. LLM (Large Language Model) → Massive AI models trained on huge text datasets to understand language, answer questions, summarize information, and generate human-like responses. 16. Neural Network → A computational architecture inspired by the human brain, consisting of interconnected nodes that help AI recognize patterns and make decisions. 17. RAG (Retrieval-Augmented Generation) → A technique where AI retrieves external or updated information before generating responses, improving factual accuracy and context relevance. 18. Embeddings → Mathematical vector representations of text, images, or data that allow AI systems to understand meaning, similarity, and relationships between information. 19. Vector Database → Specialized databases designed to store and search embeddings efficiently, enabling semantic search and advanced AI retrieval systems. 20. Agentic AI → Advanced AI systems capable of reasoning, planning, memory handling, decision-making, and autonomously completing complex multi-step tasks. 21. Open Source AI → AI models and frameworks publicly available for developers and researchers to access, modify, improve, and build upon collaboratively. 📌 AI Resources: https://whatsapp.com/channel/0029Va4QUHa6rsQjhITHK82y Double Tap ❤️ For More

🔅 Coding Exercises: MongoDB 📝 Practice your MongoDB querying skills with a series of code challenges thatll help you level up your CRUD expertise in MongoDB. 🌐 Author: John Cokos 🔰 Level: Intermediate ⏰ Duration: 1h 45m 📋 Topics: MongoDB 🔗 Join Web Development for more courses

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