How AI is Built? | Part 2 – AI Security Engineering (தமிழில்) #cybersecurity #ai #infosec #trending

Welcome back to Bowman & Fletcher — Learn, Build & Defend! 🔐 How is an AI system actually built? What is the difference between an algorithm and a model? And how do AI, Machine Learning, Neural Networks, and Deep Learning relate to each other? In Part 2 of our AI Security Engineering series, we'll break down these concepts with practical examples and a cybersecurity perspective, explained in a natural mix of Tamil and English (Tanglish). 📚 What You'll Learn Components of an AI System — Understand data, algorithms, training pipelines, models, inference, and monitoring. The AI System Workflow — Follow the journey from training data to a deployed model. The AI Stack — Understand how the components of an AI system fit together. AI vs Machine Learning vs Deep Learning — Learn the differences and how these concepts relate. Algorithm vs Model — Understand the difference between the method used to train a model and the trained model itself. Underfitting vs Overfitting — Discover why a model can perform poorly or fail to generalize to new data. AI Security Connection — Learn why trained models are valuable assets and why protecting them matters. 🔐 Why This Matters in Cybersecurity AI security involves much more than securing a model. Data pipelines, model files, APIs, inference services, and monitoring systems can all introduce security risks. This is part of our ongoing AI Security Engineering series, where we build a strong foundation before exploring AI attacks, vulnerabilities, and defensive techniques. 👍 If you find this video useful, like, share, and subscribe! 🔔 Subscribe to Bowman & Fletcher for practical cybersecurity tutorials, AI security, SOC engineering, threat hunting, and hands-on labs. #AISecurity #ArtificialIntelligence #MachineLearning #DeepLearning #AISecurityEngineering #TamilTech #Tanglish #BowmanAndFletcher