Welcome to the community! This is a space for builders, consultants, and career-changers who are serious about mastering AI systems with security-first thinking. Whether you’re already implementing AI workflows or just starting your cybersecurity journey, you’re in the right place. 👇 Comment below and tell us: - Where you’re from - What you’re currently building or learning - What you’re hoping to master here Can’t wait to learn and grow together 💡

Hey everyone, do post your intro and what you do so we can make sure we have the right audience and the contents we will create will be aligned.

If you're diving into the world of AI or implementing AI for companies, embrace best practices right from the start to avoid the pitfalls! Here are a few key pointers to keep you on the right track: 🤖 Data is King - Ensure you have quality, diverse datasets to avoid biases. Garbage in, garbage out, as they say! 🔐 Ethical Responsibility - Be transparent about your AI's capabilities and limitations. Don't overpromise and underdeliver. 👥 Cross-Disciplinary Teams - Combine tech experts with domain specialists for a well-rounded approach to problem-solving. 🔄 Continuous Learning - AI isn't a set-it-and-forget-it deal. Constantly train and retrain your models for accuracy. 🌐 Security & Privacy - With great power comes great responsibility. Protect user data like it's your own. Adopt these best practices, and you'll be well on your way to AI success! 🚀 #AI #BestPractices #MachineLearning #DataScience #EthicalAI

AI can automate almost anything—but if we don’t secure it, we create more problems than we solve. So here’s a challenge: Pick one small AI process you’ve implemented (or plan to) and map out what could go wrong. ✅ Could someone spoof the inputs? ✅ Is data encrypted at rest and in transit? ✅ Does it log activity for review? Then… share your answers below. I’ll be here giving feedback and suggestions 💬 Let’s get used to thinking like builders AND defenders.