AI and ML in a simple way:
Nishanth ??? ????♂?? ? ???????
Sr. Software Engineer III @ FIS Global Business Pvt Ltd | Expertise in AWS, Kubernetes, and Generative AI Engineering Specialist - #CloudMasters,#pythondeveloper,#LLM,#CostOptimization,#AIOps,#DL,and #NeuralNetworks
1. AI (Artificial Intelligence):
- AI is like a brain. Imagine it as the "thinking" part of a computer system.
- AI aims to make machines smart. It wants computers to perform tasks that typically require human intelligence, like understanding language, recognizing objects, making decisions, and even learning from experience.
- AI can use different techniques. These include Machine Learning (ML), which is one of the tools in AI's toolbox.
- AI can be broader. It covers everything related to making computers act intelligently, which includes ML and other techniques like rule-based systems and expert systems.
2. ML (Machine Learning):
- ML is like a student. It's a subset of AI that focuses on learning from data.
- ML learns from examples. Instead of being explicitly programmed, ML systems learn patterns and make predictions based on data.
- ML is great at specific tasks. It's fantastic for tasks like recognizing faces in photos, making recommendations (like Netflix suggesting movies), and even playing games like chess or Go.