Physical AI: From Traditional AI to Intelligent Machines

Physical AI is an exciting field where artificial intelligence (AI) meets physical systems like robots and smart devices, allowing them to interact and adapt to the real world. It’s no longer just about software that processes data — Physical AI gives machines the power to think, learn, and act in physical environments, making them smarter and more useful.How AI Has Evolved Over TimeBasic AI (Rule-Based Systems)Early AI systems were built using if-then rules, where machines followed predefined instructions. For example, chatbots that answered basic questions or early recommendation systems that suggested products worked by following these rules. However, these systems struggled with complex and unpredictable situations. Agentic AI (AI Agents)As AI advanced, we moved to agentic AI — systems that could observe, plan, and take actions with more independence. AI agents, such as virtual assistants like Alexa and Siri, learn from user behaviour and adjust their responses over time. They handle more dynamic situations and automate repetitive tasks, but are still limited to software-based environments. Physical AI (Intelligent Machines)Physical AI goes one step further by integrating it into physical systems, allowing machines to make real-time decisions in the physical world. For instance, self-driving cars use sensors to detect objects, interpret traffic, and adjust their speed. Similarly, smart prosthetics with AI can predict and adapt to a person’s walking style, making movements more natural.

Physical AI: From Traditional AI to Intelligent Machines

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