AI refers to the simulation of human intelligence in machines that can perform tasks such as learning, reasoning, problem-solving, and decision-making.
ML is a subset of AI that enables systems to learn from data patterns and improve performance without being explicitly programmed.
AI and ML are used in healthcare, finance, autonomous vehicles, customer service (chatbots), fraud detection, and personalized recommendations.
Robotics is the design and creation of robots that can automate tasks. AI-powered robots can learn and adapt to their environment, making them more intelligent and efficient.
Automation in AI refers to the use of intelligent systems to perform repetitive tasks without human intervention, increasing efficiency and reducing errors.
Predictive Analysis uses AI and ML to analyze data and predict future trends, helping businesses make data-driven decisions in finance, healthcare, and marketing.
AI can automate repetitive tasks, but it also creates new opportunities by enhancing human capabilities rather than completely replacing jobs.
Ethical concerns include data privacy, AI bias, job displacement, and ensuring that AI decisions remain transparent and accountable.
