Download
1 / 8
0 likes | 6 Views
Artificial Intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think, learn, and solve problems like humans. AI enables computers and software to perform tasks that traditionally required human cognitive functions, such as understanding language, recognizing patterns, making decisions, and improving over time with experience.
E N D
What is.... Artificial Intelligence?
Artificial Intelligence (AI) refers to the development of computer systems capable of performing tasks that typically require human intelligence. These tasks include learning, reasoning, problem-solving, perception, and language understanding.
Types of AI Narrow AI (Weak AI) AI designed and trained for a specific task, such as image recognition or language translation. General AI (Strong AI) AI with human-like cognitive abilities, capable of understanding and performing any intellectual task that a human can.
Components of AI Machine Learning Neural Networks Introduction to artificial neural networks, inspired by the structure and functioning of the human brain. Subset of AI that enables systems to learn from data and improve over time without explicit programming. NLP, Computer Vision, Robotics Brief descriptions of other key components contributing to AI's capabilities, including NLP, computer vision, and robotics.
AI Applications Healthcare: Finance: AI assists in disease diagnosis, personalized treatment plans, and drug discovery. AI algorithms power fraud detection, algorithmic trading, & risk assessment in financial markets. Automotive Customer Service Self-driving cars utilize AI for navigation, object recognition, and decision-making on the road. Chatbots provide automated customer support and assistance in various industries. Gaming AI opponents in video games employ adaptive strategies and behaviors to challenge players.
AI Techniques Machine Learning Deep Learning Algorithms that enable systems to learn from data and improve over time without explicit programming. Subset of machine learning using neural networks with many layers, capable of learning representations of data.
Future Trends Autonomous Systems Continued development of self-learning and self-optimizing AI systems. Human-AI Collaboration Enhancing human capabilities through AI augmentation rather than replacement. Ethical AI Increased focus on developing AI systems that are transparent, fair, and aligned with human values.
