1. Machine Learning: This is the most common technique used in AI. It involves training a model using large amounts of data and then using this model to make predictions or decisions without being specifically programmed to perform the task.

2. Deep Learning: This is a subset of machine learning that makes the computation of multi-layer neural networks feasible. It is responsible for advances in image and speech recognition.

3. Natural Language Processing (NLP): This is a branch of AI that focuses on the interaction between computers and humans through natural language. The ultimate objective of NLP is to read, decipher, understand, and make sense of human language in a valuable way.

4. Cognitive Computing: This approach aims to simulate human thought processes in a computerized model. It involves self-learning systems that use data mining, pattern recognition, and natural language processing to mimic the way the human brain works.

5. Robotics: This involves creating machines that can substitute for humans and replicate human actions. Robots can be used in many situations and for lots of purposes, but today many are used in dangerous environments, manufacturing processes, or where humans cannot survive.

6. Computer Vision: This is the science that aims to give a similar, if not better, capability to a machine or computer. Computer vision is concerned with the automatic extraction, analysis, and understanding of useful information from a single image or a sequence of images.

7. Expert Systems: These are computer systems that mimic the decision-making ability of a human expert. Expert systems are designed to solve complex problems by reasoning through bodies of knowledge, represented mainly as if–then rules rather than through conventional procedural code.

8. Speech Recognition: Interacting with technology by speaking to it is becoming increasingly prevalent. This involves teaching a computer to understand spoken language.

9. Biometrics: This technology can recognize, measure, and analyze human behavior and physical aspects of the body’s structure and form. It allows for more natural

Question

1. Machine Learning: This is the most common technique used in AI. It involves training a model using large amounts of data and then using this model to make predictions or decisions without being specifically programmed to perform the task.

2. Deep Learning: This is a subset of machine learning that makes the computation of multi-layer neural networks feasible. It is responsible for advances in image and speech recognition.

3. Natural Language Processing (NLP): This is a branch of AI that focuses on the interaction between computers and humans through natural language. The ultimate objective of NLP is to read, decipher, understand, and make sense of human language in a valuable way.

4. Cognitive Computing: This approach aims to simulate human thought processes in a computerized model. It involves self-learning systems that use data mining, pattern recognition, and natural language processing to mimic the way the human brain works.

5. Robotics: This involves creating machines that can substitute for humans and replicate human actions. Robots can be used in many situations and for lots of purposes, but today many are used in dangerous environments, manufacturing processes, or where humans cannot survive.

6. Computer Vision: This is the science that aims to give a similar, if not better, capability to a machine or computer. Computer vision is concerned with the automatic extraction, analysis, and understanding of useful information from a single image or a sequence of images.

7. Expert Systems: These are computer systems that mimic the decision-making ability of a human expert. Expert systems are designed to solve complex problems by reasoning through bodies of knowledge, represented mainly as if–then rules rather than through conventional procedural code.

8. Speech Recognition: Interacting with technology by speaking to it is becoming increasingly prevalent. This involves teaching a computer to understand spoken language.

9. Biometrics: This technology can recognize, measure, and analyze human behavior and physical aspects of the body’s structure and form. It allows for more natural

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