AI is the creation of software that imitates human behaviors and capabilities. Some important tasks that are done using computers are teaching them how to learn, detecting unusual things, helping them see things like humans do, understanding human language, and discovering useful information.

Machine Learning
Machine learning is the foundation for an AI system and is used to make predictions and draw conclusions from data. Machine learning can be used to solve difficult problems, such as sustainable farming techniques. Microsoft Azure provides the Azure Machine Learning service, a cloud-based platform for creating, managing, and publishing machine learning models. Azure Machine Learning is a service offered by Microsoft Azure that allows you to create, manage, and publish machine learning models on the cloud. IT provides following features such as: automated machine learning, Azure Machine Learning Designer, data and compute management and pipelines.

Anomaly Detection
Anomaly detection is a way for computers to find unusual changes in data over time using machine learning. For example, let’s determine how we can use anomaly detection in racing cars. The anomaly detection system in the car is designed to detect any changes in the telemetry data over time. If the measurement is not within the expected range. It informs the race engineer to call the driver to stop to fix the issue before the car forces retirement from the race.

Computer Vision
Computer vision helps computers understand and interpret visual information from cameras, videos, and images. Computer Vision is an area of AI that deals with visual processing. The Seeing AI app shows how AI can help people see and understand their surroundings by describing people, text, and objects nearby. It's made for people who are blind or have low vision. Some of the common computer vision tasks include: image classifications, object detection, semantic segmentation, image analysis, optical character recognition and face detection analysis and recognition. Microsoft Azure offers several services that can assist you in developing computer vision solutions. I work with computer vision to recognize faces and forms, and I can also create custom vision solutions.

Natural Language Processing (NLP)
Natural language processing is used to interpret written or spoken language and respond in kind. NLP is a part of AI that helps software understand written and spoken language, analyze and interpret text, understand spoken language, create spoken responses, translate phrases between languages, understand commands, and decide what to do next. For example, Starship Commander is a VR game from Human Interact that uses NLP to enable players to control the narrative and interact with characters and starship systems.Microsoft Azure has NLP solutions for Language, Translator, Speech, and Azure Bot.

Knowledge mining
Knowledge mining helps to gather information from huge amounts of data that may not be organized. Azure Cognitive Search is a private, enterprise search solution that uses AI capabilities such as image processing, content extraction, and natural language processing to perform knowledge mining of documents. This helps to make previously unsearchable documents searchable and analyze large amounts of data quickly to gain valuable insights.

6 Principles of Microsoft
AI can be really helpful for the world, but we need to make sure we use it responsibly. Developers who create AI applications may face challenges and risks such as biased results, potential harm from errors, data exposure, solutions that don't work for everyone, the need for users to trust a complex system, and determining liability for AI-driven decisions. Microsoft has six principles that guide the development of their AI software. These principles aim to make sure that the AI applications solve tough problems and don't have any unintended negative effects. These are the principles for AI systems: they should treat everyone fairly, without giving an unfair advantage to any specific group based on gender, ethnicity, or other factors. The development of AI-based software should be tested and reliable. AI systems should be secure and respect privacy. AI should benefit everyone in society, regardless of physical ability, gender, sexual orientation, ethnicity, or other factors. AI-based solutions should be understandable to users and meet ethical and legal standards. Principles of responsible AI can help developers create ethical AI solutions.