What we learned
Artificial intelligence systems ingest large amounts of labeled training data, analyze the data for correlations and patterns, and use these patterns to predict future states. If a chatbot is fed examples of text messages, it will learn to produce lifelike exchanges with people, or an image recognition tool will learn to identify and describe images by reviewing millions of examples. There are four types of artificial intelligence 1- Reactive machines. During the 1990s, Deep Blue defeated Garry Kasparov. The Deep Blue algorithm can identify pieces on a chessboard and make predictions, but because it has no memory, it cannot use past experiences to inform future decisions.
2: Limited memory. These artificial intelligence systems are capable of learning from their past experience to make future decisions. In self-driving cars, some of the decision-making functions are designed in this way.
- Theory of mind. This is a psychology term. If applied to AI, it means the system will be able to understand emotions. In order for AI systems to become integral members of human teams, they need to be able to infer human intentions and predict behavior.
4- Self-awareness. These AI systems possess a sense of self, which gives them consciousness. Self-aware machines recognize their own situation as it is. Such AI does not yet exist.
##Examples of AI technology
Automation. Combined with AI technologies, automation tools can increase the volume and types of tasks performed. RPA, Machine learning. The science of getting a computer to act without programming. In very simple terms, deep learning can be described as the automation of predictive analytics
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