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What Is Artificial Intelligence? *Newspaper article - informal/semi-formal style Artificial Intelligence is the process of building intelligent machines from vast volumes of data. Systems learn from past learning and experiences and perform human-like tasks. It enhances the speed, precision, and effectiveness of human efforts. Al uses complex algorithms and methods to build machines that can make decisions on their own. Machine Learning and Deep learning form the core of Artificial Intelligence. Vast volumes of data 101001 010010 00 Learn from data Build intelligent systems Al is now being used in almost every sector of business: • Transportation • Healthcare • Banking • Retail • Entertainment • E-Commerce Now that you know what Al really is, let's look at what are the different types of artificial intelligence? Types of Artificial Intelligence Artificial Intelligence can be broadly classified into several types based on capabilities, functionalities, and technologies. Here's an overview of the different types of Al: 1. Based on Capabilities Narrow Al (Weak Al) This type of Al is designed to perform a narrow task (e.g., facial recognition, internet searches, or driving a car). Most current Al systems, including those that can play complex games like chess and Go, fall under this category. They operate under a limited pre-defined range or set of contexts. General Al (Strong Al) A type of Al endowed with broad human-like cognitive capabilities, enabling it to tackle new and unfamiliar tasks autonomously. Such a robust Al framework possesses the capacity to discern, assimilate, and utilize its intelligence to resolve any challenge without needing human guidance. Superintelligent Al This represents a future form of Al where machines could surpass human intelligence across all fields, including creativity, general wisdom, and problem-solving. Superintelligence is speculative and not yet realized. 2. Based on Functionalities Reactive Machines These Al systems do not store memories or past experiences for future actions. They analyze and respond to different situations. IBM's Deep Blue, which beat Garry Kasparov at chess, is an example. Limited Memory These Al systems can make informed and improved decisions by studying the past data they have collected. Most present-day Al applications, from chatbots and virtual assistants to self-driving cars, fall into this category. Theory of Mind This is a more advanced type of Al that researchers are still working on. It would entail understanding and remembering emotions, beliefs, needs, and depending on those, making decisions. This type requires the machine to understand humans truly. Self-aware Al This represents the future of Al, where machines will have their own consciousness, sentience, and self-awareness. This type of Al is still theoretical and would be capable of understanding and possessing emotions, which could lead them to form beliefs and desires. 3. Based on Technologies Machine Learning (ML) Al systems capable of self-improvement through experience, without direct programming. They concentrate on creating software that can independently learn by accessing and utilizing data. Deep Learning A subset of ML involving many layers of neural networks. It is used for learning from large amounts of data and is the technology behind voice control in consumer devices, image recognition, and many other applications. Natural Language Processing (NLP) This Al technology enables machines to understand and interpret human language. It's used in chatbots, translation services, and sentiment analysis applications. Robotics This field involves designing, constructing, operating, and using robots and computer systems for controlling them, sensory feedback, and information processing. Computer Vision This technology allows machines to interpret the world visually, and it's used in various applications such as medical image analysis, surveillance, and manufacturing. Expert Systems These Al systems answer questions and solve problems in a specific domain of expertise using rule-based systems Branches of Artificial Intelligence Al research has successfully developed effective techniques for solving a wide range of problems, from game playing to medical diagnosis. There are many branches of Al, each with its focus and set of techniques. Some of the essential branches of Al include: • • Machine learning: It deals with developing algorithms that can learn from data. ML algorithms are used in various applications, including image recognition, spam filtering, and natural language processing. Deep learning: It is a branch of machine learning that harnesses artificial neural networks to acquire knowledge from data. Deep learning algorithms effectively solve various problems, including NLP, image recognition and speech recognition. Natural language processing: It deals with the interaction between computers and human language. NLP techniques are used to understand and process human language and in various applications, including machine translation, speech recognition, and text analysis. • • Robotics: It is a field of engineering that deals with robot design, construction, and operation. Robots can perform tasks automatically in various industries, including manufacturing, healthcare, and transportation. Expert systems: They are computer programs designed to mimic human experts' reasoning and decision-making abilities. Expert systems are used in various applications, including medical diagnosis, financial planning, and customer service. Conclusion We might be far from creating machines that can solve all the issues and are self-aware. But, we should focus our efforts toward understanding how a machine can train and learn on its own and possess the ability to base decisions on past experiences.