Patterns of artificial intelligence and digital transformation

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Bilal Khaled El Hefnawi

Scientists usually classify artificial intelligence technology into three main types in terms of the capabilities that distinguish it and the level of imitation of human intelligence, and these patterns are: Narrow or weak artificial intelligence (Narrow AI), which is artificial intelligence that has a narrow range of capabilities, and strong or general artificial intelligence AI), which is equal to human capabilities in some jobs, and super or advanced artificial intelligence (Super AI), which is the future intelligence in which the machine’s ability is expected to exceed human capacity, as the three types are classified by their ability to simulate human characteristics, and the technology they use to do so, and its real-world applications. Narrow AI (ANI) is the only type of AI that has been successfully achieved so far. This type of AI is goal-oriented, designed to perform single tasks, and very smart at completing the specific task. out. While these machines may appear intelligent, they operate under a narrow set of constraints, terms, and conditions, which is why this type of intelligence is referred to as weak AI; It does not simulate or replicate human intelligence at all, but rather simulates human behavior based on a narrow range of criteria such as face recognition and speech recognition, as it is used in voice assistants, chatbots, and natural language processing (NLP: Natural). Language processing), and is also applied in self-driving cars (Autonomous cars), and narrow artificial intelligence systems are used today in medicine to diagnose cancers and other diseases with extreme accuracy. In our time, humans have achieved only narrow artificial intelligence. Although there is a continuation of the development of machine learning capabilities, and a continuation of research and development by scientists to reach artificial general intelligence. The second type is called artificial general intelligence (AGI) and also referred to as strong AI or deep AI, which is a concept of a machine with general intelligence that simulates Human intelligence and/or human behaviors, with the ability to learn and apply intelligence to solve any problem the system might encounter, and an AI can also think, understand, and act in a way that is indistinguishable from that of a human being in any given situation. However, artificial general intelligence is still an emerging field since the human brain is the model for creating general intelligence, and it does not seem that this will happen relatively soon due to the lack of comprehensive knowledge of the functions of the human brain. One of the main approaches to artificial general intelligence is the so-called "whole brain simulation", Where the brain’s memory and mental state are transferred to a computer, as the structure of the computer is similar to the structure of the brain because it works through a system of neurons called neural networks, so that technology can learn and form intelligent neural pathways, and also quantum computing computers with High speeds and capabilities that rely on quantum mechanics to process more data than ordinary computers, to serve as the next technological frontier to facilitate artificial general intelligence. There are various predictions about the expected time to reach artificial general intelligence, in the year 2017, the opinions of more than 350 learning experts were surveyed robotics and neuroscience and about 50% believe that will happen before 2060. Louis Rosenberg, CEO of technology company Unanimous AI, predicts that this will happen before 2060. It will happen soon around 2030, while the professor and former director of the Artificial Intelligence Laboratory at the Massachusetts Institute of Technology (CSAIL-MIT) - Patrick Winston, stated that the expected date is the year 2040. It constitutes a path to a future that not only simulates or understands human intelligence and behavior; Rather, it is the intelligence in which machines become self-aware and surpass human intelligence and ability. Also, artificial intelligence at that time develops to be very close to human feelings, experiences and capabilities, so that it not only understands them, but also raises its own feelings, needs, beliefs and desires, and super intelligence will be able to perform exceptionally and is theoretically much better in everything we do in the areas of Mathematics, science, sports, art, medicine, hobbies and emotional relationships, and will also have a greater memory and a faster ability to process and analyze data, so the decision-making and problem-solving abilities of super-intelligent beings will be much higher than the capabilities of humans. It is a basic pillar of digital transformation, and it constitutes a real support for other digital transformations such as the Internet of Things, cloud computing, big data and cybersecurity, in the rationale for using machine learning in analyzing and processing big data and extracting important and influential information in decision-making as it is used in the Internet of Things in analyzing data from sensors and make the appropriate decision, as Gartner reported in a report It was announced in November 2018 that “Artificial intelligence will be applied to a wide range of IoT information, including video, still images, speech, network traffic activity, and sensor data.” Malware that may be exposed to electronic systems so that it forms a line of defense first by intervening to protect security and privacy and detect any harmful viruses and malicious software. Artificial intelligence is also closely related to cloud computing, where artificial intelligence is integrated into the information technology infrastructure, The private and public cloud will rely on these AI tools to monitor, manage, and even self-heal when a problem occurs. According to Statista, the global value of the AI ​​market will exceed $89 billion annually by 2025. A large proportion of this value will be realized when AI supports cloud computing; Thus, cloud computing acts as a driver to increase the scope and impact that AI can have in the marketplace.