What Are The Foundations Of AI? | FACTS ABOUT AI | #shortsvideo #artificialintelligence #innovation

WHAT ARE 8 FOUNDATIONS OF AI? Artificial Intelligence (AI) has come a long way since its inception, and today it is considered a vital technology that has the potential to change the world. However, to truly understand how AI works, one needs to look at its foundations. There are eight foundational concepts that underlie AI, including algorithm, incompleteness theorem, computable, tractability, NP completeness, non-deterministic polynomial and probability. Algorithm refers to a set of instructions that are given to a computer to solve a problem. It is the building block of AI and is used to create intelligent machines. Incompleteness theorem is a concept in mathematical logic that states that some statements cannot be proven within a formal system. This theorem has important implications for AI, particularly in the development of logical reasoning and decision-making systems. Computable refers to the idea that a problem can be solved by a computer algorithm. This concept is the foundation of computability theory, which seeks to determine which problems can be solved by a computer and which cannot. Tractability refers to the idea that a problem can be solved in a reasonable amount of time using a computer algorithm. This concept is critical to the development of efficient AI systems. NP completeness is a concept in computational complexity theory that refers to the class of problems that are difficult to solve. These problems are particularly challenging for AI systems, and finding efficient solutions to them is an ongoing area of research. Non-deterministic polynomial is a concept in theoretical computer science that refers to the class of problems that can be solved by a non-deterministic Turing machine in polynomial time. This concept has important implications for the development of efficient AI algorithms. Finally, probability is a fundamental concept in AI that underlies many machine learning algorithms. Probability theory is used to model uncertainty and to make predictions based on incomplete data. In conclusion, the eight foundational concepts of AI are essential to the development of intelligent machines. Each of these concepts provides a unique perspective on the challenges and opportunities of AI, and understanding them is crucial for anyone interested in this exciting field. #AI #artificialintelligence #innovation #machinelearning #neuralnetworks #deeplearning #datascience #automation #robotics #bigdata #algorithms #computervision #naturallanguageprocessing #knowledgeengineering #expertsystems #cognitivescience #philosophyofmind #cybernetics #controltheory #patternrecognition #symbolicreasoning #statistics #mathematics #neuroscience #computerscience #engineering #shortsvideo