The concept of Artificial Intelligence (AI) has been around for centuries, but its modern journey began in the 1950s when Alan Turing famously investigated the possibilities of intelligent machines. Early AI research focused on symbolic AI, which aimed to represent knowledge and solve problems using logical reasoning. While this approach achieved some success, it faced limitations in handling real-world complexity.

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A significant amount of progress has been made since that time, and artificial intelligence (AI) has become a prevalent component of numerous visible and invisible tasks in daily life. The development of AI has been characterized by periods of growth and excitement coupled with stagnation phases, which are often referred to as “AI summers and winters.” This fluctuation is often influenced by cycles of government funding allocated for research.

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Since 2010, a new era has emerged, fueled by vast amounts of data and advanced computing capabilities such as machine learning and deep learning. These techniques allow machines to learn from vast amounts of data, enabling them to recognize patterns, make predictions, and generate human-like text and images. This advancement leads to a substantial surge in both research and applications related to AI.

 

Consequently, AI-based tools are increasingly entering into common usage and awareness. From self-driving cars to medical diagnosis, AI's potential is immense. In parallel, ethics and legal frameworks around AI are heavily discussed and being implemented through new regulations.