Artificial intelligence
Artificial Intelligence (AI) has evolved from a theoretical concept into a pivotal force driving technological advancement across multiple sectors. Initially motivated by the desire to emulate human intelligence in machines, AI research has spanned over 65 years, leading to breakthroughs in both theory and practical applications. The discipline draws on fields such as mathematics, computer science, cognitive psychology, neurobiology, and systems engineering. From the symbolic reasoning models inspired by Aristotle and Alan Turing’s foundational theoretical computer models to the development of neural networks and expert systems, AI has transformed how machines interact with the world and solve complex problems.
AI is now integrated into nearly every aspect of human life, including healthcare, finance, communication, transportation, and energy systems. Technologies like speech recognition, natural language processing, autonomous vehicles, and image classification exemplify its widespread applicability. The global AI market is expected to reach $190 billion by 2025, reflecting a compound annual growth rate (CAGR) of more than 36% from 2018.
Despite its transformative potential, the development of AI has not been linear. The field has experienced periods of stagnation, known as AI winters, often caused by inflated expectations, lack of infrastructure, overestimated capabilities, and underappreciation of limitations. These setbacks underscore the importance of balanced, realistic, and interdisciplinary approaches in AI development. Today, most success lies within Artificial Narrow Intelligence (ANI), as opposed to the more comprehensive and human-like Artificial General Intelligence (AGI), which remains a significant research challenge.
