<![CDATA[Advancements in the field of Artificial Intelligence (AI) have led to the development of systems capable of ef iciently solving various complex tasks. However, behind these achievements lie significant theoretical challenges that limit AI's capabilities. This article discusses the primary limitations of AI, including computational complexity, dif iculties in generalization, knowledge representation constraints, and challenges related to bias and ethical implications. Furthermore, it explores opportunities arising from these limitations, such as the development of hybrid models, energy-ef icient approaches, and improved algorithm interpretability. By examining these challenges and opportunities, this study aims to provide deeper insights into the future direction of AI development. An interdisciplinary approach is proposed as the key to addressing theoretical challenges and responsibly expanding AI's potential.]]>
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