<ul><li>Neural networks, often described as "black boxes," have a critical shortcoming of tightly coupled components.</li><li>Modular AI systems with loose coupling are essential for flexibility, scalability, and accountability.</li><li>Data should be stored independently, memory structures should store explicit patterns, and algorithms should act as independent processors.</li><li>By embracing modularity, AI systems can be safer, more transparent, and accountable.</li></ul>

Breaking the Black Box: Why AI Must Embrace Modularity

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