Generative models now write working code, produce realistic images, and hold long conversations, yet the mechanisms behind their intelligence still evade our understanding. This thesis explores that puzzle through Associative Memory (AM), an idea that emerged from physics and its concept of energy, in which patterns are stored as energy minima and retrieved through attractor dynamics.
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