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Explore a revolutionary post-Transformer AI architecture called Baby Dragon Hatchling (BDH) that addresses the fundamental limitation of current AI systems - their inability to generalize over time. Discover how this biologically inspired, scale-free network architecture overcomes the static nature of traditional Large Language Models by enabling continuous adaptation from experience. Learn about the inherent interpretability and computational efficiency advantages of BDH-based systems, and understand how this next-generation LiveAIâ„¢ paradigm delivers critical improvements in cost, efficiency, adaptability, and performance compared to existing AI architectures. Gain insights into the future of adaptive AI systems that can think and learn more like humans through this AWS re:Invent 2025 conference presentation.
