In the AI world, Dragon Hatchlings (often abbreviated as BDH for Brain-like Dragon Hatchlings) refer to a breakthrough "post-transformer" neural architecture that emerged in late 2025.
Unlike the standard Transformers that power models like GPT-4, Dragon Hatchlings are designed to mimic the efficiency and learning style of the human brain. Developed by researchers at the startup Pathway, this architecture is a "scale-free" model that moves away from traditional "black box" processing toward a more interpretable, biological approach.
On-the-Fly Learning: While most AI models are "frozen" after training, a Dragon Hatchling uses Hebbian learning (the "neurons that fire together, wire together" principle). It can learn and adapt during a conversation without needing expensive retraining.
Extreme Efficiency: They use sparse activation. While a typical AI might use its entire "brain" to answer a simple question, a Dragon Hatchling only fires about 5% of its neurons—similar to the energy-efficient 20-watt human brain.
The "Nest" Metaphor: In tech circles, the "Nest" is the live data framework that feeds these models. The "Hatchlings" are the specialized agents or models that emerge from that data, ready to grow and evolve.
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