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The Dragon Hatchling Learns to Fly: Inside AI’s Next Learning Revolution

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Manage episode 515066225 series 3474148
Content provided by HackerNoon. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by HackerNoon or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

This story was originally published on HackerNoon at: https://hackernoon.com/the-dragon-hatchling-learns-to-fly-inside-ais-next-learning-revolution.
Exploring Brain-like Dragon Hatchling (BDH) — a new AI model that learns on the fly, adapts like a brain, and challenges the transformer era.
Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning. You can also check exclusive content about #neural-networks, #bdh-neural-architecture, #brain-like-dragon-hatchling, #inference-time-learning, #hebbian-learning-in-ai, #interpretable-ai, #modular-model-merging, #hackernoon-top-story, and more.
This story was written by: @zhukmax. Learn more about this writer by checking @zhukmax's about page, and for more stories, please visit hackernoon.com.
This article demystifies the Brain-like Dragon Hatchling (BDH), a neural architecture that keeps learning during inference using Hebbian “fast memory” while retaining pre-trained “slow” weights. BDH aims for interpretable reasoning, stable long-range behavior, modular model merging without catastrophic forgetting, and efficiency suited to GPUs and neuromorphic chips. A minimal Rust+tch proof-of-concept (XOR) illustrates the mechanics and why σ (fast memory) shines on sequence/context tasks, pointing toward practical lifelong learning systems.

  continue reading

389 episodes

Artwork
iconShare
 
Manage episode 515066225 series 3474148
Content provided by HackerNoon. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by HackerNoon or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.

This story was originally published on HackerNoon at: https://hackernoon.com/the-dragon-hatchling-learns-to-fly-inside-ais-next-learning-revolution.
Exploring Brain-like Dragon Hatchling (BDH) — a new AI model that learns on the fly, adapts like a brain, and challenges the transformer era.
Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning. You can also check exclusive content about #neural-networks, #bdh-neural-architecture, #brain-like-dragon-hatchling, #inference-time-learning, #hebbian-learning-in-ai, #interpretable-ai, #modular-model-merging, #hackernoon-top-story, and more.
This story was written by: @zhukmax. Learn more about this writer by checking @zhukmax's about page, and for more stories, please visit hackernoon.com.
This article demystifies the Brain-like Dragon Hatchling (BDH), a neural architecture that keeps learning during inference using Hebbian “fast memory” while retaining pre-trained “slow” weights. BDH aims for interpretable reasoning, stable long-range behavior, modular model merging without catastrophic forgetting, and efficiency suited to GPUs and neuromorphic chips. A minimal Rust+tch proof-of-concept (XOR) illustrates the mechanics and why σ (fast memory) shines on sequence/context tasks, pointing toward practical lifelong learning systems.

  continue reading

389 episodes

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