{
  "patent_number": "US 10832138",
  "country": "US",
  "title": "How to Automatically Expand Neural Networks by Adding New Nodes",
  "original_title": "Method and apparatus for extending neural network",
  "summary": "A method for growing artificial intelligence models by identifying underperforming parts of a network and adding new nodes based on the behavior of existing ones.",
  "what_it_does": "This patent describes a way to make neural networks smarter by letting them grow dynamically. Instead of building a fixed-size model, the system monitors how often nodes 'fire' (activation frequency) and how consistently they behave (activation entropy). When the network hits a performance plateau, the processor identifies a specific node that needs help and adds a new one to that layer. The new node inherits some of its connection weights from the original node, while the rest are set to initial values, allowing the network to adapt to new data without starting training from scratch.",
  "what_it_does_not_cover": [
    "Does not cover static neural networks that do not add nodes during or after training.",
    "Does not cover methods of network expansion that rely on random weight initialization for all new nodes.",
    "Does not cover pruning or shrinking techniques that remove nodes without adding new ones.",
    "Does not cover hardware-specific implementations that do not use activation frequency or entropy as selection criteria."
  ],
  "filed": "2015-05-05",
  "granted": "2020-11-10",
  "expires": null,
  "status": "active",
  "holder": "Samsung Electronics Co Ltd",
  "holder_url": "https://patentbrief.org/company/samsung-electronics-co-ltd",
  "inventors": [
    {
      "name": "Heeyoul CHOI",
      "url": "https://patentbrief.org/inventor/heeyoul-choi"
    }
  ],
  "times_cited": 3,
  "tags": [
    "ai_ml",
    "consumer_electronics",
    "semiconductors"
  ],
  "abstract": "Methods and apparatus for extending a neural network, reducing its dimension and processing input data are provided. The method of extending a neural network involves selecting, with a processor, a node of a neural network, adding a new node in a layer that includes the selected node, and setting connection weights of the new node based on connection weights of the selected node.",
  "url": "https://patentbrief.org/patent/us/10832138/gpt-language-model-pre-training",
  "markdown_url": "https://patentbrief.org/patent/us/10832138/gpt-language-model-pre-training/md",
  "google_patents_url": "https://patents.google.com/patent/US10832138",
  "relatedPatents": []
}