{
  "patent_number": "US 12033006",
  "country": "US",
  "title": "Running AI Models Locally on Edge Devices with Cloud Updates",
  "original_title": "Edge deployment of cloud-originated machine learning and artificial intelligence workloads",
  "summary": "This patent describes a system for deploying AI models to local edge devices, allowing them to run and learn from local data, with the ability to send updates back to a central cloud for further model improvement.",
  "what_it_does": "This patent details a method where a containerized edge unit, placed at a remote location, can request and receive pre-trained AI or machine learning models from a central cloud. The edge unit then uses these models to process local sensor data, performing 'inference.' It sends batches of this inference information back to the cloud. The cloud uses this data to retrain or fine-tune the models, sending updated versions back to the edge unit. Crucially, the edge unit can then perform 'localized instruction tuning' on these updated models using its own local data store, adapting them for specific local tasks. For example, an edge unit at a factory could receive a general defect detection model, use it to analyze camera feeds of products on an assembly line, send data back to the cloud for model improvement, and then further fine-tune the model locally to recognize specific defects unique to that factory's production.",
  "what_it_does_not_cover": [
    "Deploying AI models that are not pre-trained in a cloud environment.",
    "Edge units that cannot receive updated models from a cloud management platform.",
    "AI models that are not containerized for deployment on the edge unit.",
    "Systems where the edge unit does not perform localized instruction tuning on the updated model.",
    "Edge units that do not obtain sensor data streams at their local edge location."
  ],
  "filed": "2023-09-05",
  "granted": "2024-07-09",
  "expires": "2043-09-05",
  "status": "active",
  "holder": "Armada Systems",
  "holder_url": "https://patentbrief.org/company/armada-systems",
  "inventors": [
    {
      "name": "Janardhan Prabhakara",
      "url": "https://patentbrief.org/inventor/janardhan-prabhakara"
    },
    {
      "name": "Pragyana K Mishra",
      "url": "https://patentbrief.org/inventor/pragyana-k-mishra"
    },
    {
      "name": "Anish Swaminathan",
      "url": "https://patentbrief.org/inventor/anish-swaminathan"
    },
    {
      "name": "Pradeep Nair",
      "url": "https://patentbrief.org/inventor/pradeep-nair"
    }
  ],
  "times_cited": 11,
  "tags": [
    "consumer_electronics",
    "software",
    "telecommunications",
    "ai_ml",
    "semiconductors"
  ],
  "abstract": "A process can include receiving, by an edge compute unit, a pre-trained machine learning model from a cloud management platform, wherein the edge compute unit is deployed to an edge location and configured to obtain one or more sensor data streams at the edge location. The edge compute unit can transmit one or more batch uploads of information associated with inference performed by the edge compute unit using the pre-trained machine learning model and the one or more sensor data streams. The edge compute unit can receive one or more updated machine learning models generated by the cloud management platform responsive to the one or more batch uploads of information, wherein the one or more updated machine learning models are based on retraining or finetuning of the pre-trained machine learning model with the one or more batch uploads of information.",
  "url": "https://patentbrief.org/patent/us/12033006/edge-deployment-of-cloud-originated-machine-learning-and-artificial-intelligence",
  "markdown_url": "https://patentbrief.org/patent/us/12033006/edge-deployment-of-cloud-originated-machine-learning-and-artificial-intelligence/md",
  "google_patents_url": "https://patents.google.com/patent/US12033006",
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}