Developing and Operating AI/ML Capabilities at the Edge 2022 DoD AI/ML TEM Special Session

Abstract

What does using AI/ML at the edge mean? Common thought: Developing models in the cloud and then deploying them on edge devices. Reality is more complex: AI/ML engineering stages include:- data collection, data curation, model training, model testing, model deployment, model inferencing, etc.

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Document Details

Document Type
Technical Report
Publication Date
Oct 31, 2022
Accession Number
AD1183576

Entities

People

  • Benji Maruyama
  • Jeffrey Chrabaszcz
  • Kevin Pitstick

Organizations

  • Carnegie Mellon University

Tags

DTIC Thesaurus Topics

  • Accuracy
  • Algorithms
  • Artificial Intelligence
  • Contracts
  • Data Curation
  • Department Of Defense
  • Deployment
  • Engineering
  • Governments
  • Guarantees
  • High Pressure
  • Human-Machine Systems
  • Inference Engines
  • Learning
  • Machine Learning
  • Materials
  • National Governments
  • Software Development
  • Training
  • Universities

Readers

  • Computational Modeling and Simulation
  • Geospatial Intelligence and Artificial Intelligence Analytics
  • Maritime Combat Support and Expeditionary Logistics.