ML DevOps


Enterprises invest in AI development often face the following challenges

  • Multiple heterogeneous resource requirements
    • Server, GPU, Object storage, File storage
  • Complex software components
    • Big Data
    • Machine Learning
    • Web Services
  • Different professional expertise departments
    • Data Scientist
    • AI Scientist
    • IT Operations
  • Leading to each department having its own process data
    • Operational Silos

Gemini ML DevOps Solution Advantages

  • Support multiple Raw Data formats
  • Quickly and automatically create the computing environment required for AI/ML
  • Flexibility to adjust the computing resources required for each ML project
  • AI training data will be storing and sharing in the cloud
  • Continuous training and improving AI inference model