Changelog Master Feed

The landscape of AI infrastructure (Practical AI #37)


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Being that this is “practical” AI, we decided that it would be good to take time to discuss various aspects of AI infrastructure. In this full-connected episode, we discuss our personal/local infrastructure along with trends in AI, including infra for training, serving, and data management.

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  • Featuring:

    • Chris Benson – Website, GitHub, LinkedIn, X
    • Daniel Whitenack – Website, GitHub, X

    Show Notes:

    Our locally installed stuff:

    • Jupyter
    • Docker
    • Python
    • Go
    • Postman
    • Where we see AI workflows running:

      • AWS
      • GCP
      • Azure
      • Kubernetes and KubeFlow
      • On-prem workstations:
        • NVIDIA
        • Lambda Labs
        • System76
        • Experimentation / model development:

          • JupyterLab
          • Google Colaboratory
          • AWS SageMaker
          • Data Science platforms:
            • Domino
            • DataBricks
            • DataRobot
            • H2O.ai
            • Pipelining and automation:

              • Pachyderm
              • Airflow
              • Luigi
              • Model optimization:
                • OpenVino
                • TensorRT
                • TensorFlow Lite
                • Serving:

                  • MXNet
                  • TensorFlow serving
                  • Seldon
                  • Monitoring/visibility:

                    • TensorBoard
                    • Netron
                    • Knock knock
                    • Prometheus
                    • ElasticSearch
                    • Something missing or broken? PRs welcome!

                      ...more
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