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The landscape of AI infrastructure (Practical AI #37)

Podcast |: Changelog Master Feed
Publisher |: Changelog Media
Media Type |: audio
Podknife tags |: Business,; Entrepreneurship,; Interview,; Master Feeds,; Software How-To,; Tech News,; Technology,; Web Development
Categories Via RSS |: Software How-To,; Tech News,; Technology
Publication Date |: Apr 02, 2019
Episode Duration |: 00:51:33

Description
Content Encoded

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.

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 – Twitter, GitHub, LinkedIn, Website
Daniel Whitenack – Twitter, GitHub, Website

Show Notes:

Our locally installed stuff:

Where we see AI workflows running:

AWS
GCP
Azure
Kubernetes and KubeFlow
On-prem workstations:

Experimentation / model development:

JupyterLab
Google Colaboratory
AWS SageMaker
Data Science platforms:
- Domino
- DataBricks
- DataRobot
- H2O.ai

Pipelining and automation:

Serving:

Monitoring/visibility:

Something missing or broken? ai-37.md">PRs welcome!

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