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? PRs welcome!

The landscape of AI infrastructure 51:33 Share

Practical AI: Machine Learning, Data Science, LLM

Shownotes Transcript

The landscape of AI infrastructure