Containerized data center apparatus for resilient and self-contained high-performance computing at the edge

A method comprising:

• transmitting, by a containerized edge data center unit, a request corresponding to a pre-trained machine learning model, wherein the containerized edge data center unit is deployed to an edge location and configured to obtain one or more sensor data streams at the edge location;
• receiving, by the containerized edge data center unit, the pre-trained machine learning model;
• transmitting, by the containerized edge data center unit, information associated with inference using the pre-trained machine learning model and the one or more sensor data streams;
• receiving, by the containerized edge data center unit, an updated machine learning model responsive to the information, wherein the updated machine learning model is based on retraining or finetuning of the pre-trained machine learning model with the information;
• and
• performing, by the containerized edge data center unit, localized instruction tuning of the updated machine learning model to a task of the inference,
• wherein the containerized edge data center unit comprising:
• one or more cooling components;
• one or more power distribution components;
• and
• one or more compute components.