Baseline: ARTIST - Media Video AI High Level Architecture

This represents a high level architecture for a Media Video AI system.   I call it the {A}rt of {R}eporting, {T}raining, {I}nferance, & {S}tate {T}racking  or A.R.T.I.S.T. for short.    

     0. CI/CD: Jenkins Continuous integration & delivery of docker container environments.

1. Capture & Prep: Captures Video and prepares it for processing by ML
2. Model Training: Training of models to be used by Detectors.
3. HITL & Data Collection DB:  Transactional DB for managing data entry and labeling. 
4. HITL Team: Outsourced team to perform labeling and data entry.
5. Job & State Mgmt: Job Management for scheduling and running ML tasks.
6. Job & State Mgmt DB:  Transactional DB for managing processes and states.
7. Detectors: Inference Engines for detecting content in video/audio/text
8. Videos & ML Results S3 Buckets: Video, Frames Audio, and ML Detection Storage.
9. 3rd Party ML Services: Voice to Text, and other types of NLP or video detection service
10. Audience Behavior & Ratings Warehouse:  Storage and large volume processing warehouse DB
11. 3rd Party Watch Log Providers:  Watch Event log data providers & audience/critic panels
12. Gallery Data Warehouse:  Finale Data warehousing of Gallery for integration with other services
13. Gallery DB Cache:  Gallery data distributed across the world and localized to its common language 
14. Gallery UI:  Public UI for customers to view the media Gallery