An AWS AI service already does your task well. What should guide build or use?
Why C is the answer
Cost, effort and how well it meets the need
The choice depends on cost, effort and how well a managed service meets the need.
In detail
- Weigh cost, effort and how well it meets the need.
- Measure quality on your own data first.
Use case
An illustrative scenario, not a real incident.
A team could build a sentiment model, but an AWS service already does it well at lower cost and effort.
See it in different ways
mindmap
root((SageMaker AI))
Data
Data Wrangler
Ground Truth
Clarify
Train
JumpStart
Automatic model tuning
Debugger
Deploy
Pipelines
Model Registry
Operate
Model Monitorflowchart TD
Q{"Does a managed service meet the need?"}
Q -->|"Yes, at fair cost"| A0["Use it"]
Q -->|"No"| A1["Build a custom model"]Key point: Weigh cost, effort and fit.
Why the other options are wrong
- A. The number of engineers who enjoy training models
- Enjoyment is not a reason.
- B. The newest research paper on the subject
- A new paper does not decide this.
- D. Whether a custom model sounds more impressive
- Impressiveness is not a reason.