Cold Start
The response latency that occurs when an AI system is launched from an inactive state, or the phenomenon in recommendation systems where accurate results cannot be provided to new users due to a lack of data.
Detailed explanation
Why It Matters in Tool Selection
Cold start determines the 'first impression' of a service. If model loading is slow, users leave, and if irrelevant recommendations are provided to new users, service trust drops. Therefore, for services with frequent large-scale traffic or influx of new users, the ability to control cold starts is a key criterion for tool selection.
What to Look For
- Does it provide 'always-warm' or provisioned concurrency capabilities in a serverless environment?
- Does backup logic based on popularity or metadata activate when new users/items occur?
- Is runtime lightweighting and dependency optimization supported during model deployment?
Example
Showing 'most popular content' first to a newly registered user because they have no viewing history is a response to a data cold start, whereas an image generation AI model that was dormant during dawn hours taking over 10 seconds to respond to its first request is an example of an infrastructure cold start.