Results for "deployment"
Shadow Deployment
IntermediateRunning new model alongside production without user impact.
This approach lets developers test a new version of a model alongside the current one without anyone noticing. Imagine a restaurant trying out a new recipe while still serving its regular menu. Customers don’t see the new dish, but the restaurant can gather feedback on how it performs. In the tec...
Coordinating models, tools, and logic.
Assigning AI costs to business units.
Startup latency for services.
Running models locally.
Performance drop when moving from simulation to reality.
Requirement to reveal AI usage in legal decisions.
International agreements on AI.
Restricting distribution of powerful models.
Risk threatening humanity’s survival.
Training a smaller “student” model to mimic a larger “teacher,” often improving efficiency while retaining performance.