Results for "real-world testing"

A dataset + metric suite for comparing models; can be gamed or misaligned with real-world goals.

Randomizing simulation parameters to improve real-world transfer.

Combining simulation and real-world data.

Automated testing and deployment processes for models and data workflows, extending DevOps to ML artifacts.

Stress-testing models for failures, vulnerabilities, policy violations, and harmful behaviors before release.

AI systems that perceive and act in the physical world through sensors and actuators.

Artificial environment for training/testing agents.

Intelligence emerges from interaction with the physical world.

Testing AI under actual clinical conditions.

Time from request to response; critical for real-time inference and UX.

Maximizing reward without fulfilling real goal.

Control using real-time sensor feedback.

Differences between simulated and real physics.

Controlled experiment comparing variants by random assignment to estimate causal effects of changes.

Learned model of environment dynamics.

Simulating adverse scenarios.

Performance drop when moving from simulation to reality.