Data Lineage

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

Hardware resources used for training/inference; constrained by memory bandwidth, FLOPs, and parallelism.

Techniques that fine-tune small additional components rather than all weights to reduce compute and storage.

PEFT method injecting trainable low-rank matrices into layers, enabling efficient fine-tuning.

Standardized documentation describing intended use, performance, limitations, data, and ethical considerations.

Structured dataset documentation covering collection, composition, recommended uses, biases, and maintenance.

Central system to store model versions, metadata, approvals, and deployment state.

Ability to replicate results given same code/data; harder in distributed training and nondeterministic ops.