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GPU
A highly parallel processor widely used to train and run modern machine-learning models.
Inference
The process of running a trained model on new input to produce predictions, embeddings, or generated output.
KV Cache
A cache of attention keys and values used to avoid recomputing earlier context during autoregressive generation.
Knowledge Distillation
A training method in which a smaller student model learns from the outputs or representations of a larger teacher model.
Latency and Throughput
Two core serving metrics describing response delay and the amount of work a system completes over time.
Mixture of Experts (MoE)
A model architecture that routes each input to a subset of specialized parameter blocks called experts.
Quantization
A technique that represents model weights or activations with lower numerical precision to reduce resource use.
Vector Search
Search that retrieves items by similarity between numerical vector representations.