Look up any term in AI.

Support Vector Machines (SVM)

A classifier that separates two classes with the widest possible margin, using support vectors and the kernel trick to handle non-linear data.

Disaggregated Serving (Prefill/Decode)

Disaggregated serving runs LLM prefill and decode on separate GPU pools because the two phases hit opposite limits: compute versus memory bandwidth.

State-Space Models (Mamba)

State-space models are sequence models that scale linearly with length, not quadratically like attention. Mamba's input-dependent state made them competitive.

Reinforcement Learning (RL)

How an agent learns to act by trial and error: it takes actions in an environment, earns rewards or penalties, and adjusts to maximize long-term reward.

Interconnect (NVLink, InfiniBand)

The wiring that moves data between AI chips: on-package memory, NVLink inside a server, InfiniBand between them — and why each tier is far slower than the last.

Data Processing

What happens to raw data before a model can use it: ingestion, validation, transformation, ETL vs ELT, batch vs streaming, and what silently breaks.