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Real-time Processing

Visual diagram · (in preparation) · Math · (in preparation) · Worked example · 3 difficulty levels.

TL;DR. Handling data and producing results within strict latency bounds, often milliseconds.

Technical Definition

Handling data and producing results within strict latency bounds, often milliseconds.

How it works

Real-time ML powers fraud detection, ad ranking, recommendation, and live transcription. It demands low-latency feature stores, efficient models, and robust monitoring. Often paired with offline batch jobs that retrain models on accumulated data.

Related Concepts

  • Latency — The time between sending a request and receiving the first (or final) response.
  • Streaming — Returning model output incrementally — token by token — as it is generated.
  • Offline Processing — Computing predictions or transforming data in batches, without strict latency requirements.