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triton

Applied AI interview questions tagged triton, across every topic.

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Concepts behind "triton"

The curriculum that explains the ideas these questions test.

Core
🖥️ ML Infrastructure & ServingSign in
Model Serving FrameworksYou rarely build a serving stack from scratch; frameworks handle the production plumbing. General servers (Triton, TorchServe, KServe) serve many model types with dynamic batching, multi-model hosting, and versioning. LLM-specific servers (vLLM, TGI, TensorRT-LLM) add the essentials general servers lack: continuous batching, paged KV cache, and token streaming. Applied-AI interviews probe it because knowing what these provide, and that LLM serving needs the specialized ones, is practical deployment knowledge.
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