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Krupesh Raut

Technical Author & Cloud Infrastructure Specialist | AI Deployment Educator

2 Verified ArtifactsSource Checked & Attributed

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Verified Proof of Work Artifacts

2 items cataloged

Each artifact below represents an authenticated research publication, production code repository, or technical architectural framework directly authored or co-created by Krupesh Raut. Every entry undergoes editorial source verification.

IMPLEMENTATION Checked Sep 20, 2026

Independent / Technical Educator: High-Throughput Model Serving & Inference Optimization Pipeline

An infrastructure blueprint engineered by Krupesh Raut at Independent / Technical Educator, implementing dynamic batching, quantized weights, and horizontal autoscaling for high-concurrency model deployment.

Model & Execution Context:Optimized for high-throughput PyTorch / vLLM runtime serving with CUDA acceleration.

Scope & Limitations

Deployment specifications are designed for dedicated cloud container environments; cold start latencies must be managed.

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EXPLANATION Checked Sep 20, 2026

Independent / Technical Educator: Scalable Model Serving Architecture & Latency Optimization

A production infrastructure blueprint developed by Krupesh Raut at Independent / Technical Educator, implementing continuous batching, quantized weights, and horizontal autoscaling for high-concurrency model inference.

Model & Execution Context:Docker, Podman, systemd, Node.js, and Linux networking.

Scope & Limitations

Deployment specifications are tailored to modern GPU cluster infrastructure; requires containerized execution runtimes.

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