Edge Computing
Processing data near its source on local devices or edge servers rather than in centralized cloud data centers.
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Why It Matters
AI inference is moving to the edge for speed and privacy, creating demand for engineers who can deploy and optimize AI models on resource-constrained devices at the network periphery.
How to Get Started
Experiment with edge platforms like AWS Greengrass or Azure IoT Edge, deploy a simple ML model on a Raspberry Pi or NVIDIA Jetson, and study edge-cloud architecture patterns.
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