AI & ML2 min read
Building Reliable Edge AI Systems
An architectural guide on optimizing deep learning models for real-time, low-latency CPU inference on edge IoT gateways.
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Practical write-ups from building production software: optimising models for edge hardware, moving data from request to dashboard, and the trade-offs behind each decision.
An architectural guide on optimizing deep learning models for real-time, low-latency CPU inference on edge IoT gateways.
How to engineer high-throughput data ingestion, caching, and database schemas for real-time AI dashboards.
The notes explain the techniques. The case studies show them running in production.