federated learning

AI networking on Linux is becoming practical and urgent: turn on eBPF for kernel-level, per-process telemetry; build a lightweight IsolationForest detector from tshark flows and auto-throttle offenders with tc; baseline history via Prometheus and Grafana; and prep enforcement speed with OVS/DPDK and SmartNICs. Start small, wire observe–infer–act loops, and iterate toward self-optimizing, resilient fabrics.

A Linux-first guide to local AI that’s private, fast, and cost-predictable: set up Ollama for instant LLMs, compile llama.cpp for lean performance (CPU/GPU), add whisper.cpp for offline speech-to-text, and script a grep-powered RAG-lite workflow—all from Bash—plus a sizing/performance checklist and real-world uses like log triage, PR summaries, and offline field notes.