Key idea: the economics of inference favor devices. As models get smaller and hardware gets faster, moving intelligence to the edge reduces latency and cloud spend while improving privacy.
1) Latency matters
Realtime features—voice assistants, AR overlays, robotics—feel dramatically better when inference is sub‑50ms and doesn’t cross the WAN.
2) Privacy by default
Keeping data local reduces exposure surface, simplifies compliance, and unlocks sensitive use cases in healthcare and finance.
3) Smarter caching
Hybrid patterns will dominate: coarse reasoning in the cloud, reflexes at the edge, with on‑device caches for prompts, embeddings, and policies.
What to build now
- Local voice UIs with streaming ASR/TTS
- On‑device vector search for personal knowledge
- Edge agents for IoT, inspection, and safety systems
Written by GMB Custom Software Editorial. © 2025.