Edge AI

Edge AI

Edge AI is the deployment of AI models on local devices near users, sensors, or machines rather than relying entirely on remote cloud inference [src-117].

Key points

  • Google's Coral Board demo shows compact Gemma models running on a small on-device AI board with a local accelerator [src-117].
  • The edge signal matters when the AI workflow uses cameras, microphones, low-latency interaction, private data, or offline execution [src-117].
  • Edge AI overlaps with Local Frontier AI, but it emphasizes smaller embedded devices rather than only laptops, desktops, or local GPU boxes.

Related entities

Related concepts

Source references

  • [src-117] Google for Developers – "Run Gemma on the edge with the Coral Board" (2026-06-15)

Robin Cartier perspective

This page is part of Robin Cartier's working AI knowledge graph: a practical research layer for production AI, recommendation systems, experimentation, GEO, and agentic web readiness.

The useful next step is to connect this concept back to applied product leadership and operating models.

Recommended next

Keep reading from this thread

From 491 indexed pages and articles.

  1. Wiki concept Coral Dev Board Represented here by Google's official demo of running Gemma locally on a small on-device AI board with a Coral Related by 117
  2. Wiki concept Gemma Google's open model family represented here by the Google for Developers demo of running Gemma locally on Coral Board hardware [src-117]. Related by 117
  3. Insight AI Measurement and Experimentation How to measure AI product impact with evals, adoption metrics, online experiments, guardrails, and cost tracking Related by offline