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Mobile AI Assistant Offload Router (2D)

Interactive 2D simulation of the on-device vs. cloud arbitration a mobile AI assistant runs on every query: drag to pan the device/cloud map while a confidence threshold, network RTT, arrival rate and dead-zone probability trade off latency, battery and accuracy in real time.

AI & Machine Learning2DModerate60 FPS📱 Mobile-adapted⇄ 3D version

Every voice or text query a mobile AI assistant receives is first scored by a small on-device NLU model, then routed: answer locally right away, or ship it to a much bigger cloud model and wait for the round trip. This 2D simulator runs that arbitration live — a confidence threshold decides the split, a network-RTT slider stands in for WiFi vs. weak cellular, and a dead-zone slider forces local-only fallback — while a pannable/zoomable map shows each query as a glowing dot looping near the phone when it stays on-device or arcing out to a cloud icon and back when it's offloaded, backed by a live confidence histogram and rolling latency trace. Live readouts track the device/cloud split, average end-to-end latency, cumulative battery drained, and the resulting average answer accuracy, so you can see exactly how the threshold trades speed and battery life against correctness — the same cascade Siri, Google Assistant and Alexa run behind the scenes on every command.

⚙ Under the hood

Simulate the on-device vs. cloud arbitration a mobile AI assistant runs on every query on a pannable 2D map: tune a confidence threshold, network latency and dead-zone probability while a live histogram and latency trace show how they trade off speed, battery and accuracy.

AI assistantedge AImobileNLPbatterylatency

2D · HTML5 Canvas 2D · 60 FPS target · runs fully client-side, no install