Smart Glasses AI Configurator

Design your personal AI assistant for wearable glasses. Balance capability, privacy, battery, and latency in real time.

Presets

Glasses Preview

Ready
Configure your assistant to see the preview
Select use cases and configure your assistant to begin.

How It Works

Use Cases Drive Requirements

Each use case (navigation, translation, meeting notes, etc.) requires specific sensors and model capabilities. Select your priorities and the configurator computes the minimum viable configuration.

Model Tier vs. Inference Mode

Tiny/Small models run fully on-device for privacy and latency. Medium/Large models need cloud for quality but increase latency and reduce privacy. Hybrid mode routes simple queries locally, complex ones to cloud.

Battery Life Estimation

Base: 8 hours. Each sensor adds drain. Local inference uses NPU efficiently; cloud inference saves compute but adds radio usage. Estimates are approximate—real world varies by temperature, signal, and workload.

Privacy Score

100 = fully local, no cloud, auto-delete, no training. Deductions: cloud inference (-30), no auto-delete (-15), training opt-in (-10), cloud sync (-5). Score guides but doesn't guarantee compliance—review your org's policies.

Export & Portability

The JSON spec captures every setting. Import it into another session, share with your team, or feed it to a provisioning pipeline. No account required—everything runs in your browser.

Source & Assumptions

Inspired by Meta's Connect 2024 keynote announcing Muse on AI glasses. Specs are illustrative: real hardware varies. Battery models reference public Snapdragon AR2 / AR1 data. Latency assumes 5G/edge for cloud. No proprietary Meta data used.

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