privacy

Coverage here centers on keeping user data under user control when working with AI systems. Expect practical takes on running models locally or in-browser so prompts and documents never leave the device, along with the tradeoffs of on-device inference versus cloud APIs. Topics include data retention, telemetry, WebGPU and edge deployment, and how to build tools that respect confidentiality without sacrificing capability or convenience.

Glowing AI brain inside a browser window above a laptop, showing local in-browser AI

in-browser-ai, webgpu, local-ai, webllm, on-device-ai, privacy

The Day the AI Moved Into Your Browser

AIpster built a Playground and Post Companion that run real language models entirely in your browser using WebGPU and WebLLM. Your prompts never leave your device, and every inference costs the site nothing.