Show HN: Bringing the alternative to remove.bg that are privacy and AI-first (ihatebackground.com)

A developer posted a Show HN project presenting an alternative to remove.bg that emphasizes privacy and on-device AI. The tool is free, processes images very quickly, can handle multiple images at once, and—crucially—does not upload files to a server; all background removal runs entirely in the browser so users’ photos never leave their machine. The pitch focuses on ease of use and 100% privacy, making it attractive for individuals and organizations that need immediate, local image editing without cloud exposure. For the AI/ML community this showcases the growing practicality of client-side inference for nontrivial vision tasks. Delivering fast, quality background removal in-browser typically requires model optimization (quantization, pruning), compact segmentation/matting architectures, and browser acceleration (WebGL/WebGPU/WASM or TF.js), so the project highlights advances in lightweight models and deployment tooling. It also underscores trade-offs: on-device UX improves privacy and latency but must balance model size, accuracy, and device constraints. The approach has implications for privacy-first ML products, decentralized workflows, and competitors to cloud services—encouraging more ML tools to ship fully local consumer experiences.