Ai Picture Editor
Edit photos with prompts — no signup or watermark
What it does
AI Picture Editor turns plain-language prompts into polished photo edits in your browser. Upload a JPG, PNG, or WEBP and remove or replace backgrounds, erase unwanted objects, restore old photos, retouch portraits, create product images, apply new styles, or enhance quality. Review before-and-after results and refine them with another prompt—without layers, masks, downloads, or design skills. Guest editing is available without signup or a credit card, and every export is watermark-free.
Use our AI Picture Editor to edit photos with text prompts. Remove objects, replace backgrounds, restore old images, and download watermark-free results.
The selected resolution controls the configured credit cost. From quick background removal to complete photo restoration, turn simple text prompts into polished results with free online editing tools. Remove the background from any picture automatically — hair-level precision, no manual selection needed. Get a clean transparent PNG ready for product listings, profile pictures, or creative composites. The built-in AI Picture Editor background remover works instantly. Type a scene — "beach at sunset," "modern office," or "tropical forest" — and the AI Image Editor adjusts lighting, shadows, and perspective automatically. For catalog work, the AI Image Editor for product photos can place an…from aipictureeditor.net
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I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
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Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
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Hello HN! I found that picking out plausible but diverse skin tones for my digital art and game development projects was kind of difficult, and I got curious about if there was a way to define a color space that made it easy. I've built a color picker and procedural generation algorithm based on the space as well as a bunch of other fun js features and demos throughout the page that use the equations. If you find it interesting, I have lots of explanations of how I built it and what properties the space has. The methodology might be a bit shaky, but hopefully the result is as helpful for…
Life & fun · Aug 2026 · toneyalexander.github.io


I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
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