Unique Research · Insight / product review · July 4, 2023
Chushou AI Pro (触手AI专业版) is the AI painting product of Jellyfish Intelligence (水母智能), itself incubated by LKK Innovation Design Group (洛可可). Available as an app and as mini-programs on WeChat / Douyin / Kuaishou, it aims to build a shared open creation ecosystem for model trainers, creators, and hobbyists — claiming millions of users and 100M+ AIGC works generated. This review covers the web Pro edition then in public beta at https://acgnai.com/ (Edge 114, June 2023).
Creation
Users generate images from text, images, or reference images.
Text-to-image
Enter a short keyword prompt → choose style, aspect ratio, and count → generate. UX highs: (1) broad style models — system-recommended, community-shared, and user-trained — with model stacking for niche looks; (2) post-gen actions (params, regen, variation, HD, img2img, reference, download, add to works); (3) prompt engineering with recommended positive/negative terms to lower the barrier. Friction: many styles without preview tiles — suggest sample outputs per style.
Image-to-image
Upload → “magic brush” local mask → keyword for the region → style → generate. Side-by-side original vs output and the same quick actions help iteration. Mask quality can miss expectation; algorithm/UI polish needed.
Reference generation
Reference image + text → new image. Condition options: pose, region, depth, contour strength, normal maps, line maps — strong ControlNet-style flexibility. Parameter panel sits mid-lower in the workspace (hard to find); shortcuts or a split model/params workspace would help.
Training — private models
No local GPU required: upload ≥8 images, set fast-mode params, train a private model. Training data can be local uploads or prior generated works — a clear differentiation for personalized styles.
SWOT & commercial read
- Demand: digital art / design demand + pro tools (private training, model stack) should keep pull among pros and enthusiasts.
- Moat: feature completeness and pro focus; community models + private train as sticky loops.
- Monetization: premium features, private training, community/ads/partnerships.
- Risks: crowded AI drawing market, tech shifts, shifting user expectations — continuous iteration required.
8 CN images (structure / feature screens); attach on ingest. Author Xiao Heng · Review Ski, Huajia.
— END —