Blog
Tutorials, news and AI image generation insights from the SlyGen team.
How to Animate a Photo in SlyGen: What Works and What Breaks the Animation
How to animate a photo in SlyGen: which shots yield smooth animation and which break the result. We break down source images, prompts, and camera movements to get predictable video instead of random outcomes.
Wasting Coins? 8 Mistakes That 'Eat' Your Results and How to Fix Them
Analysis of common mistakes when working with SLYGEN that reduce generation quality and increase coin consumption. The material explains how to improve prompt structure, source images, and the approach to creating queries to achieve more stable and predictable results.
Style Logic in SLYGEN: How the Same Idea Becomes Different Visual Realities
Breakdown of SLYGEN styles and their impact on image perception: realism, anime, hentai, cartoon, cyberpunk, pinup, and fantasy. How a single prompt changes the result, amplifies emotions, and shapes different visual and psychological perceptions in AI image generation.
How to Choose a Photo for AI Animation: A Detailed Guide for Realistic Results
How to properly select photos for AI animation and video generation to maintain maximum facial similarity and achieve stable results. Key factors are analyzed: angle, lighting, image quality, and face size in the frame, as well as why neural networks distort faces with poor source material.
Realistic AI Adult Content: How the NSFW Generator Works
AI has stopped being a 'picture generation toy' and has become a tool where the result depends not on the neural network itself, but on how accurately a person can describe the scene they need. Instead of searching for ready-made content, a new model emerges — creating a personal visual experience through simple text prompts, where the key role is played by description structure, lighting, style, and composition.
AI-Powered NSFW Anime Generator in SLYGEN
NSFW anime generation with AI isn't "neural network magic" but rather working with prompts and visual logic. We break down how generation works, why prompt structure matters, which errors break the result, and how to create stable anime images in diffusion models.