AI Excels in Small Domains

max prehoda - Jun 6 - - Dev Community

When it comes to AI, the average user often thinks of large language models like ChatGPT or Claude AI that are trained on vast amounts of data across a wide range of domains. While these models are incredibly impressive in their ability to engage in open-ended conversations and tackle a variety of tasks, they can sometimes struggle with hallucinations or inconsistencies when dealing with highly specific or niche topics.

This is where AI trained on smaller, focused domains truly shines. By narrowing the scope of training data to a specific area, such as CSS animations and transitions, AI models can become extremely proficient and efficient at generating accurate and creative solutions within that domain. The limited syntax and well-defined rules of CSS animations make it an ideal candidate for AI specialization.

I recently had the opportunity to put this concept to the test by building an AI model specifically trained on CSS animations and transitions. Initially, I experimented with the Claude API and found that it performed quite well in generating animations. However, the real magic happened when I switched to a self-trained AI model running locally. The results were very impressive.

The locally trained AI model demonstrated an incredible ability to generate complex and visually stunning CSS animations with ease. It had a deep understanding of the syntax, timing functions, and various properties involved in creating smooth and engaging animations. The model's outputs were not only technically accurate but also showcased a level of creativity and innovation that surpassed my expectations.

The new model is going live today @ aicssanimations.com

Try it out for yourself and feel free to give feedback!

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