Semantic Search
Search technology that understands the meaning and context of a query, not just keyword matches. Finds 'vehicle maintenance tips' when you search for 'car repair advice.'
Why it matters
Old-style search only found pages containing your exact words, so you had to guess the right keywords. Semantic search understands what you mean, which is why modern help centers, document search, and shopping sites feel smarter. It matters because you can now ask questions in natural language and still get relevant results, even when your wording is nothing like the original text.
In practice
Search a company help site for "my payment won't go through" and semantic search can surface an article titled "Troubleshooting declined transactions," even though you shared no keywords with it. It matched the meaning, not the letters. That's why searching your own notes or a big PDF library with a plain question increasingly works, instead of forcing you to remember the exact phrase you originally wrote.
Related terms
AI Dubbing
Automated translation and re-voicing of audio/video content into other languages while preserving the original speaker's voice characteristics, timing, and emotional delivery.
AI Orchestration
Coordinating multiple AI models, tools, and data sources in a unified pipeline. An orchestration layer manages prompt routing, context passing, error handling, and output aggregation across different AI services.
API (Application Programming Interface)
A way for software applications to communicate with each other. AI APIs let developers integrate AI capabilities into their own applications programmatically.
Attention Mechanism
A technique that allows AI models to focus on the most relevant parts of input data when generating output. In language models, attention determines which words in a sentence are most important for understanding each other word.
Diffusion Model
A type of generative AI that creates images by gradually removing noise from a random starting point. Powers tools like Stable Diffusion, DALL-E, and Midjourney. Works by learning the reverse of a noise-adding process.
Distillation
A technique where a smaller 'student' model learns to replicate the behavior of a larger 'teacher' model. Produces compact models that retain most of the teacher's capability while being faster, cheaper, and deployable on smaller devices.