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.
Why it matters
Big models are accurate but slow and expensive to run. Distillation lets companies capture most of that quality in a model small enough to run on a phone, a laptop, or a cheap server. That's why you can now get useful AI responses instantly and often for free. Many of the fast, low-cost models you compare on aggregators started as distilled versions of a heavyweight teacher.
In practice
Suppose a company has a giant model that answers customer questions brilliantly but costs too much to run at scale. They train a small student model on the big model's answers to thousands of questions. The student learns to mimic those responses closely. Now it handles routine support tickets at a fraction of the cost, and the expensive teacher is reserved only for the trickiest cases.
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.
Embedding
A mathematical representation of text (or images) as a vector of numbers that captures meaning. Similar concepts have similar embeddings, enabling semantic search and clustering.