What does "Input Embeddings" mean?
Table of Contents
Input embeddings are a way to represent words or phrases in a form that a computer can understand. When we use language in a computer, it doesn't see words like we do. Instead, it uses numbers to show the meaning of those words.
How It Works
Words are turned into vectors, which are like a list of numbers. Each word gets its own vector based on its meaning and how it relates to other words. For example, the words "cat" and "dog" might be close together in this number space because they are both animals.
Importance
Input embeddings help machines understand language better. They make it easier for computers to learn patterns and relationships between different words. This understanding is crucial for tasks like translation, answering questions, and generating text.
Advances
Recent studies show that changing how we create these embeddings can improve how well computers learn from them. New methods can reduce the amount of computer power needed to train models while still making them more effective in understanding language. This means computers can get better at tasks without needing to start from scratch every time.