Embodied AI
AI Infrastructure
Dense vector representations of data that capture semantic meaning in a form usable by machine learning models. These enable efficient processing of text images or other data types.
Detailed Explanation
Embeddings are dense vector representations that encode data—such as words, images, or other modalities—into a numerical form capturing their semantic meanings. They facilitate efficient processing by machine learning models, allowing similar items to have nearby vectors in the embedding space. This enhances tasks like language understanding, image recognition, and recommendation systems by providing meaningful, compact data representations.
Use Cases
- •Improving search relevance by matching user queries with semantically similar documents using embedding-based retrieval.
Related Terms
Other terms in the AI Infrastructure category