Discover how vector databases power AI, enhance search, and scale data processing. Learn their benefits and applications for your business with InterSystems.
including scalable type and text. For example, company and brand logos are displayed at different sizes; they show up in the corner of a mobile application or on a roadside billboard. A logo created with vector graphics can be scaled up or down without loss of quality or creating a large ...
The tool has plenty of design features, including vector editing, pixel-level editing, and powerful resizing features. Teams can also create reusable elements to save time. Meanwhile, the “styles” features help teams stay on-brand and consistent. The tool has plenty of real-time collaboration ...
bunny, rabbit, and hamster, are more closely grouped based on vector properties to each other compared to hutches. This directionality within the n-dimensional space allows neural networks to
A vector database is an advanced form of database specifically designed to handle vector embeddings, learn more here.
Similarity search, also known as vector search, vector similarity, or semantic search, refers to the process when an AI application efficiently retrieves vectors from the database that are semantically similar to a given query’s vector embeddings based on a specified similarity metric such as: Eu...
In a vector database, the vectors are typically stored along with their associated metadata, such as labels, identifiers, or any other relevant information. The database is optimized for efficient storage, retrieval, and querying of vectors based on their similarity or distance to other vectors. ...
Vector based logos designed in Illustrator and saved as AI files are clear and scalable, so they can be used in everything from a business card to a billboard in Times Square. Plus, AI is great for laying out typography that will remain crisp and legible at any size. ...
A vector database stores, manages and indexes high-dimensional vector data to be stored as arrays of numbers called “vectors,” clustered based on similarity.
This blog offers an introduction to vector search and some of the technology behind it such as vector embeddings and neural networks.