GEES
Sketch
Figma
FigJam
Zeplin
Adobe XD
Copy.ai
Axure RP
Weaviate
Qdrant
Milvus
pgvecto.rs
txtai
Zilliz
Vespa.ai
EVA DB
GEES is an all-in-one AI design platform that is shaping a future where different design modes can seamlessly switch within the same file. In GEES (beta version), the whiteboard mode and UI design mode have already been launched, while the prototype design and graphic design modes will be launched in the near future. With AI assistance integrated into each design mode, GEES empowers users to enhance their design workflows effectively. GEES believes that such a new all-in-one era can make everyone enjoy a better design and collaboration experience. Whether you're a UI/UX designer, graphic designer, product manager, developer, or marketing manager, all your work can be unified in one file.
GEES WeaviateBased on our record, Weaviate seems to be more popular. It has been mentiond 28 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Weaviate: An open-source, cloud-native vector database built for scalable and fast vector searches. It's particularly effective for semantic search applications, combining full-text search with vector search for AI-powered insights. - Source: dev.to / 3 months ago
Weaviate is an open-source vector search engine with out-of-the-box support for vectorization, classification, and semantic search. It is designed to make vector search accessible and scalable, supporting use cases such as semantic text search, automatic classification, and more. - Source: dev.to / 4 months ago
Congrats to them! What have your experiences with vector databases been? I've been using https://weaviate.io/ which works great, but just for little tech demos, so I'm not really sure how to compare one versus another or even what to look for really. - Source: Hacker News / 4 months ago
A RAG implementation's quality and performance highly depend on the similarity-based search of embeddings. The challenge arises from the fact that embeddings are usually high-dimensional vectors, and the knowledge base may have many documents. It's not surprising that the popularity of LLM catalyzed the development of specialized vector databases like Pinecone and Weaviate. However, SQL databases are also evolving... - Source: dev.to / 5 months ago
To find semantically similar texts we need to calculate the distance between vectors. While we have just a few short texts we can brute-force it: calculate the distance between our query and each text embedding one by one and see which one is the closest. When we deal with thousands or even millions of entries in our database, however, we need a more efficient way of comparing vectors. Just like for any other way... - Source: dev.to / 6 months ago
Sketch - Professional digital design for Mac.
Qdrant - Qdrant is a high-performance, massive-scale Vector Database for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
Figma - Team-based interface design, Figma lets you collaborate on designs in real time.
Milvus - Vector database built for scalable similarity search Open-source, highly scalable, and blazing fast.
FigJam - An online whiteboard from Figma designed for teams
pgvecto.rs - Scalable, Low-latency and Hybrid-enabled Vector Search in Postgres. Revolutionize Vector Search, not Database. - tensorchord/pgvecto.rs