Awadb is an AI-native database built for working with embedding vectors. It is available as a public open-source repository on GitHub, where users can access the code, contribute to development, or deploy it locally on Mac OSX or Linux, or run it as a standalone service. The project is designed to support AI applications that rely on vector embedding functionality.
SVGStud.io is an AI-powered SVG generator and editor. It generates SVGs from textual descriptions and optional example images, refines them iteratively, and offers semantic search across a library of 127303 SVGs plus a gallery and in-browser editing. Generated SVGs are licensed under CC-BY-SA 4.0. Inputs are logged and generated SVGs are added to the public library.
This is an article by Amelia Wattenberger exploring creative uses of embeddings, including her development of the PenPal writing app and a sentence length highlighting tool for analyzing writing style.
Chroma is open-source search infrastructure for AI under Apache 2.0. It supports vector, full-text, regex and metadata search, built on object storage. Chroma Cloud offers serverless, scalable deployment with usage-based pricing.
Explore any niche. Discover pain points, content opportunities, and what solutions people are eager to pay for.
Archivarix Tube Search is a search engine for finding deleted, removed, and unavailable YouTube videos. It searches the Wayback Machine, Common Crawl, and other web archives to recover video metadata, thumbnails, subtitles, and links to archived video files. Users can search by channel, by video URL or ID, or full-text.
Phenaki is a Google Research model that synthesizes realistic videos from textual prompt sequences. It uses an encoder-decoder tokenizer for variable-length videos and a transformer that translates text embeddings to video tokens, trained jointly on image-text and video-text data.
Community notes
Be the first to share how this project worked for you.
Sign in with a verified account to leave a review or join the discussion.
Sign in to reviewKeep exploring
SVGStud.io is an AI-powered SVG generator and editor. It generates SVGs from textual descriptions and optional example images, refines them iteratively, and offers semantic search across a library of 127303 SVGs plus a gallery and in-browser editing. Generated SVGs are licensed under CC-BY-SA 4.0. Inputs are logged and generated SVGs are added to the public library.
This is an article by Amelia Wattenberger exploring creative uses of embeddings, including her development of the PenPal writing app and a sentence length highlighting tool for analyzing writing style.
Chroma is open-source search infrastructure for AI under Apache 2.0. It supports vector, full-text, regex and metadata search, built on object storage. Chroma Cloud offers serverless, scalable deployment with usage-based pricing.
Explore any niche. Discover pain points, content opportunities, and what solutions people are eager to pay for.
Archivarix Tube Search is a search engine for finding deleted, removed, and unavailable YouTube videos. It searches the Wayback Machine, Common Crawl, and other web archives to recover video metadata, thumbnails, subtitles, and links to archived video files. Users can search by channel, by video URL or ID, or full-text.
Phenaki is a Google Research model that synthesizes realistic videos from textual prompt sequences. It uses an encoder-decoder tokenizer for variable-length videos and a transformer that translates text embeddings to video tokens, trained jointly on image-text and video-text data.
