Rockset (acquired by OpenAI)

OpenAI is acquiring Rockset. Rockset will become part of OpenAI and power the retrieval infrastructure backing OpenAI’s product suite. We are thrilled to join OpenAI to contribute to safe, beneficial AGI! https://lnkd.in/gPviRAUK

Real-time visualizations and dashboards ➡ build these really simply using Explo and Rockset. Hang out with Sofia Jakovcevic and Annette Chen on our May 29 workshop where you'll learn about: 1️⃣ Connecting Explo and Rockset to streaming data sources 2️⃣ Real-time SQL using Rockset 3️⃣ Customizable dashboards on Explo that update as data changes See you there! 👉 https://lnkd.in/gCw9JkdV #realtime #analytics #dashboards #dataviz

Build your personal AI assistant, watch the full tutorial! 🤖💡 During our past live coding workshop, we built an app that uses the Gemini family of AI models to provide personalized furniture recommendations based on uploaded images. 🛋️📸 Additionally, we demonstrated a live example of generating video descriptions and identifying top global locations similar to your uploaded video. 🌍🎥 Learn how to leverage Rockset as a vector database to manage and query large datasets efficiently, and how to use Gemini APIs within your apps. Subscribe to our channel and watch the full workshop—link in comments! 📺 #AI #MachineLearning #Gemini #Rockset #VectorDatabase #LiveCoding #Tutorial #TechWorkshop

All vector search = hybrid search, as it drives the most relevant, real-time application experiences. 🚀 Despite the impressive effectiveness of keyword search honed over 30 years, hybrid search leverages the simultaneous use of both keyword and vector searches within the same database to deliver superior results. By blending the outputs of both search types based on algorithmic confidence, hybrid search can significantly enhance the accuracy and relevance of search results. 🔍✨ Whether your query is keyword-based or concept-driven, hybrid search adapts to provide the best possible answers. 🤖📈 Discover more about how hybrid search can elevate your search capabilities by reading Rockset's whitepaper. Link in comments. 📄🔗 #HybridSearch #VectorSearch #KeywordSearch #RealTimeData #Rockset #AI #MachineLearning #DataScience

Final talk of the day on enabling distributed transactions across microservices with #RocksDB. #indexconf

Excited to welcome the RocksDB community to #indexconf as Uber shares how they built differential backups on MyRocks

Shu Zhang discusses GPUs for #recsys. Go with what works best at any point in time. There is opportunity to move back and forth between CPUs and GPUs depending on where hardware is advancing and where the industry is trending. #indexconf

Vishal Kathuria shares about recommendations at Facebook. Given a post, predict what kind of value it will likely deliver to the user. Given the user, predict what they want. Harvested info from comments and built a model based on this. Incorporated user feedback to dramatically improve what users were being recommended. #recsys #indexconf

Jaya Kawale discusses the need to harmonize offline and online. Offline model must accurately track state of online and we need to encode the online world in a way that is reproducible both offline and online. #recsys #indexconf

Yexi Jiang sharing on the #recsys panel at #indexconf. On moving from batch to real time, user behavior changes quite often, even intra-day, so there is benefit to having more dynamic predictions for users. They first moved from offline to online inference using batch features, as their streaming platform was not as mature, but still realized gains from using request time information.