Unum
@unum_cloud
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Scaling Intelligence. Rebuilding the Cloud: From Storage to Compute to AI. Across Search, Numerics, & Modeling. https://t.co/URCKuqxKYE
San Francisco
Joined December 2020
USearch adoption is snowballing — well beyond ClickHouse, DuckDB, YugaByte, TiDB & ScyllaDB open-source gurus and the vector search use-case to the contents of slide 41 of this 2023 lecture and further! So many ways to exploit just a few thousand lines of C++ templates ⚛️
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USearch is getting close to earning the title of "SQLite of Search" 🥳 After C++11, C99, Python, Rust, JS, Java, Obj-C, Swift, C#, Go, Wolfram, Kotlin, and Clojure — @ZigLang becomes the 14th language with @unum_cloud USearch binding ⚡️ Check out Adib's repo for details 👇
Usearch was missing a @ziglang binding so here you go, have fun building blazingly fast vector database systems on your own in zig. https://t.co/a7XT5MHdEr
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Genome sequencing is advancing faster than Moore’s Law. Great for personalized medicine — but we can’t just keep adding compute. New algorithms & hardware-friendly libs are needed! Our story with @unum_cloud & @nebiusai on porting StringZilla to GPUs: https://t.co/eXt3pWcOXf
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Powered by our MLOps-tailored AI Cloud, @unum_cloud optimized an open-source string processing library StringZilla with hardware-specific kernels to efficiently leverage GPU parallelism at the software layer. Read the full story: https://t.co/ROjUaM4Z4L
#StringZilla #Strings
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The 26-year-old Apache Lucene is my worst nightmare. It’s arguably one of the world’s top 3 search engines — powering Elastic, Solr, MongoDB Atlas, AWS OpenSearch, and Azure Cognitive Search. Alongside Meta’s FAISS and (my) @Unum_Cloud’s USearch — the younger successors. So yes,
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Although most of our open-source libraries focus on in-memory processing, truly large-scale processing typically begins in external memory. Here's a glimpse from 2022 into what has been in the works for quite some time and will hopefully be available to everyone 🔜
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USearch everywhere 🎉 @Unum_Cloud 🤝 @Yugabyte
As vector search becomes foundational to modern #AI workloads, databases must rethink how their architecture handles high-dimensional vector data at scale.🤔 This new blog from @Yugabyte expert Sandeep Lingam reveals how #YugabyteDB integrates a distributed vector indexing
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Higher recall + Python, JS, & Swift fixes🎉 Entirely community-driven - I did nothing 🤗 Upgrade to USearch v2.17.8 today 😉 https://t.co/B3r5bkAJlW
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For everyone using @unum_cloud USearch For <1B vectors per index you should aim for >100K insert & search queries/second with reasonable accuracy on 1 node 100M vecs ~ 20 mins I’ve met several AI labs, using it and not realizing its 10x faster 😉
With this, building a FAISS HNSW index on GPU is as fast as ... building a Usearch HNSW index on CPU? H/t @ashvardanian
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One more DBMS project leveraging @unum_cloud USearch for Vector Search 🥳 https://t.co/5wGq8LBwY4
github.com
Fast Open-Source Search & Clustering engine × for Vectors & Arbitrary Objects × in C++, C, Python, JavaScript, Rust, Java, Objective-C, Swift, C#, GoLang, and Wolfram 🔍 - unum-cloud/USearch
By leveraging #Scylla's scalability and USearch library's performance, we designed a system with exceptional query latency and throughput. In 15 min., Szymon Wasik will cover vector search use cases and compare our implementation with vector databases. https://t.co/auaAvL2DY8
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20 million Python downloads across SimSIMD, StringZilla, and @unum_cloud USearch 🎉 If you’re chasing performance, upgrading to Ubuntu 24.04 LTS is worth it — modern Linux kernels, compilers and improved SIMD intrinsics support make a huge difference! https://t.co/dhIxDGnLqS
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Thanks to @PingCAP for trusting @unum_cloud USearch, opening a PR, and mentioning their project involvement! Are there any other DBMS, AI, and Cloud companies that should be mentioned? https://t.co/jM9u49xW8I
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Your pocket device is much more powerful than you know! Together with our partners at @TheStageAI, we've accelerated the inference time of our UForm models by 5x, reaching only 0.5 ms for multimodal retrieval pipelines... locally, without exposing your privacy! Details 👇
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Rewinding to 2022... We shared our first major public talk on Linux kernel bypass & GPU-accelerated ACID-transactional storage — the result of 7 years of R&D. We hit 1M transactions per SSD and scaled linearly to 24 drives! 🎥 Watch now:
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Tech conferences come and go, but Unum is here for the long run! We’re preserving some of the most impactful talks by re-uploading them to our official YouTube channel. Starting with "Vector Search and Databases at Scale" from 2023. 🎥 Watch now: https://t.co/yfuu2rfTST 🧵
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