Superlinked

The future of #softwareengineering in the era of #GenAI according to Guy Podjarny - “Code will mostly disappear, and devs will need to touch it only in special cases, similar to assembly today. SWEs will take a more architectural role” ?? Thanks GV (Google Ventures) for a cool event ????

Superlinked continues to grow, and it might be your (or your friend's) opportunity to join the rocket-ship ?? Are you excited about the future of AI, have a technical background and love closing deals? ?? We are looking for an energetic salesperson to join the team, help build our sales motion and bring the next-gen information retrieval infrastructure to more enterprise customers?? Ready to make your mark in the AI landscape? Check out the full job description and apply here: https://lnkd.in/eHukffPX Let's build the future together! ?? #recruiting #jobpost #salesjob

In this quick breakdown, we tackle problem no 2 with vector search: handling OCR for complex docs. When support agents need to find specific parts in technical manuals with diagrams, traditional vector search falls short. Why? Standard OCR extracts text but loses critical spatial relationships between parts in technical diagrams. When your support team needs to identify "where is the burner located?" in a complex manual, the relationship between components matters! The solution? Superlinked offers an elegant solution to this structural problem, preserving the relationships between components that make support agents actually useful. But that's not all - we also address the growing complexity of vector search infrastructure. DM us to learn more, or visit docs.superlinked.com to try it out yourself! #VectorSearch #AISearch #OCR #Agents

In this quick breakdown, we tackle problem no 2 with vector search: handling OCR for complex docs. When support agents need to find specific parts in technical manuals with diagrams, traditional vector search falls short. Why? Standard OCR extracts text but loses critical spatial relationships between parts in technical diagrams. When your support team needs to identify "where is the burner located?" in a complex manual, the relationship between components matters! The solution? Superlinked offers an elegant solution to this structural problem, preserving the relationships between components that make support agents actually useful. But that's not all - we also address the growing complexity of vector search infrastructure. DM us to learn more, or visit docs.superlinked.com to try it out yourself! #VectorSearch #AISearch #OCR #Agents

How Embeddings and Clustering Reduced File Understanding Time by 96% ?? A case study from Dropbox. ???? Reading through entire documents to extract key information is time-consuming and inefficient. ?? Dropbox aimed to automate and accelerate this process. Dropbox's engineering team introduced AI-powered summaries and Q&A for file previews. This solution works in two phases ???: ?? Phase 1: Text Extraction and Embedding? ? Riviera converts any file type into text? ? Text is split into paragraph-sized chunks? ? Each chunk is converted into vector embeddings ? Embeddings are cached to improve efficiency for subsequent operations? ? This system processes nearly an exabyte of data daily through 300 supported file types ?? Phase 2: Content Understanding? ? For summaries: K-means clustering identifies diverse, representative chunks ? For Q&A: Embeddings match question to relevant text chunks? ? Dynamic context selection determines how much context to provide ? Direct questions receive fewer, more relevant chunks while broad questions get more context ? The system provides source references so users can verify information ?? The Results ? Processing time reduced by 96% (115s → 4s) ? Cost-per-summary cut by 93% This combination of intelligent chunking, strategic embedding, and dynamic context selection proves to be a powerful approach for extracting meaning from unstructured data at enterprise scale. ??

In this quick breakdown, we tackle a common challenge with vector search: metadata handling. When customers search for "popular pants" on an e-commerce site, traditional vector search falls short. Why? You can't efficiently pull half your database just to rerank by popularity, and simple filtering struggles with subjective concepts like "popular." The solution? Superlinked - our open-source library that elegantly handles both text semantics AND metadata in one query. With a simple schema creation, you can define how both text and ratings get properly vectorized, delivering results that are both "popular" AND "pants" simultaneously. No reranking. No filtering. Just efficient vector search that actually works for real-world queries. Follow and stay tuned for more such content. DM us to learn more, or visit docs.superlinked.com to try it out yourself! #VectorSearch #AISearch #Ecommerce #RecommenderSystems

Superlinked + Streamkap = Amazing impact! ?? Great working with you Paul Dudley and Ricky Thomas. Let's help more #ecommerce businesses deliver a real time and personalised experiences to their users and make loads of money on the process ?? #realtime #personalisation

In this quick breakdown, we tackle a common challenge with vector search: metadata handling. When customers search for "popular pants" on an e-commerce site, traditional vector search falls short. Why? You can't efficiently pull half your database just to rerank by popularity, and simple filtering struggles with subjective concepts like "popular." The solution? Superlinked - our open-source library that elegantly handles both text semantics AND metadata in one query. With a simple schema creation, you can define how both text and ratings get properly vectorized, delivering results that are both "popular" AND "pants" simultaneously. No reranking. No filtering. Just efficient vector search that actually works for real-world queries. Follow and stay tuned for more such content. DM us to learn more, or visit docs.superlinked.com to try it out yourself! #VectorSearch #AISearch #Ecommerce #RecommenderSystems

?? Unlock the Power of Vector Embeddings with Superlinked ?? Are you diving into the world of Generative AI and vector embeddings? ?? Superlinked is here to help take your AI applications to the next level! Superlinked is an open-source project designed to streamline the management and utilisation of vector embeddings, making it easier than ever to integrate them into GenAI workflows. Whether you're building a recommendation engine, working on semantic search, or creating advanced machine learning models, Superlinked provides a framework for seamlessly managing and interacting with your embeddings. Why Superlinked? ?? ? Efficient handling of vector embeddings for GenAI tasks ? Powerful tools to store, query, and optimize your embeddings ? Seamless integration into real-world applications ? Open-source, so you can customise it to fit your needs! If you’re working with vector-based models or looking to enhance your Generative AI solutions, Superlinked is the perfect addition to your toolkit. ?? Check out Superlinked on GitHub [https://lnkd.in/gx943Pjf] and ? star the repo to show your support! Let’s push the boundaries of AI together! ?? #AI #GenerativeAI #VectorEmbeddings #MachineLearning #DeepLearning #AIApplications #OpenSource #GitHub