Weaviate is hiring! 🌟 Join our team and help shape the future of AI technology. Check out our open roles: • Event Marketing Manager: https://lnkd.in/d4sK7kNq • Senior Software Engineer Database: https://lnkd.in/daa2F-uM • Revenue Operations Manager: https://lnkd.in/dSkHt2uh • Client-Focused Site Reliability Engineer: https://lnkd.in/dAvgickM • Machine Learning Engineer: https://lnkd.in/edunj5yu Explore more roles and learn more about them on our Careers page: https://lnkd.in/dzibHnwZ Stay tuned for more opportunities coming soon! 👀
Weaviate
Technologie, informatie en internet
Amsterdam, North Holland 21.037 volgers
The AI-native database for a new generation of software.
Over ons
Weaviate is a cloud-native, real-time vector database that allows you to bring your machine-learning models to scale. There are extensions for specific use cases, such as semantic search, plugins to integrate Weaviate in any application of your choice, and a console to visualize your data.
- Website
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https://weaviate.io
Externe link voor Weaviate
- Branche
- Technologie, informatie en internet
- Bedrijfsgrootte
- 51 - 200 medewerkers
- Hoofdkantoor
- Amsterdam, North Holland
- Type
- Particuliere onderneming
- Opgericht
- 2019
Locaties
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Primair
Amsterdam, North Holland, NL
Medewerkers van Weaviate
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Ben Sabrin
Head of Global Sales at Weaviate , The Open AI Native VectorDB
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Sam Ramji
Co-founder and CEO of Sailplane
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Igor Taber 🇺🇦
Founder and General Partner at Cortical Ventures - funding and incubating next AI leaders
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Dharmesh Thakker
General Partner at Battery Ventures - Supporting Cloud, DevOps, AI and Security Entrepreneurs
Updates
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Weaviate heeft dit gerepost
Create personalized product descriptions from user personas using the Gemini API and Weaviate 🔹 I'm excited to share my contribution to Google's Gemini cookbook! In this notebook, you'll learn how to: 1. Write product descriptions based on other attributes 2. Generate synthetic user personas 3. Write customized product descriptions for each persona Notebook: https://lnkd.in/eetSm-92
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Are you attending #ConfluentCurrent in Austin, TX on September 17th and 18th? Join ⚙️Mohd S., Deepti Naidu, and Jobi George in the Expo hall to learn about Wealingo! Wealingo uses Weaviate's vector database and Confluent Cloud's streaming capabilities to provide real-time, personalized language learning. We'll explore how Weaviate generates embeddings and interacts with large language models (LLMs) to craft questions tailored to each user's previous mistakes and interests. Learn more about Confluent Current and register here: https://lnkd.in/eKH7wAdG
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We’re proud to be listed as #38 in #WillReedsTop100 Class of 2024! At Weaviate, we see culture as a differentiator, so it means a lot to be recognized along with other B2B companies building values-driven cultures. #BuildTogether 💚 Read more: https://lnkd.in/e746M4YC See the full list here: https://lnkd.in/gfycPAdF
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Weaviate heeft dit gerepost
Today is Verba's birthday, and we're celebrating with a big update! 🎂 Verba 2.0.0 is now available via `pip install goldenverba`. ✨ This release brings a lot of exciting new features and improvements: Completely revamped ingestion process: - Upgraded to Weaviate v4 for super-fast, async indexing - Integrated with unstructured.io (https://unstructured.io/) for enhanced data ingestion - Partnered with Firecrawl (https://www.firecrawl.dev/) for efficient web scraping Enhanced chunking capabilities: - New chunkers from the amazing LangChain library (https://www.langchain.com/) - Built-in Tokenizer and Sentencizer from the best NLP library (I'm very biased) spaCy from Explosion (https://spacy.io/) for super fast chunking. Expanded model support: - SentenceTransformers powering all Hugging Face models - Ollama powering our favorite open source Large Language Models - Added support for Anthropic, Voyage AI, Cohere, and OpenAI Improved customization: - Detailed configurations available for every component And much, much more! Thanks a lot to the community. Without you and your contributions, this project wouldn't be what it is today ❤️ Check out the new version here GitHub: https://lnkd.in/d3sRrBW9 Or try out our updated Live demo: https://verba.weaviate.io/
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Weaviate heeft dit gerepost
Developer Relations @ Weaviate | Developer Education and Experience | Builder and International Speaker
I'll be live with WeAreDevelopers talking about giving your website eyes! 👀 Yes, eyes! Learn about multimodal search and beyond with Weaviate in my talk and see how all this is possible in our beloved Javascript. Link to register in the comments 👨🏾🌾
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Ready to Build AI-Powered Apps with Streamlit & Weaviate? Learn how to use Streamlit-Weaviate connection to easily import data from Weaviate into a Streamlit app. Here, we create a movie recommendation app where you can search for movies using hybrid, semantic, and keyword options, filter them by year, and get recommendations based on the viewing occasion! Check out this full demo and code walkthrough by JP Hwang: https://lnkd.in/ezJmxgqx
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Struggling with accurate retrieval for long context RAG? If you've ever built a RAG application that ingests long documents, the difficulty of high-quality search for over them will be a very familiar one. Late chunking may just be the solution you’ve been looking for! This new approach proposed by Jina AI helps to preserve context across large documents by changing when chunking is applied in the embedding process. The result? Individual embeddings that have contextual awareness of their neighbouring chunks ✨ Want to know more about how late chunking could improve your long context search? Check out our latest blog: https://lnkd.in/eXcgBzuj
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We’re excited to announce the free RAG in Production course in collaboration with Weights & Biases and Cohere 🧠 Learn about data ingestion and preprocessing, query enhancement, retrieval and re-ranking, and more! You can register for the pre-order here: https://lnkd.in/ggWwT-ht
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Weaviate heeft dit gerepost
Ever wondered what happens when Weights & Biases, Cohere and Weaviate join forces? 🍳 Have a look at what we've been cooking up for you. https://lnkd.in/ggWwT-ht