Hopsworks

We are proud to announce our biggest and most innovative release yet! 🎉 Hopsworks 4.0 introduces game-changing innovations for building AI systems, whether for batch, real-time or LLM applications, all powered by our AI Lakehouse infrastructure. Release Highlights: 🔹 Kubernetes Deployments - Fully containerized services deployable on any Kubernetes cluster, cloud, or on-premises. 🔹 Hopsworks Query Service - Provides Python clients with up to 45 times higher throughput when reading data. 🔹 Vector Search / Embeddings - Added support for vector & similarity search to easily build GenAI applications. The product will be generally available soon! Stay tuned. https://lnkd.in/d2vR-aZ7 

We migrated Hopsworks to Kubernetes, reducing deployment times significantly. 🚀 In our latest Show, Don’t Tell video, Javier Cabrera demonstrates how we've cut deployment from 2 hours to less than 30 minutes using a Helm install.

We’re soon entering November, which means it’s time for PyData NY! 🗽 Being one of our favourite annual conferences, we’re happy to be back at with a presentation on “Building Python based AI Systems with LLMs”. Jim Dowling will go through a working example to demonstrate the viability now of using AI to build AI systems.

Unlocking feature freshness in milliseconds with Hopsworks AI lakehouse infrastructure. ⚡️ In Ray’s presentation at this year’s Feature Store Summit he introduced the AI Lakehouse, which is an extension to the Lakehouse to include MLOps capabilities. Watch it here https://bit.ly/4fgcRbA

Our webinar on 'Transforming Healthcare with Hopsworks Medical Copilot' is now live!

More than a year has passed since we created the MLOps and LLMOps dictionary. We share the lessons we learned from working with it in this blog post. https://bit.ly/40df7vG If you want to get your hands on a downloadable version of the dictionary we’ve got you covered! Here are the 25 most popular entries that had the highest growth from the past year. https://bit.ly/4dhIa45

I had the privilege and honor of contributing to a massive team effort to migrate Hopsworks' infrastructure to Kubernetes. This journey began a year ago, and with the release of version 4.0, Hopsworks is now fully compatible with Kubernetes as the first AI Lakehouse helm package. https://lnkd.in/ewVzYu7U

Jim Dowling explains the secret sauce to TikTok’s recommendation system. TikTok learns your preferences incredibly fast by updating your features (clicks) in mere seconds and uses that input for making predictions. 🔮 This clip is from Jim’s presentation at PyData Berlin where he showed the audience how to build their own TikTok-like personalized recommendation system in Python, of course using Hopsworks. https://lnkd.in/dCEP2UYv

As organizers of the Feature Store Summit we’re incredibly proud of this year’s lineup and topics. Today we can look forward to hear presentations from Uber, Stripe, Etsy, Airbnb and many more! To join the party, make sure to tune in at 8.30 AM PT // 5.30 PM CEST 

Tomorrow is finally the day for the Feature Store Summit and we’re excited to have the opportunity to present two sessions from our engineering team.  Don’t miss: 📌 Raymond Cunningham's presentation on “From Feature Store to AI Lakehouse”: https://bit.ly/3znfMjf 📌 Javier de la Rúa Martínez’s presentation on “The Snowflake Schema Data Model comes to Feature Stores”: https://bit.ly/4eu0vwj 📌 If you haven’t registered yet, don’t forget to do so: https://bit.ly/48aIXTx