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 

The AI Lakehouse extends the Lakehouse architecture by adding components specifically designed for AI/ML, such as AI pipelines, AI query engine, catalog(s) for AI assets and infrastructure for LLMs and ML workflows. Deep dive into the components and Hopsworks AI Lakehouse architecture here https://bit.ly/3YV5roA 🛠️

Hopsworks medical copilot is a LLM powered digital assistant that can be used for reviewing extensive medical records and providing doctors with a full summary, in just a matter of seconds. ⚡ https://bit.ly/4fbBfeG

Did you miss this year’s summit? Don’t worry, we have recorded all presentations. ✅ Rewatch as Ray from Hopsworks explains how to unlock feature freshness in milliseconds with Hopsworks AI lakehouse infrastructure. ➡️ https://lnkd.in/dGQ4wBtU

Only a few days left until PyData NYC and we’re more than proud to be able to present two talks this year! 🔥 In Javier’s session he’ll describe the capabilities that need to be added to a Lakehouse architecture to make it an AI Lakehouse that can support building and operating AI-enabled batch and real-time applications as well as LLM-powered applications.

We are speaking at Nodes 24! 🌐 Discover how Hopsworks and Neo4j are transforming patient care, enhancing productivity, and accelerating medical research with AI-powered copilot applications. Join Fabio Buso, Darryl Salas to learn how these tools empower healthcare providers to make data-driven decisions in real time.

At the Feature Store Summit, Javier de la Rúa Martínez presented how Hopsworks supports the snowflake schema data model. ❄️ The snowflake schema data model, in comparison to the star schema data model, allows you to reduce the number of serving keys that your AI application need to make a prediction. https://bit.ly/3UOYt2f

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