From RAG to autonomous apps with Weaviate and Gemini on Google Kubernetes Engine

As generative AI applications mature, retrieval-augmented generation (RAG) has become popular for improving large language model-based apps. We expect teams to move beyond basic RAG to autonomous agents and generative loops. We'll set up a Weaviate vector database on Google Kubernetes Engine (GKE) and Gemini to showcase generative feedback loops.
After this session, a Google Cloud GKE user should be able to:
- Deploy Weaviate open source on GKE
- Set up a pipeline to ingest data from the Cloud Storage bucket
- Query, RAG, and enhance the responses
Speakers: Brian Kaufman, Bob van Luijt
Watch more:
All sessions from Google Cloud Next → goo.gle/next24
#GoogleCloudNext
OPS209

[@lebesguegilmar1]

Fantastic