What you can do with Gemini Embedding 2
Skills:
RAG Basics90%
Building multimodal RAG or agentic workflows? This model natively maps text, images, video, audio, and documents into a single unified embedding space-no intermediate conversions required.
With Matryoshka Representation Learning (MRL), you get full control over your output. Truncate from 3072 dimensions down to 1536 or even 768 to optimize for scale while maintaining high-level accuracy.
Resources:
Watch the full deep dive → https://goo.gle/4uFoT63
Subscribe to Google for Developers → https://goo.gle/developers
Speakers: Patrick Loeber
Products Mentioned: Gemini
Watch on YouTube ↗
(saves to browser)
Sign in to unlock AI tutor explanation · ⚡30
More on: RAG Basics
View skill →Related AI Lessons
⚡
⚡
⚡
⚡
Zero-Trust RAG: Defeating the Shared Private Link Deadlock in Azure Terraform
Dev.to · david
Choosing the Right RAG Strategy A Complete Decision Guide to Chunking, Agentic RAG, and GraphRAG
Dev.to · Seenivasa Ramadurai
The simplest self-hosted RAG you'll ever set up (Apache 2.0, 20K stars)
Dev.to · retrovirusretro
Tencent just released a RAG framework and nobody's talking about it
Dev.to · retrovirusretro
🎓
Tutor Explanation
DeepCamp AI