Based on this YouTube video's total view count of 112K views and industry-standard rates, the estimated total earning is $79 - $225 through ad revenue. Historical data is not yet available to calculate daily, weekly, or monthly averages.

Explore Google's New Model + Claude Code Just Changed RAG Forever with 112,532 views, 3,049 likes, and 147 comments. Experience the impact of this video content that has captured audience attention.

My FREE AI OS Course: https://www.skool.com/ai-automation-society/about?el=googles-new-model-claude-code-just-changed-rag&hcategory=youtube-videos&utm_campaign=free-group Full courses + unlimited support: https://www.skool.com/ai-automation-society-plus/about?el=googles-new-model-claude-code-just-changed-rag&hcategory=youtube-videos&utm_campaign=ais-plus Apply for my YT podcast: https://podcast.nateherk.com/apply Work with me: https://uppitai.com/ My Tools💻 FREE MONTH voice to text: https://get.glaido.com/nate Code NATEHERK for 10% off VPS (annual plan): https://www.hostinger.com/vps/claude-code-hosting Google just dropped Gemini Embeddings 2, a new model that natively understands images, videos, and text all at once. In this video I use it with Claude Code to build a full visual search engine from scratch. The crazy part is you don't have to build any of the chunking or ingestion pipeline yourself anymore. Just describe what you want, point it at your files, and Claude Code handles everything. It extracts content from images, generates descriptions, builds out your Pinecone vector database, all of it. You basically just throw everything you want to be searchable at it and it works. This is a massive unlock for anyone building with RAG. Sponsorship Inquiries: 📧 [email protected] Connect with me: https://www.linkedin.com/in/nateherkelman/ https://x.com/nateherk https://www.instagram.com/nateherk/ TIMESTAMPS 0:00 What Gemini Embeddings 2 Can Do 0:38 Instruction Manual Demo 2:24 Roofing Company Demo 4:01 Why This Is a Big Deal 4:22 How RAG & Embeddings Work 6:54 Setting Up Claude Code 7:31 Planning the Build 9:30 Creating the Vector Database 10:13 Building the Chat App 11:48 Testing & Improving Results 13:40 Searching Videos with RAG 14:04 Current Limitations 14:53 Final Thoughts

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