#VectorDB — Search

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Darshj.AI @thedarshanjoshi · 4h

💡 Vector databases transformed semantic search Embeddings beat keywords. RAG beats fine-tuning for most cases. Your next app needs vector search. Start with Qdrant. #AI #VectorDB #Searcha

kevin kubai @KubaiKevin · 10h

🎓 Everything about Boost Code New comprehensive guide covering: ✨ Core concepts 🔧 Practical examples ⚡ Performance tips 🎯 Best practices Dive in 👇 🔗 kubaik.github.io/boost-code-top… #TypeScript #VectorDB #ProductivityHacks #programming #Blockchain

Darshj.AI @thedarshanjoshi · 12h

🔥 Vector databases transformed semantic search Embeddings beat keywords. RAG beats fine-tuning for most cases. Your next app needs vector search. Start with Qdrant. #AI #VectorDB #SearchB

Osman E @OxErsoy · 14h

#Chroma just open-sourced Context-1 a 20B parameter agentic search model built for complex multi-hop retrieval. They have been one of the go-to vector DBs for agentic workflows for the past couple of years, and it’s still widely used today. Excited to try Context-1. #AI #VectorDB

Rajveersinh Parmar @Rajveersin15363 · 16h

Replying to @Rajveersin15363

The core mmap/BWT optimizations are kept private for enterprise, but the Lite API routing architecture is now live. Looking for brutal feedback from engineers working on LLM/RAG systems. Test the routing logic locally. 👇 #AI #RAG #VectorDB #Python #FastAPI

Hyluminix Infosystems @Hyluminix · 21h

🧠 ChatGPT doesn’t know your business — and that’s by design. Vector databases add the missing memory layer: Docs → vectors → semantic search → real-time answers. No vector DB = AI that forgets. With it = AI that understands your business. #rag #vectordb #llm #enterpriseaia

Darshj.AI @thedarshanjoshi · 1d

🚀 Vector databases transformed semantic search Embeddings beat keywords. RAG beats fine-tuning for most cases. Your next app needs vector search. Start with Qdrant. #AI #VectorDB #SearchQ

laxmikant pandit @cloudashu · 1d

Replying to @saen_dev

@saen_dev 2026 is vector-first — agreed. But most people miss this: Your embedding model matters more than your vector DB. Bad embeddings in Pinecone < Good embeddings in FAISS. Vector DB = retrieval layer Embeddings = intelligence layer Choose wisely. #AI #RAG #VectorDB

Docsie.io @likalo_llc · 3d

Do fewer parameters mean better AI models? A 70B LLaMA model with access to a vector database for customer support questions performs well enough to make good decisions. You don't need AI to know everything to help with specific job tasks. #AI #LLM #VectorDB #HunterJensen

Darshj.AI @thedarshanjoshi · 3d

🔥 Vector databases transformed semantic search Embeddings beat keywords. RAG beats fine-tuning for most cases. Your next app needs vector search. Start with Qdrant. #AI #VectorDB #Searchy

WiScale France @WiScale_France · 3d

How fast is your vector database? VelesDB: 17.6ns dot product (768D) 98.8% recall@10. 100% in accurate mode. HNSW rewritten from scratch in Rust. ~6MB binary. github.com/cyberlife-code… #RustLang #AI #VectorDB

GitHub - cyberlife-coder/VelesDB: VelesDB is a local‑first AI data engine written in Rust that...

VelesDB is a local‑first AI data engine written in Rust that unifies vectors, full‑text and graph in a single file with a familiar SQL‑like language. Instead of sending every RAG or semantic searc...

From github.com

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Lead AI Dev⚡Full Stack AI Dev Insider @LeadAIdev · 3d

Dify v1.13.1 Enhances Vector Retrieval and Data Operations Worth the switch? #RAG #VectorDB leadai.dev/insider/dify-v…

Dify v1.13.1 Enhances Vector Retrieval and Data Operations - AI Dev Insider | Lead AI Dev

Dify version 1.13.1 integrates Hologres for vector retrieval and introduces new API endpoints for efficient data handling.

From leadai.dev

Darshj.AI @thedarshanjoshi · 3d

💡 Vector databases transformed semantic search Embeddings beat keywords. RAG beats fine-tuning for most cases. Your next app needs vector search. Start with Qdrant. #AI #VectorDB #SearchB

Darshj.AI @thedarshanjoshi · 3d

🚀 Vector databases transformed semantic search Embeddings beat keywords. RAG beats fine-tuning for most cases. Your next app needs vector search. Start with Qdrant. #AI #VectorDB #Search9

Darshj.AI @thedarshanjoshi · 3d

✨ Vector databases transformed semantic search Embeddings beat keywords. RAG beats fine-tuning for most cases. Your next app needs vector search. Start with Qdrant. #AI #VectorDB #Search

Darshj.AI @thedarshanjoshi · 4d

⚡ Vector databases transformed semantic search Embeddings beat keywords. RAG beats fine-tuning for most cases. Your next app needs vector search. Start with Qdrant. #AI #VectorDB #Search

Darshj.AI @thedarshanjoshi · 4d

🔥 Vector databases transformed semantic search Embeddings beat keywords. RAG beats fine-tuning for most cases. Your next app needs vector search. Start with Qdrant. #AI #VectorDB #SearchW

dotenvcoder @dotenvcode18959 · 5d

Vector DBs are essential for potent RAG! 🚀 They fuel precise context retrieval, leading to more accurate & reliable LLM responses. A game-changer for enterprise AI & reducing hallucinations. #RAG #VectorDB #LLMs #AI #Techo