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BMBasith M Rasakcoralithm.hashnode.devMay 10 · 3 min read

Why FAISS Was the Only Choice for My Medical AI Project

When I started building my RAG-based medical assistant, I never spent a single minute debating between vector databases. FAISS was the plan from day one. No Pinecone trial, no Chroma experiment, no sp

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Aaiagentmemoryaiagentmemory.hashnode.devApr 7 · 5 min read

FAISS Vector Database in Memory: Accelerating AI Agent Recall and Memory

A FAISS vector database in memory keeps its entire vector index loaded into RAM for sub-millisecond similarity searches. This architecture provides AI agents with exceptionally fast recall capabilities, enabling more responsive and intelligent intera...

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Aaiagentmemoryaiagentmemory.hashnode.devApr 7 · 10 min read

AI Episodic Memory with FAISS: Enhancing Agent Recall

AI agents can now store and recall specific past events with remarkable efficiency using ai episodic memory faiss. This approach combines human-like memory systems with FAISS's lightning-fast vector similarity search, allowing agents to access precis...

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CMChidozie Managwufreecodecamp.orgMar 16 · 14 min read

How to Ship a Production-Ready RAG App with FAISS (Guardrails, Evals, and Fallbacks)

Most LLM applications look great in a high-fidelity demo. Then they hit the hands of real users and start failing in very predictable yet damaging ways. They answer questions they should not, they bre

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MMindsDBmindsdb.hashnode.devJan 29 · 26 min read

Building a Semantic Search Knowledge Base with MindsDB

Written by Andriy Burkov, Ph.D. & Author, MindsDB Advisor What happens when a developer searches for "how to make async HTTP calls" but your documentation says "asynchronous network requests"? Traditional keyword search fails—even though the content ...

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RKRahul Kaushalrahulkaushal.hashnode.devJan 12 · 19 min read

How AI Finds What You Actually Mean

So. You have heard the word "embedding" thrown around about forty times in AI tutorials. You have nodded along politely. You still have no idea what it actually is. That ends today. This post is going

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SBSai Bhargavsaibhargav.hashnode.devDec 29, 2025 · 12 min read

How to Migrate from FAISS to Qdrant: A Real-World Guide Using the MS MARCO Passage Dataset

Published first in Medium 1. Introduction Why FAISS is great for experimentation but difficult in production If you are an ML engineer, you probably started your vector search journey with FAISS. It’s the standard for a reason: it’s blazing fast and ...

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EJEshan Jairatheshanjairath.hashnode.devNov 20, 2025 · 5 min read

Designing Smarter RAG Systems with Effective Chat History Management

Building a robust RAG (Retrieval-Augmented Generation) system isn’t only about retrieving information, it’s about creating conversations that feel contextual, continuous, and intelligent. One of the biggest challenges in achieving this is managing ch...

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SSShivam Shasheeshshivamshasheesh.hashnode.devOct 20, 2025 · 9 min read

I Built a Production-Grade RAG Framework With Hybrid Search, Contextual Chunking, and Zero Cloud Lock-In

I Built a Production-Grade RAG Framework With Hybrid Search, Contextual Chunking, and Zero Cloud Lock-In Every RAG tutorial on the internet follows the same pattern: take a document, split it into 512-token chunks, embed with OpenAI, dump into a vect...

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KKashifblog.ifkash.devAug 28, 2025 · 4 min read

I Built a Tiny Vector Database (and Pointed It at FAISS)

Vector DBs are everywhere these days: Pinecone, Weaviate, Qdrant, Chroma, FAISS … you name it! Most of them are full-featured systems with servers, APIs, dashboards, the works. Sometimes the best way to demystify hype is to build it yourself. Here’s ...

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Trending tags this week

Why FAISS Was the Only Choice for My Medical AI Project

FAISS Vector Database in Memory: Accelerating AI Agent Recall and Memory

AI Episodic Memory with FAISS: Enhancing Agent Recall

How to Ship a Production-Ready RAG App with FAISS (Guardrails, Evals, and Fallbacks)

Building a Semantic Search Knowledge Base with MindsDB

How AI Finds What You Actually Mean

How to Migrate from FAISS to Qdrant: A Real-World Guide Using the MS MARCO Passage Dataset

Designing Smarter RAG Systems with Effective Chat History Management

I Built a Production-Grade RAG Framework With Hybrid Search, Contextual Chunking, and Zero Cloud Lock-In

I Built a Tiny Vector Database (and Pointed It at FAISS)