🚀 Medial Secures Investment on Shark Tank India - Fueling the Future of Professional Social Networking. 🔥

News

Messages

Try our Valuation Calculator →

Back

Saswata Kumar Dash

Former Research Gen ... • 22d

🚨 Everyone says "RAG is dead" — but I say: It’s just been badly implemented. I’ve worked on AI systems where Retrieval-Augmented Generation (RAG) either changed the game… or completely flopped. Here’s the hard truth 👇 --- 🤯 Most teams mess up RAG not in generation — But in retrieval. What’s going wrong? 🔍 Cosine similarity isn’t context understanding 🧠 Embeddings don’t mean relevance 🚨 Vector DB ≠ Smart Retrieval --- In the last few months, I’ve been diving deep into fixing real-world RAG pipelines that broke in production. And trust me... ⚙️ Demos lie. Logs don’t. So I built a framework to diagnose and optimize retrieval pipelines — from embedding selection to rerankers and beyond. #ai #rag #llms #retrieval #vectorsearch #machinelearning #freelancer #hiring #founders #openai #neuralretrieval #consulting #startupjobs #genai #nlp #jobsearch #allinai

https://www.instagram.com/_the_allin_?igsh=MTc5NzJjYmNjN2Q1aA==

Recommendations from Medial

Rohit joshi

Dev dev dev • 4m

🚀 New Video Alert! 🎉 We've just released a tutorial on building a Retrieval-Augmented Generation (RAG) application using Ollama and Microsoft's Phi-3 model. Key Points: Ollama:A platform that enables running large language models locally, enhanc

Account Deleted

Hey I am on Medial • 2m

Hello Friends, I’ve been diving deep into Retrieval-Augmented Generation (RAG) and its evolved form — Agentic RAG — lately, and I’m genuinely curious about how others are thinking about it. I’d love to hear your ideas, interesting use cases, or eve

Yogesh Jamdade

..... • 3m

How RAG Gen AI Helps Businesses Retrieval-Augmented Generation (RAG) enhances AI by combining real-time data retrieval with generative models, making it highly effective for businesses. Key Benefits: Better Decision-Making – Provides real-time ins

Anonymous

Hey I am on Medial • 3m

Retrieval-Augmented Generation (RAG) is a GenAI framework that enhances large language models (LLMs) by incorporating information from external knowledge bases, improving accuracy, relevance, and reliability of generated responses. Here's a more det

Chetan Bhosale

Software Engineer | ... • 7m

💡 5 Things You Need to Master for learn for integrating AI into your project 1️⃣ Retrieval-Augmented Generation (RAG): Combine search with AI for precise and context-aware outputs. 2️⃣ Vector Databases: Learn how to store and query embeddings for e

3 Replies

Aroneo

| Technologist | ML ... • 4m

In the ever-evolving AI landscape, a new player is making waves — Deepseek. While OpenAI, Google DeepMind, and Meta AI have been dominant forces, Deepseek is emerging as a formidable contender in the AI race.The recent buzz around Deepseek stems from

Inactive

AprameyaAI • 11m

Meta has released Llama 3.1, the first frontier-level open source AI model, with features such as expanded context length to 128K, support for eight languages, and the introduction of Llama 3.1 405B. The model offers flexibility and control, enabli

Amit Soni

A billion dollar dre... • 5m

Turn ANY Website into LLM Knowledge in SECONDS 🤯 Tired of LLMs with limited knowledge? 🧠 This video shows you how to easily scrape any website and turn it into a powerful knowledge base for your own custom AI agents. 🤖 We'll explore: * Crawl for

Aparna Pradhan

fullstack dev specia... • 16h

Hey friends, I’ve been building something close to my heart — a *portfolio project* that reimagines how AI can work as your startup team. Introducing *AgentFlow* — a *virtual office of autonomous AI agents* that think, plan, and collaborate like a le

Chamarti Sreekar

Passionate about Pos... • 4m

Why India’s Biggest Companies Are Betting on Agentic AI Agentic AI refers to autonomous GenAI agents capable of performing complex tasks with minimal human supervision. Indian companies, from startups to enterprises like Zomato, Infosys, and Zoho,