Understanding Embedding Models 🤖

Everyone’s talking about embedding models lately—but what do they actually do, and why does it matter? In this video, @RaphaelDeLio breaks it down in simple terms and shows how embeddings power search, recommendations, and AI features behind the scenes.

You’ll learn:
✅ What embedding models are and how they represent meaning using vectors 🧠
✅ How they help computers understand text, images, and unstructured data 📄🖼️
✅ Why embeddings power search, recommendations, and even fraud detection 🔍
✅ Where to find ready-to-use models—and how to get started quickly ⚙️

0:00 - Intro
0:16 - How humans vs. computers see data
0:40 - Why understanding text and images is hard
1:21 - The solution: embeddings
3:00 - Real-world use cases
3:35 - Where to find embedding models
3:54 - Where to get started

Resources:
https://github.com/redis-developer/redis-ai-resources
https://huggingface.co
Word2Vec paper: https://arxiv.org/pdf/1301.3781
Transformers paper: https://arxiv.org/pdf/1706.03762v7

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