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How does AI understand meaning in text, images, or even audio? 🤔 The secret is Embeddings — a powerful technique that converts data into numbers (vectors) so machines can compare meaning, similarity, and context. In this video, you’ll learn: ✅ What embeddings are in simple terms ✅ How words/sentences become vectors ✅ Why embeddings capture semantic meaning ✅ Cosine similarity & how AI finds “closest matches” ✅ Real-world uses: Search, Recommendations, Chatbots, RAG ✅ Why embeddings are the backbone of modern AI apps Perfect for AI beginners, developers, and anyone curious about how systems like ChatGPT understand language. 👉 Like | Share | Subscribe for more AI concepts explained clearly! 🚀 embeddings explained what are embeddings in AI turning meaning into numbers vector embeddings text embeddings sentence embeddings semantic similarity cosine similarity explained vector search RAG embeddings AI search system recommendation system embeddings ChatGPT embeddings LLM embeddings machine learning embeddings #Embeddings #AIExplained #MachineLearning #GenerativeAI #LLM #VectorSearch #SemanticSearch #RAG #ChatGPT #ArtificialIntelligence #TechExplained