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What is LLM Mixture of Experts ?

📹 VIDEO TITLE 📹 What is LLM Mixture of Experts ? ✍️VIDEO DESCRIPTION ✍️ Mixture of Experts (MoE) in Large Language Models (LLMs) is changing the game for AI efficiency and scalability! In this video, we’ll break down what MoE is, how it works, and why it’s becoming a key technique in cutting-edge AI models. Instead of activating all parameters for every input, MoE uses a gating mechanism to select only a few specialized "expert" networks, making LLMs faster, cheaper, and more powerful than traditional dense models. We’ll dive into the core architecture of MoE, explaining how expert selection, sparse activation, and dynamic routing work together to boost AI efficiency. You’ll also learn about real-world MoE models like Mixtral, and DeepSeek, which achieve state-of-the-art performance while keeping computational costs low. Plus, we’ll explore the trade-offs of MoE, including load balancing challenges, routing complexity, and training stability. Whether you’re an AI researcher, machine learning engineer, or just curious about how the next generation of AI models is evolving, this video will give you a clear, high-level understanding of MoE in LLMs. Don’t forget to like, subscribe, and drop a comment if you have questions or want a deep dive into specific MoE architectures. Let’s explore the future of scalable, efficient AI together! 🧑‍💻ACADEMIC PAPER URL 🧑‍💻 https://www.cs.toronto.edu/~fritz/abs... 📽OTHER NEW MACHINA VIDEOS REFERENCED IN THIS VIDEO 📽 Build an MP Neuron with PyTorch -    • Build an MP Neuron with PyTorch   LangChain versus LangGraph -    • LangChain versus LangGraph   Chroma versus Pinecone Vector Database -    • Chroma versus Pinecone Vector Database   What is the Chroma Vector Database ? -    • What is the Chroma Vector Database ?   RAG with OpenAI & Pinecone Vector Database ? -    • RAG with OpenAI & Pinecone Vector Dat...   What are LLM Function Calls ? -    • What are LLM Function Calls ?   Embeddings with Open AI & Pinecone Vector Database -    • Embeddings with Open AI & Pinecone Ve...   What is Hugging Face? -    • What is Hugging Face ?   RAG vs Fine-Tuning -    • RAG versus LLM Fine-Tuning   What is RAG ? -    • What is RAG ?   What is the Perceptron? -    • What is the Perceptron ?   What is the MP Neuron? -    • What is the MP Neuron ?   What is Physical AI ? -    • What is Physical AI ?   What is the Turing Test ? -    • What is the Turing Test?   What is LLM Alignment ? -    • What is LLM Alignment ?   What are Agentic Workflows? -    • What are Agentic Workflows ?   Why is AI going Nuclear? -    • Why is AI going Nuclear?   What is Synthetic Data? -    • What is Synthetic Data?   What is NLP? -    • What is NLP ?   What is Open Router? -    • What is Open Router ?   What is Sentiment Analysis? -    • What is Sentiment Analysis ?   What is Mojo ? -    • What is Mojo ?   LangChain HelloWorld with Open GPT 3.5 -    • LangChain HelloWorld with Open GPT 3.5   Forget about LLMs What About SLMs -    • Forget about LLMs What About SLMs ?   What are LLM Presence and Frequency Penalties? -    • What are LLM Presence and Frequency P...   What are LLM Hallucinations ? -    • What are LLM Hallucinations ?   Can LLMs Reason over Large Inputs ? -    • Can LLMs Effectively Reason over Larg...   What is the LLM’s Context Window? -    • What is the LLM's Context Window ?   What is LLM Chain of Thought Prompting? -    • What is LLM Chain of Thought Prompting?   Algorithms for Search Similarity -    • Algorithms for Search Similarity   How LLMs use Vector Databases -    • How LLMs use Vector Databases   What are LLM Embeddings ? -    • What are LLM Embeddings ?   How LLM’s are Driven by Vectors -    • How LLM’s are Driven by Vectors   What is 0, 1, and Few Shot LLM Prompting ? -    • What is 0, 1, and Few Shot LLM Prompt...   What are the LLM’s Top-P and TopK ? -    • What are the LLM’s Top-P + Top-K ?   What is the LLM’s Temperature ? -    • What is the LLM’s Temperature ?   🔠KEYWORDS 🔠 #MixtureOfExperts #LLMMoE #AIOptimization #MachineLearning #DeepLearning #SparseModels #AIArchitecture #ExpertModels #AIResearch #EfficientAI #NeuralNetworks #LLMTraining #ModelScalability #MoEArchitecture #Mixtral #DeepSeekMoE #AIInference #AIAcceleration