Скачать с ютуб Mixture of Agents: Multi-Agent meets MoE? в хорошем качестве

Mixture of Agents: Multi-Agent meets MoE?

Discover how MoA combines the collective strengths of multiple LLMs to set new quality benchmarks, building on innovations like the Mixture of Experts within transformer architectures. This session will delve into how MoA enhances standard multi-headed self-attention mechanisms, offering significant performance improvements. We'll dissect the original research, examine the structural foundations and assumptions, and provide a detailed performance analysis. Join us for a comprehensive walkthrough of the MoA concept and its practical implementation. Whether you're looking to enhance your AI toolkit or integrate MoA into your production environments, this event is your gateway to understanding and leveraging the full potential of multi-agent LLM applications Join us every Wednesday at 1pm EST for our live events. SUBSCRIBE NOW to get notified! Speakers: ​Dr. Greg, Co-Founder & CEO AI Makerspace   / gregloughane   The Wiz, Co-Founder & CTO AI Makerspace   / csalexiuk   Apply for The AI Engineering Bootcamp on Maven today! https://bit.ly/AIEbootcamp LLM Foundations - Email-based course https://aimakerspace.io/llm-foundations/ For team leaders, check out! https://aimakerspace.io/gen-ai-upskil... Join our community to start building, shipping, and sharing with us today!   / discord   How'd we do? Share your feedback and suggestions for future events. https://forms.gle/z96cKbg3epXXqwtG6 00:00:00 Understanding Mixture of Agents vs. Mixture of Experts 00:04:02 Exploring Existential Questions with AI 00:09:07 Understanding Self-Refinement in AI Models 00:13:00 Understanding Neural Network Layers 00:16:47 Understanding Large Language Models (LLMs) as Agents 00:20:26 Exploring Self-Reflective Neural Networks 00:24:11 Understanding the Mixture of Experts Approach 00:28:59 Introduction to the Event and Build of the Day 00:31:58 Understanding Multi-Agent Layer System 00:35:23 Challenges with LLM Context and Bias 00:38:50 Experimenting with Llama 3.1 Model and Aggregator Prompts 00:41:48 Layered Approach to AI Complexity 00:45:15 Understanding Multi-Agent Systems 00:49:10 Advantages of Using Smaller, Flexible Models 00:52:48 Future of MOA in AGI Development 00:56:24 Exploring the Critique and Actor-Critic Model 01:00:20 Conclusion and Feedback Request