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"Can you figure out what the experts in a Mixture of Experts model are each specialized in?" Yes, this is touched on in the Mixtral paper (2024) and discussed quite extensively in the ST-MoE paper (2022), section 7. Also summarized in https://t.co/dxs41w33Bd People's intuition… https://t.co/xH1i0ey1ey
The trend to compose experts by MoE is on the rise. 📈 Branch-Train-Mix (BTX) uses a experts in math, code, and Wikipedia knowledge along with a 4th generalist model. Soon, customizing your generalist LLM will be made as cheap as LoRA when you Bring Your Own Expert (BYOE) https://t.co/Gy1NFvg0Xd
Developers have figured out that model performance can be improved by combining a couple of LLMs, a concept called model merging. https://t.co/F8pJwqppEE AI Agenda by @steph_palazzolo
Developers are exploring model merging, a technique that combines multiple Language Model Models (LLMs) to enhance AI model performance. The concept involves creating a Mixture of Experts (MoE) by combining smaller models to improve efficiency and task-specific capabilities. The trend is gaining traction as it offers a cost-effective way to customize generalist LLMs and reduce latency in AI applications.
