DeepMind’s PEER scales language models with millions of tiny experts [VentureBeat]

Parameter-Efficient Expert Retrieval (PEER) is a technique that allows LLMs to scale to millions of experts and remain resource efficient.

AI,Business,Data Infrastructure,AI research,AI, ML and Deep Learning,category-/Computers & Electronics,category-/Science,data,DBRX,DeepMind,feedforward (FFW) layers,Gemini 1.5 Pro,Google Deepmind,GPT-4,Grok,large language models,LLMs,Mixtral,mixture of experts,Parameter Efficient Expert Retrieval (PEER),parameter-efficient fine-tuning (PEFT),research,scaling models,tokens,transformer block

Parameter Efficient Expert Retrieval (PEER)