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Nexus: Specialization meets Adaptability for Efficiently Training Mixture of Experts

Cohere

Efficiency, specialization, and adaptability to new data distributions are qualities that are hard to combine in current Large Language Models.

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Research Cohere

ResearchMetadata Archaeology: Unearthing Data Subsets by Leveraging Training DynamicsCohere ResearchExploring Low Rank Training of Deep Neural NetworksCohere ResearchTo Code, or Not To Code? Exploring Impact of Code in Pre-trainingCohere ResearchScalable Data Ablation Approximations for Language Models through Modular Training and MergingCohere ResearchPolicy Primer - Efficient AICohere ResearchUnderstanding and Mitigating Language Confusion in LLMsCohere BlogsThe Most Important Work in AI Training Is Also the Most Overlooked - Deepgram Blog ⚡️Deepgram BlogsHow to implement AI training for employeesZapier BlogsAI frameworks: Definition, types, and how to chooseZapier NewsWhen CI Meets CD: Deliver With ConfidenceThenewstack BlogsBuilding an RL theorem-proving workflow on ModalModal BlogsComputed Values: More Than Meets the EyeCss Tricks EventsDuck Duck Stream: How to Efficiently Load Data into DuckLake with EstuaryMotherduck BlogsDocker Captain Take 5Docker BlogsDocker Community All Hands RecapDocker BlogsToday Is The Day!Docker BlogsIntroducing the Docker Desktop WSL 2 BackendDocker Blogswith Docker Using Node.jsDocker Blogs6 tips every developer should know when using Cursor and Windsurf AIMintlify BlogsInteractive Training Videos (+ How to Create One with AI)Synthesia