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Cohere summary

Cohere offers LLM products to deploy AI solutions with the enterprise.

Value proposition

  • Focus to solve problem with ML and AI
  • Strong in NLP in different human's languages.
  • Command LLMs are easy to customize and fine tune
  • Strong on RAG, with Embeddings, Rerank products. Dedicated AI research group. Support open science initiatives: Aya is a state-of-the-art multilingual open-source research model and dataset covering 101 languages.
  • Use SaaS offering, with chat and playground: Playground allows developer to experience the power of LLM without coding a single line.
  • Easy integration via SDK and APIs
  • Scalable models

Products

Three main products: Command for LLM, Embed, and Rerank.

Command-R

A LLM optimized for long-context task, and to support enterprise deployments using:

  • Advanced Retrieval Augmented Generation with citation to reduce hallucinations
  • 128K context length
  • Multilingual coverage in 10 key languages to support global business operations
  • Tool Use to automate sophisticated business processes using single-step tool or multi-step tool like an agent

Embed

Embeddings can be used for estimating semantic similarity between two texts, choosing a sentence which is most likely to follow another sentence, or categorizing user feedback. Embed improves the accuracy of search, classification, clustering, and RAG results. Cohere embedding associates each word with a vector of length 4096. It supports more than 100 languages.

Rerank

Rerank models sort text inputs by semantic relevance to a specified query. They are often used to sort search results returned from an existing search solution. Rerank is used to inject the intelligence of a language model into an existing search system.

References