
"Cohere, the Toronto-based startup building large language models for business customers, has long had a lot in common with its hometown hockey team, the Maple Leafs. They are a solid franchise and a big deal in Canada, but they've not made a Stanley Cup Final since 1967. Similarly, Cohere has built a string of solid, if not spectacular, LLMs and has established itself as the AI national champion of Canada."
"Now it's making a renewed bid for relevancy: Last month the company raised $500 million, boosting its valuation to nearly $7 billion; hired its first CFO; and landed a marquee recruit in Joelle Pineau, Meta's longtime head of AI research. Pineau announced her departure from Meta in April, just weeks before Mark Zuckerberg unveiled a sweeping AI reorganization that included acquiring Scale AI, elevating its cofounder Alex Wang to chief AI officer, and launching a costly spree to poach dozens of top researchers."
"Cohere was founded in 2019 by three Google Brain alumni - Nick Frosst, Ivan Zhang and Aidan Gomez, a coauthor on the seminal 2017 research paper, titled "Attention Is All You Need," that jump-started the generative AI boom. According to Frosst, in May the startup reached $100 million in annual recurring revenue. It's an important milestone, and there have been unconfirmed reports that Cohere projects doubling that by the end of year."
Cohere is a Toronto-based startup building large language models for business customers and has been compared to the Maple Leafs as a prominent but trophy-less national franchise. The company raised $500 million last month, boosting its valuation to nearly $7 billion, hired its first CFO, and recruited Joelle Pineau from Meta. Pineau left Meta just before a major AI reorganization and her arrival provides a reputational boost for Cohere. Founded in 2019 by three Google Brain alumni, Cohere reached $100 million in annual recurring revenue and expects potential growth, but still lags larger rivals like OpenAI and Anthropic.
Read at Fortune
Unable to calculate read time
Collection
[
|
...
]