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Home » Cohere lays off staff after $500 Million Funding Round.

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Cohere lays off staff after $500 Million Funding Round.

Although Cohere cut about 20 roles, the startup continues to hire aggressively to meet up with demands.

Charles Ndubuisi
Charles Ndubuisi
July 25, 2024
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On Tuesday, Cohere the AI startup, which had declared having 400 employees following the completion of its $500 million funding round, has cut down its workforce by 20 roles.

Founded by an ex-Google AI researcher and backed by Nvidia, Cohere’s funding round attracted investments from Nvidia, AMD, Oracle, and Salesforce, more than doubling the value of the AI startup to $5.5 billion compared to its last year’s valuation.

However, Cohere continues to hire in departments such as product design, customer operations, sales, modeling, revenue, and partnership, despite recent cuts.

With our most recent round of financing in place, we have a clear vision for the future of Cohere, which has required some internal realignment. We will continue to aggressively hire people as we work to offer companies the most accurate, secure, and private multilingual AI solutions in the market.

Cohere’s Press representative

Cohere’s business model prioritizes generative AI for enterprises, moving away from the consumer chatbots that have dominated tech since the launch of ChatGPT in 2022. In mid 2023, the AI startup secured $270 million in a funding round from Oracle and Salesforce, placing the startup at a $2.2 billion valuation.

In March, Martin Kon, Cohere’s president and Chief Operating Officer, explained to CNBC that focusing exclusively on enterprise AI allows the startup to operate efficiently and keep costs under control despite challenges like chip shortages, rising GPU costs, and fluctuating AI model licensing fees.

At the time, Kon mentioned that Cohere had a reserve of Google chips for over two years, acquired in its early days to help pre-train its models. However, the startup is now shifting its focus to Nvidia’s H100 GPUs, which are powering many of the latest large language models.

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