Mistral CEO Bets on Open-Source and Local AI

Mistral co-founder and CEO Arthur Mensch said the battle for artificial intelligence primacy has nothing to do with geography.

Instead, the contest is between open and closed systems, he said, Bloomberg News reported Wednesday (Feb. 18).

“Betting on open source is something Europe is doing actively and heavily,” he said during an interview at the AI Impact Summit in India, per the report.

Open-source technology is a “safer bet” for India and other countries that wish to build AI on local infrastructure, he said, according to the report. Open models can include cultural nuances, like the hundreds of languages spoken in India, and are easier to deploy on local infrastructure.

Mistral is viewed as Europe’s best option for competing with large AI companies in the United States, the report said. The company has championed its “open weight” AI models as a differentiator.

AI models from companies such as Google, OpenAI and Anthropic are closed-source, meaning the underlying code isn’t publicly available.

Mensch told the Financial Times (FT) last week that Mistral’s annualized revenue run rate, a figure based on the previous month’s sales multiplied by 12, was “north of $400 million,” compared to $20 million a year ago.

Easy access to debt financing means Mistral won’t need to go public this year, a path OpenAI and Anthropic are taking, he said.

“This is definitely something we have in mind for the next few years,” he said, to “guarantee our independence down the line.”

The desire for independence is something felt by companies and governments throughout Europe due to worries about U.S. foreign policy, the FT report said.

Meanwhile, AI is changing the way companies handle billing for software-as-a-service (SaaS) products.

“For the better part of two decades, enterprise software ran on a deceptively simple economic engine: the seat,” PYMNTS reported Wednesday, meaning that companies would buy a certain number of licenses or subscriptions.

But with AI, software spending is tied to how intensely models are exercised, not who uses the tool, leading to “a cost model that behaves less like a subscription and more like a commodities market,” the report said.

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