Mistral AI's Bold Journey

From Paris to Global Stage: The Unconventional Rise of a French AI Unicorn and Its Open-Source Revolution

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Ksenia Se & Tasmia Ansari
January 05, 2024

Updates:

June 11, 2024

This French startup, founded in April 2023 with the ambitious goal of challenging the European Union's technological supremacy, has earned both admiration and skepticism. What sets Mistral AI apart is its focus on open-source technology and its bold approach, unapologetically offering models devoid of safety controls. According to a list of 178 questions and answers composed by AI safety researcher Paul Röttger and 404 Media’s testing, Mistral AI’s models have been churning out some rather dicey advice. The content generated by Mistral AI's models has ignited debates on morality, spanning topics from ethnic cleansing to retrograde discrimination, even venturing into unsettling DIY territory.

In December 2023, only 7 months after their launch, Mistral AI ripped all the charts, becoming a GenAI unicorn with a valuation exceeding $2 billion. They also unconventionally launched an open-sourced model, Mixtral 8x7B, based on the sparse mixture-of-experts technique, via a torrent link! Who are these bold French innovators, what drives them, why the Mixtral model is so efficient, who supports them, and why? Let’s find out.

  1. Starting point of Mistral AI

  2. The founders' (or France's?) vision

  3. Founder’s views toward AI risks 

  4. Financial situation

  5. It took them four months to roll out their first LLM

  6. Next step: Mixtral – understanding SMoE architecture and what makes that model so efficient

  7. How does Mistral make money? 

  8. Conclusion

Starting point of Mistral AI

“The foundational layer story isn't written yet. There are still many things to invent. And that's what we're starting doing,” Mensch told Sifted. “That's why we left our companies that weren't innovative enough — that’s why we started Mistral AI.”

Arthur Mensch (CEO), along with his co-founders Timothée Lacroix (CTO) and Guillaume Lample (Chief Science Officer), go way back – to their AI-studying days at École Polytechnique and École Normale Supérieure. Lacroix and Lample both started at Facebook in 2014 as interns and eventually ended up in Meta’s Paris AI hub. Mensch joined DeepMind's Paris office in 2020, working on “Large language modeling - multimodal models - retrieval”. According to their first lead investor, Lightspeed Venture Partners, “During his time at DeepMind, Arthur was a lead contributor to the Retro, Flamingo, and Chinchilla projects, gaining valuable experience in optimizing large language models. Guillaume led the development of LLaMa LLM along with Timothée.”

Then the friends started mulling over where AI is headed and how they can create a credible open-source alternative and make Europe – specifically Paris, France – a main hub for that.

“It is a market where, in Europe, many actors won’t be willing to rely on American providers,” says Mensch. “There is a geographical stake here that we are willing to exploit.”

The founders' (or France's?) vision

Recently, prominent French AI leaders such as Yann LeCun of Meta and Clément Delangue of Hugging Face have been actively promoting French tech achievements on Twitter. This effort culminated in a partnership between Meta, Hugging Face, and Scaleway at Paris's Station F, signaling a shift in the global tech landscape. France, with its academic excellence and government support, aims to emerge as a potential open-source AI capital.

Mistral AI fits neatly into this narrative. Although their website provides an extensive explanation of why the trio is building Mistral AI – emphasizing community-backed model development to combat censorship and bias, and offering open-weight models as a credible alternative to AI oligopolies – it appears more like the founding trio – Mensch, Lacroix, and Lample – found themselves in the right place at the right time, with the right expertise.

The question remains – with the European Union's intended stringent control of AI and the unclear position of open-source in this model – how will Mistral AI comply?

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Arthur Mensch

Guillaume Lample 

Timothee Lacroix

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