A French Startup Wants to End Europe’s Reliance on American AI Tools

Summary

Summary of WSJ Tech News Briefing: "A French Startup Wants to End Europe’s Reliance on American AI Tools"

Release Date: June 12, 2025
Host: Victoria Craig, The Wall Street Journal

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Introduction

In the June 12th episode of the WSJ Tech News Briefing, host Victoria Craig delves into Europe's growing ambition to reduce its dependence on American artificial intelligence (AI) giants. The spotlight is on French startup Mistral, which is positioning itself as a formidable competitor in the global AI landscape. Additionally, the episode explores innovative solutions to global water scarcity, highlighting a revived 1960s desalination technology.

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Europe's Quest for AI Sovereignty

J.D. Vance's Paris AI Summit Speech
At the Paris AI Summit, U.S. Vice President J.D. Vance declared, “AI is going to make us more productive, more prosperous and more free. The United States of America is the leader in AI and our administration plans to keep it that way” (00:55). Vance criticized European regulations, suggesting they might hinder AI advancement. However, he also expressed openness to collaboration with European entities.

Mistral: Challenging the AI Giants

Introduction to Mistral
Victoria Craig introduces Mistral, a two-year-old French startup, as “one of Europe's biggest developers of large language models” (01:44). Competing with industry behemoths like OpenAI and Google, Mistral focuses on creating generative AI tools for applications such as computer coding, chatbots, and customer service. Their primary clients include major corporations and governmental bodies.

Insights from WSJ's Sam Schechner
Sam Schechner elaborates, “Mistral is really one of the few companies in Europe that is keeping up in this space... Their tools may not be like the cutting edge of the most recent tools from those big labs, but perform almost as well” (02:14). Mistral differentiates itself through efficiency, cost-effectiveness, and by releasing its models as open-source—similar to Chinese firms like DeepSeq. This openness addresses security concerns associated with software from certain regions, making Mistral an attractive option for businesses seeking strategic autonomy.

Strategic Partnerships and Expansion

Collaboration with Nvidia
Nvidia CEO Jensen Huang announced a partnership with Mistral to build a new AI cloud infrastructure (03:36). According to J.D. Vance, “Today we're announcing that we're going to build an AI cloud together here to deliver their models, as well as deliver AI applications for the ecosystem of other AI startups” (03:46).

Full-Stack AI Solutions
Sam Schechner explains that this partnership extends Mistral’s reach beyond model development to controlling the underlying hardware and software stack (04:03). By situating a data center near Paris, Mistral offers European companies and governments the ability to manage their data independently of U.S.-based supply chains, enhancing strategic autonomy.

Government Support and AI Sovereignty
French President Emmanuel Macron emphasized France’s role in AI sovereignty, referring to the initiative as “our fight for sovereignty or strategic autonomy” (05:39). Highlighting France's energy surplus from nuclear power, Macron underscored the country's capacity to support energy-intensive AI operations. Investments from both private sectors and governments, including the UAE, are accelerating the establishment of AI campuses in France, with Mistral aiming to capitalize on this momentum.

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Innovative Solutions to Water Scarcity

Desalination Technology Revival
The episode transitions to address global water scarcity, presenting a revived desalination technology initially developed in the 1960s (07:16). Modern advancements, particularly from the oil and gas industry, have made it feasible to deploy desalination plants deep under the ocean. This method leverages high water pressure to efficiently push seawater through membranes that filter out salt, significantly reducing energy consumption compared to traditional onshore desalination.

Applications and Challenges
Christopher Mims discusses various pilot projects, including supplying fresh water to an offshore drilling facility in Norway and potential deployments in California to aid water-stressed cities like Los Angeles (10:08). However, challenges remain, such as ensuring long-term viability in harsh ocean conditions and achieving cost-effectiveness. Success hinges on the ability to produce affordable desalinated water on a large scale without incurring prohibitive energy costs (11:13).

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Building Trust in AI

AI Governance and Security
During the episode's interlude, Hrithika Gunner, IBM’s General Manager for Data and AI, discusses strategies for building trustworthy AI systems. She emphasizes the importance of understanding data usage, enforcing privacy policies, and continually updating security measures. Gunner states, “We end up seeing a flying wheel effect of more AI that is actually built and infused into applications, which then yields a better, more engaging, innovative set of capabilities within these companies” (07:07).

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Conclusion

The WSJ Tech News Briefing episode underscores Europe's strategic efforts to establish its own AI infrastructure, reducing reliance on American technology giants through the rise of startups like Mistral and supportive government policies. Simultaneously, innovative approaches to global challenges such as water scarcity highlight the intersection of advanced technology and sustainable solutions. As the AI landscape evolves, Europe's pursuit of sovereignty and innovation positions it as a significant player on the global stage.

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Notable Quotes:

• J.D. Vance: “AI is going to make us more productive, more prosperous and more free. The United States of America is the leader in AI and our administration plans to keep it that way.” (00:55)

• Sam Schechner: “Mistral is really one of the few companies in Europe that is keeping up in this space... Their tools may not be like the cutting edge of the most recent tools from those big labs, but perform almost as well.” (02:14)

• President Emmanuel Macron: “Our fight for sovereignty or strategic autonomy.” (05:39)

• Hrithika Gunner: “We end up seeing a flying wheel effect of more AI that is actually built and infused into applications, which then yields a better, more engaging, innovative set of capabilities within these companies.” (07:07)

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Produced by Julie Chang with Deputy Editor Chris Inslee. For more insights, visit WSJ.com.

Transcript

[Hrithika Gunner]

As companies create AI powered solutions, how can they ensure they're effective and trustworthy? Join IBM at the break to hear how companies can build trust in their AI with Hrithika Ghanar, IBM's general manager for data and AI.

[Victoria Craig]

Welcome to Tech News Briefing. It's Thursday, June 12th. I'm Victoria Craig for the Wall Street Journal. Silicon Valley is a dominant force in the global AI race, but European customers say they want to break dependence on Americ American firms. Can a French startup be part of that solution? Then the world is running out of clean water. We'll introduce you to a technology that promises to fix the problem. But first, anxiety has been rising in Europe since February, when U.S. vice President J.D. vance took the stage at the Paris AI summit and said, AI we believe.

[J.D. Vance]

Is going to make us more productive, more prosperous and more free. The United States of America is the leader in AI and our administration plans to keep it that way.

[Victoria Craig]

Vance criticized European regulations that the Trump administration worries could constrain further development in artificial intelligence. But he said the US Is open to working with European players now. French startup Mistral is stepping up to the plate. At the Viva Technology conference in Paris this week, WSJ tech reporter Sam Schechner spoke to Mistral's CEO who said demand for his company's AI tools and is booming because, quote, European leaders just don't want to be talked to that way. Sam, let's just back up a second because I'm not sure Mistral is a household name for many of our listeners. So remind us what it is and what it does.

[Sam Schechner]

Mistral is a French company. It's less than two years old and it is one of Europe's biggest developers of large language models. It's a startup, but it's in competition with folks like OpenAI and Google when it comes to the market of really developing these general purpose generative AI tools for things like computer coding for chatbots, customer service. And their main clients are big companies and some governments as well.

[Christopher Mims]

So it wants to compete with the largest of the large companies in this AI space. How competitive is it with its US rivals? Because I think a lot of our audience tends to think of AI and think of either the behemoths in the US or, or even those in China. But the company's chief executive told you that European companies and governments are increasingly reaching for AI tools, not dependent on US Tech giants.

[Sam Schechner]

Yeah, well, I mean, Mistral is notable because it is really one of the few companies in Europe that is, you know, keeping up in this space. It's founded by somebody who formerly was at DeepMind and two other people who were at Meta, but they're French, and they wanted to start a company here in part to show that it was possible to do this in Europe. And their tools maybe aren't like at the cutting, cutting edge of the most recent tools from those big labs, but perform almost as well. And what they say is that it's a lot more efficient, it's a cheaper thing to run for a business, and they also release them open source, like some of those Chinese companies that you reference, Deep Seq, for instance. Open source can be a more efficient way to run some companies and governments aren't comfortable with potential security risks of running software from China. And that makes perhaps Mistral a sweet spot for some businesses. At least that's certainly what the company is hoping.

[Christopher Mims]

Nvidia CEO Jensen Huang was actually giving the keynote speech at the conference that you're attending there, and he talked about partnering with Mistral on a new data center.

[J.D. Vance]

Today we're announcing that we're going to build an AI cloud together here to deliver their models, as well as deliver AI applications for the ecosystem of other AI startups so that they can use the Mistral models or any model that they like.

[Christopher Mims]

Tell us more about what we know about this data center.

[Sam Schechner]

This is part of Mistral's new expansion, not just into developing models and into then partnering with companies that are going to use tools based on those models, but actually to offer the underlying computer that will allow companies to basically contract with Mistral in what we call the full stack way. So where they're controlling the hardware and the AI and the software on top of it. For some companies in Europe and governments as well, which are looking for strategic autonomy, they don't want to necessarily have a supply chain that is tied too closely to the us. This could be a solution for that. Obviously, Nvidia is an American company, but if they're going to be sitting 20 miles south of Paris in a Mistral data center, if you're a company, you want to control your data, that could be very attractive to you. In addition, Nvidia's CEO said, and Arthur Mensch, the CEO of Mistral, told me that they are looking possibly to work with other companies that want to develop their own models and could use this compute. So in a way, Mistral is moving to a more base level of the AI business and they could become a provider to other AI developers to train their own models too.

[Victoria Craig]

This isn't just an ambition that Mistral has to become a leader or a power player in AI. France has promoted itself as a destination for AI. And President Emmanuel Macron, on stage this week with mistral and Nvidia. CEOs encouraged French companies to sign agreements to use Mistral's new data center. He called it our fight for sovereignty or strategic autonomy.

[Sam Schechner]

There's a race by countries to make themselves friendly for AI. I think everybody wants to have AI that's based in their area. It's almost a sovereign imperative. You think if this technological revolution is going to upend businesses and industries globally, you want some of it where you're based. And so you see companies like OpenAI doing deals with places like the UAE, and you see Jensen Huang of Nvidia going around the world selling sovereign AI, if that helps him sell chips. France's card to play in this is something that French President Emmanuel Macron said spoke about in February when there was an AI summit here in Paris, which is it's nuclear power. It has a surplus in energy, and these chips use a lot of energy. So being in a country where there's energy to spare is something that's valuable. And you see investments from private actors, from governments, including the uae, in building AI campuses here in France. And that's something where Mistral is hoping to capitalize on that. They actually have the models that run on those tools. And so when you have OpenAI and Mistral end up being major players doing this kind of thing outside of the.

[Victoria Craig]

Us that was Sam Schechner, who covers tech for the Wall Street Journal. Coming up, can technology from the 60s solve the modern problem of severe water scarcity? We look into that after the break.

[Hrithika Gunner]

Enterprise AI is an unstructured data problem at scale. How does generative AI address it? Hrithika Gunner, general manager for data and AI at IB, explains.

[Unnamed Speaker]

Think of this as emails PDF PowerPoint decks that sit in an organization. Generative AI has allowed us to unlock the opportunity to be able to take the 90% of data that is buried in unstructured formats, which really unlocks a new level of driving data and insights of that data into your workflows, into your applications, which is essential for organizations as we go forward.

[Victoria Craig]

More extreme weather patterns, decimation of the world's aquifers, and growing urban populations, all of those things threaten to make water scarcity a much more acute problem in the coming decades. But a technology first floated, or rather sunk deep into the ocean in the early 1960s is offering a possible solution. WSJ tech columnist Christopher Mims has been looking into this Christopher, what is this not so new technology for getting clean water? And why is it getting fresh attention now?

[Unnamed Speaker]

So this desalination technology was invented in the 1960s, but it wasn't viable then because in order to make it work, you have to put the desalination plants at the bottom of the ocean, 400 meters down. And the reason you want it down that deep is just that the water's pretty clean and the water pressure is very high. And the way that modern desalination works is you're pushing water across a membrane with tiny holes that only admit water molecules. And the holes are so tiny that they don't let salt through. And that's how you desalinate water. So the whole idea is, why don't we use the enormous pressure at the bottom of the ocean to push seawater through this membrane? And yeah, you still got to pump some fresh water up to the surface, but it just takes a lot less energy. And that is the real bugaboo of desalination. It's why it's not ubiquitous. It just requires so much energy. It's the most expensive way to produce water.

[Christopher Mims]

Yeah, I was going to say it's a difficult and a costly process. So what about this technology is making it viable now?

[Unnamed Speaker]

Ironically, it's the oil and gas industry that's making this technology viable now. There's been so much drilling and exploitation in the Gulf and in the North Sea and in other places like that that you now have affordable, available, capable undersea robots and other types of technology, pumps, power cables, whatever that have been tested and work at great depths. And a lot of these new deep sea desalination companies are coming out of a place in Norway, around Oslo.

[Victoria Craig]

Tell us some of the ways that.

[Christopher Mims]

These companies are testing this technology in this way.

[Unnamed Speaker]

There are a handful of companies doing this. They all have pilot plants somewhere, either under the ocean or in a reservoir. One of them has this cute little 40 ton pilot plant that they are supplying water to a boutique cocktail ice company with. There are more serious applications. One is about to go into production at an offshore drilling facility in Norway called Mongstad, where, you know, if you have a platform out in the ocean, you still need fresh water there for your workers. There are islands in Greece that are talking to these companies. One of these companies, which is based in the US called Ocean well, is in early conversations with the state of California to put these offshore and help with water stressed cities in California like Los Angeles or Huntington Beach.

[Victoria Craig]

So what will it take to make.

[Christopher Mims]

This technology applicable on a much larger scale and how big is the need for desalinated water globally?

[Unnamed Speaker]

Globally, about half of all humans on Earth have at least one month out of the year where they experience severe water stress, according to the United nations. And something like 2 to 4 billion people are permanently water stressed. And this is just getting worse. But their promise of this is going to be significantly cheaper than conventional onshore desalination that has yet to be tested. And when you put things at the bottom of the ocean where we don't really know what the conditions are like long term, there could be big temperature fluctuations, there could be fluctuations in salinity, there could be seasonal changes in deep water currents that we don't know about, and all of those could affect the performance of these plants. And so if they can't produce water with significantly less energy and at a lower cost than conventional desalination, then this whole technology is a dead end.

[Victoria Craig]

That was WSJ tech columnist Christopher Mims. And that's it for Tech News Briefing. Today's show was produced Julie Chang with Deputy Editor Chris Inslee. I'm Victoria Craig for the Wall Street Journal. We'll be back this afternoon with TNB Tech Minute. Thanks for listening.

[Hrithika Gunner]

How can companies build AI they can trust? Here again is Ritika Gunner, General Manager for Data and AI at IBM.

[Unnamed Speaker]

A lot of organizations have thousands of flowers of generative AI projects booming. Understanding what is being used and how is the first step. Then it is about really understanding what kind of policy enforcement do you want to have on the right guardrails on privacy enforcement. The third piece is continually modifying and updating so that you have robust guardrails for safety and security. So as organizations have not only a process but the technology to be able to handle AI governance, we end up seeing a flying wheel effect of more AI that is actually built and infused into applications, which then yields a better, more engaging, innovative set of capabilities within these companies.

[Hrithika Gunner]

Visit IBM.com to learn how to define your AI data strategy.

[Sam Schechner]

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