We have some very strong local clusters in a range of industries: biotech, energy, software engineering, and more. And some extraordinary local talent. The heads of AI at Microsoft and Meta are from the UK and France, and innovation teams at many of the world’s largest companies are European.

We have cutting-edge knowledge in Europe, very innovative people, and a lot of groundbreaking technology. And then there’s the European economy itself. It’s more inclusive than the US, with a more generous welfare state and more focus on sustainability transition and the green economy. There are a number of things that are attractive about the European economy as a contrast. I’m not saying it’s better than the US model—it’s different. And there are real benefits for innovation and entrepreneurship.

There are three things we lack. One is a broader European market or approach. We’re too fragmented. 27 different state policies won’t cut it. Europe must devise a joint competitiveness strategy and invest in the areas of the economy where we can have a real advantage.

The second piece is that we lack “guts”, for lack of a better word. Some of these American success stories came about because they took for granted that they would dominate the world with their tech and their strategy. That’s harder to come by in a European context.

The Draghi report was a huge wakeup call. In Draghi’s analysis, the comparative reduction of EU productivity stems directly from a lack of investment in technology; but Europe remains competitive by most other measures. If we exclude Silicon Valley and Seattle, Europe is actually more productive than the US. Silicon Valley has been there since the late 1930s and we can see the long-term cluster effects of academia, capital, tech innovation, and people gathering around the innovative economy.

We have clusters in Europe too, but they’re fragmented by country, and building these clusters is about the co-location of academia, innovation, capital, business leadership, lifestyle, and all of that acting together in the long term to attract talent and capital.

Yes, for Europe to compete with the US and China we need to make the most of our relevant advantages on a European level, not one nation at a time. Authoritarianism and protectionism are both on the rise. Some people in Europe are happy, but the air under the wings of authoritarians is something we should all be wary of. There’s the notion of an ideological battle, but I think it’s largely misunderstood. The meta issue is really the crisis of trust in institutions.

It starts with education. We have a good education system in France. We have excellent engineers and are already leading in areas like AI. But I see very few comrades from engineering school who have created their own companies. Engineering schools are trying to create engineers rather than leaders. They’re not teaching people how to launch and lead successful companies. So we need to adapt the curriculum of these universities.

We need more scientific people in leadership roles and founding companies. And we need to teach more soft skills around management, hiring, negotiation, and running your business. Not just the engineering hard skills that many of them already have.

It would be great if Europe could act more as one entity and not 27 different states. We are far too small to compete with China and the US, so we need to encourage unity.

A good initiative right now is a single corporate status to let companies operate in all EU countries. That would be a great thing and would solve a lot of issues. We also need better equivalencies between the licenses you get in each country. Once you get them, licenses should be valid in all EU countries.

We should regulate smaller and better. GDPR is a classic example: Europeans lose something like 500 million hours per year just clicking on useless cookie banners. Europe could have focused this regulation on the six browser companies most people use. Millions of businesses had to spend hours with GDPR lawyers to set up cookie policies. It doesn’t seem to have had any impact on spam or privacy, and it’s wasting a huge amount of time and energy for companies.

Artificial intelligence is similar. We should regulate only when it’s necessary and not before. We need politicians who will make the tough choices and regulate less and better.

Since 2020, from my point of view, volatility has exploded. You had Covid, political instability, wars, economic crises, and energy crises. And it doesn’t seem to be slowing down. To be prepared, you need to diversify, especially internationally. The more geographies you’re in, the more you can cope with issues in any one of them. Having a portfolio attitude to risk is good. You need to be one step ahead and have mitigation plans in mind.

You also have to be obsessive about cash efficiency. Be lean, and don’t just throw money at problems.

Certainly not. We’ll only see continued investment. The vast majority of this is coming from the US – revenue growth there is much faster than in Europe right now.

We’re going to see continued investment in AI hubs around the world. London and Paris have the potential to be these hubs, as do other cities in Europe. But today, a lot of growth comes from the US, and those networks are critical for our next phase.

There are still real technical challenges to solve. The most famous models require enormous amounts of training data, which puts strain on servers and energy resources. There’s a trend towards teaching models to be just as good with much smaller data sets. These use less compute and therefore less data. This will make AI tools faster, more efficient, and much cheaper in the long run. Plus, it’s essential for sustainability.

We’re also seeing shifting demands towards the evaluation step in models. Evaluations are like the unit tests: how do you know that the model hasn’t regressed and still provides quality? So beyond building the models themselves, there’s more focus going into their maintenance and continued performance.

No, LLMs will serve as core infrastructure, but we're also seeing a growing ecosystem of smaller, open models and distilled versions. The future will likely have both: large models providing the backbone, while specialized models handle specific tasks. Organizations are recognizing the value of this diversity, selecting models based on actual needs rather than their sheer size and power.

The "hype machine" shapes both public expectations and research directions in AI. But the focus needs to be on responsible development rather than just technological advancement.

I like Jeff Bezos’ approach: focus on the things that never change. For us that means the breadth and quality of our audience, and the speed of innovation through our platform. We can always improve the data and find new ways of interpreting it.

We’re still in the early days of companies deriving real value from AI tools. And for most people, it’s still too hard to do anything. So it remains a curiosity, not a core tool. As soon as things become simpler, the demand is just going to explode. I’ve personally seen this in healthcare. We used AI to simplify workflows and track patient outcomes. The change was completely amazing – people refused to work without it afterwards.

I’ve lived in Silicon Valley and worked at Nvidia, and I see the advantages of living here in Europe. The key point is, you can’t build a Silicon Valley company in Europe, and you can’t build a European company from Silicon Valley.

We chose our headquarters in Paris for a few reasons. First, there’s strong talent here. Many of them have tasted the Silicon Valley spirit but are still European. They want to be here and build great things in Europe. People are starting companies here all the time, including in AI. Mistral has proved that you can go big from Europe in this industry.

We’re fundamentally a solutions company. Even though we’re starting with software, we need to retool everything. This starts from the workload down: networking, storage, computers – everything.

It’s difficult to defend software in AI infrastructure. The hardware people will keep coming from the bottom and eating up the software. That’s why full solutions are the best approach.

Everybody is running on Nvidia today, but we’re going to see lots of specialization.

The energy required today is huge and unsustainable. But that’s because of the way we’ve built models today: we started with solutions that are generic enough to address all workloads. But you can have more customized workloads that optimize things by a factor of 10. There’s a massive movement towards more efficient models. New open source models are very efficient, and companies are now emerging to build the chips to power them.

One of the biggest misconceptions today is that you can just simply grab an off-the-shelf model or foundational model, and instantly create a high-value product. But when you deep dive, this is not true at all.

The fact that you need to create a tool that solves a very specific problem. For us, it's that the furniture industry has a very specific pain point that needs to be solved: product photo shoots for 10 objects can cost up to $30,000 due to logistical issues and creative costs. Understanding that, and catering to that very specific need is what gives your build relevance and attracts investment.

Absolutely. AI tech isn't just a plug-and-play solution, where you can use a model like Chat GPT, plug it to anything, and it works. You have to train models to have deep expertise in order to be effective in complex domains. The higher the level of expertise, the more specific the focus, the better it will work. Adjusting our model in this way meant we could get a better quality of photorealism into our imagery and offer greater flexibility and control to our users.

We've been successful by focusing on one specific vertical. Our model performs very well in the furniture industry, and we've been able to achieve that by focusing our attention on training furniture products, which gave us relevance.

Definitely. We're here in Europe for many reasons. I think Europe is a great place to create a startup, especially Paris and France, because you have so much support to build in terms of accessing government funds. And on the tech side of things, the pool of talent here in France is probably the best outside of the US. And that's key to starting a successful business.