One of the regulatory burdens, or rather one of the regulatory problems in Europe, is that fundamentally, every time you enter a European country, you have to open a new entity, understand a new stock option regime, and understand a different labor regulation. This means you quickly need a team on the ground. I've signed hundreds of documents to open entities in about ten European countries. I've opened dozens of bank accounts because you generally need an associated bank account. You have a whole set of national regulations that are not unified. You have a tax system that is obviously not unified, whereas it absolutely should be if you want employee incentive systems that make sense. So we try to patch things, we try to do things as fairly as possible, but we end up with tax situations that are frankly disparate between countries. That is relatively catastrophic. You can't have a unified market if you don't have a form of unified taxation, a form of unified social law, and so on. That's the first thing, I would say it's the main burden.
Then you have a stack of regulations that are more or less consistent with each other and that force us to document a lot of things. You have the GDPR, you have all the laws on copyright and text and data mining. You have the AI Act, which isn't implemented yet but will be starting in August. All these things say more or less similar things. They touch on data, personal data, what's on the internet, and they don't say exactly the same thing. They require different documentation. It's implemented by 27 different enforcement bodies in Europe that are more or less strict depending on the country. And so I end up with a compliance team of five people. That's manageable for us today because we're big enough, but if you're a new entrepreneur in France and you look at all this, and you also look at the atmosphere and the fact that people are celebrating having imposed regulation on the AI Act in early 2024, you say 'I'm going to the United States,' and that's what happens, they go to the United States.
We've overcome this aspect because we're big enough. It goes into overhead costs, it remains very painful, but the main thing is that you lose a lot of entrepreneurs who go elsewhere because they're afraid. You have investors who say, 'No, Europe has lost anyway, it regulates too much.' And you have a whole narrative that is widely used by the United States saying Europe is losing because it's just bureaucrats in Brussels who don't know how to do anything, they don't know how to innovate. And in fact, it's a destructive narrative because it's also internalized by Europeans. It's a form of colonialism, if you will. But the point is that we need to reverse this narrative. To reverse it, we also need to think about having simpler, more unified regulations that allow us to go faster. So that's on the subject of regulation.
I spoke about market fragmentation as an asset. It's not an asset, it's rather a hindrance. It means you need different teams selling everywhere. It means you have about 60 telecom operators in Europe. You have three in the United States. That means they have 20 times more budget overall. So when they make an AI investment, they can put a lot of money on the table. And that's how you find that with American technology, startups, the first thing they do is sell to other startups because that recycles venture capital money, and then they sell to huge American companies that buy very quickly, and that's how they scale. Once they've scaled, they export to Europe where, since no one emerged in time, they take the whole market, they buy the few companies that know how to do things, and they end up consolidated with the whole market. That's how it happens.
In Europe, we don't have that because there's much more viscosity, because companies are smaller, and on top of that, you have to speak 20 different languages, manage 27 different regulations. So it's not an advantage. However, once you've done it, European companies are more partnership-oriented, they have more constructive approaches. Sometimes they are champions, we're lucky to have many industrial champions in particular, and they are good partners for us. And since these are partnership approaches, it's difficult for Americans to replicate them. So in a way, it's revenue that is relatively defensible. So the viscosity plays against you at first, but then it plays in your favor when you have a competitor trying to take the market. But overall, it's rather to our disadvantage. You'd prefer the market to be much less fragmented.
Next, last point on regulation as a defense and as a way to counter the Americans. I think often the intention is good, meaning saying we'll make sure it favors our European startups. But I think if we look at the entire history of what we've done, that has never been the case. And a very simple reason is that regulation fundamentally puts an overhead on you that, to overcome, you need to be big enough. And so if you don't have big enough companies with such a large regulatory burden, you end up with American actors winning. So regulation favors the big players, and that's even more true in technology. And so any discourse saying regulation can defend us, I think it's a bit like the road to hell is paved with good intentions.
There is one area, however, where we should be much better, and that is in ensuring that public demand is recycled on European territory. That is, used to do R&D on European territory. This applies to defense, it applies to the entire public sector. I think there's an awareness that isn't necessarily a regulatory awareness, but rather a political awareness that this is the thing to do, that it's what the United States has been doing since the 1940s and it worked very well for them. So, should we regulate this? Maybe we can manage this aspect a bit. It must be done while maintaining very high competition in Europe. We shouldn't be planners on where the state spends, but planners on how things are used. And that way we'll get there. But regulating to defend generally doesn't work.
We build systems that help humans be more efficient, that will automate a certain number of processes while keeping humans in the loop on important decisions. We have a whole team of designers, about ten designers, who think about human-machine interactions, ensuring that when AI summarizes information to aid decision-making, it provides enough elements so the human stays informed. I'm not saying it's an easy subject because humans tend to be a bit lazy, and if the thing does it for them, they think less and less. So there's this subject of keeping them in the loop, of stimulating the human when they're facing the machine. These are obviously subjects we think about.
Then there's a sub-part of ethics regarding engagement in defense. We work with the Ministry of the Armed Forces, we also work with certain allies of France, and it turns out this is a technology that is considered a dual-use technology, so it's fundamentally regulated in terms of exports, in terms of export controls. So all the regulatory framework on export controls applies to us. We don't claim to have an ethical framework, we don't claim to have the legitimacy for a sufficient ethical framework, not a democratic legitimacy as a company. However, we operate within frameworks that have democratic legitimacy, and that allows us to work correctly and not do what we're not allowed to do.
When we work with the Ministry of the Armed Forces in France, we don't claim, unlike other actors, to have oversight over infinite use. Because we don't claim to have the legitimacy to explain to the French armed forces what they can and cannot do with the technology. We can tell them, and we can do it project by project, we can explain the reliability of things and so on. But then, who is sovereign in the use of the technology? It's the army. The army has a democratic legitimacy that we don't have. And so in that capacity, we have a duty to advise, we explain how it works, and I can say that today it's being used in a completely reasonable manner and within the limits of what AI can do.
We must be aware that AI enables defensive capabilities, it makes armies much more operational, it improves operations and so on, it enables defensive capabilities, but it's also absolutely critical in deterrence. That is, you have armies like the Russian army that use AI massively in their drones. If you're not capable of having counters that are even activated by AI, you don't have sufficient deterrence. And so the deployment of AI in autonomous systems in particular, I think we absolutely must not cut ourselves off from. It's absolutely indispensable for having conventional deterrence today. That also means we must master AI from the bottom up.
Then on the subject of cyber defense and cyber attacks, one of our American competitors knows very well how to do fear marketing, but the fact that models are excellent programmers and are absolutely capable of orchestrating attacks, discovering vulnerabilities, and proposing exploits, that's been building for 6 months, it's rising linearly, predictably, it's rising everywhere at the same time. You have another American competitor with a model that does exactly the same thing. You have Chinese actors doing it too, and our models are capable of discovering all the vulnerabilities reported by Mythos, for example. So we work with our clients to help them on these cyber subjects. It's obviously a sovereign subject, and that's another argument for saying we need control over this technology. You can't have the French army's code bases scanned by Mythos. It creates a dependency that is so irremediable that we absolutely must find solutions.
Then, on the subject of time. On the subject of time, I would say we don't have time. I think notably because it's linked to physical constraints. We're talking about natural resources. We're talking about using natural resources to transform electricity into tokens. There isn't infinite electricity in the world. The United States is saturating their electricity to transform it into AI. They're deploying a trillion dollars next year. When they deploy a trillion dollars, it means they want two trillion dollars in return. So they see well that an immense market is being created, and they see that whoever possesses the resource, whoever supplies the chips, whoever possesses the electrons, whoever has access to energy massively, that's who wins.
So today, France has 90 terawatt-hours per year available. There are many things we can do with it, partly we'll do AI. You have actors with enormous balance sheets who have plenty of money to put on the table before seeing the demand to transform electrons into intelligence. But they're going to do it in the next two years. Once they've done it, you have no more electricity. You have to wait for new power plants to be built and so on. So there's a monopolization of European energy resources that is happening, that is accelerating at a crazy speed, and of which we're not aware, and it's really irremediable. Once it's done, it's done.
We already have a demand problem. Because the Americans arrived first on the cloud, they provide all of European industry, they provide the French state, and AI tends to compress the market share for non-American actors. Not only do they grow with the market, but their share also increases. So I think this is something that can be reversed with AI, and what we're starting to see with our clients, with our revenue, with our growth. But the problem is that even if you solve the demand problem, you have a supply problem, because once the supply is monopolized by American actors, suddenly we have no more supply and we can't transform electrons into tokens. And this is playing out in the next two years.
What needs to be put on the table today in terms of investment is tens, hundreds of billions of dollars. And to do that, you need visibility on the market. And the visibility on the market must be indicated by European actors, by European states. Today, it's not indicated massively enough for us to take the risk of deploying 100 billion dollars. So I think we need to become aware of this urgency, and unfortunately, I don't see very well how we'll become aware of it. We're going to manage to build 1 GW by 2029. That's our objective. It's not enough. We should build more. But for that, we need a form of visibility on the market and on demand that isn't the visibility we have today.
And finally, perhaps on the last question, you asked a question about distillation. What is distillation? You take a large model and use it to make a smaller one that will be more efficient. We use it massively because we train large models, which costs us a lot. Then we use our large models to train small models that we serve to our clients because it costs them less to serve. What this means is that it's absolutely indispensable. If you want to know what's in your models and control them, you need to be able to build the largest models. That means you need to know how to train them, which means you need a lot of your own compute capacity, which is pure R&D that allows you to train them. So what this allows us to catch up on... no, it's a technology that essentially reduces costs internally. So we take large models and use them internally to make small ones, and we need the large models, which means we need to invest a lot in them.
