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Issue 1

The Sachs Plan for Unity

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Founder of P Capital Partners, Vice Chair of the Open Society Foundation and a founding Council Member of the European Council on Foreign Relations, and patron of numerous foundations for business and political progress, Daniel Sachs is a leading voice promoting the business case for democracy and calling for a unified European growth agenda. Here, he outlines some of his thinking on a unified European innovation strategy.

7 Min Read

“Europe remains competitive by most other measures. If we exclude Silicon Valley and Seattle, Europe is actually more productive than the US.”

Europe presents a plethora of exciting investment opportunities. What would you say are its major advantages?

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.

Finally we’re used to dealing with regulations. Many business leaders see this as a crutch, but there are ways to use regulations to our advantage. We actually have a headstart in dealing with privacy laws, human rights, and climate legislation.

What do you think needs to change to maximise European investment in technology?

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.

And then we have a lack of growth funding. There’s lots of funding for mature businesses and we have a lot of seed funding. But most of the best ideas reach the growth stage and get funded by US investors. The kind of innovation we need is partially unicorn-level, and truly disruptive. But a lot is more capital intensive, and slower to develop. Hydrogen technology or hardware development – this can’t be 100% funded by equity.

There’s quite a lot of low-hanging fruit here. Institutions and the private sector can get more involved, but it can also be incentivized by government guarantees, the European Investment Fund, KfW in Germany, and so on. A lot of those systems have been focusing on seed funding, which is now a very well-functioning part of the market. But not enough is going towards scaling up promising technologies and companies.

How do you characterise the European ecosystem in comparison to the US and China?

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.

It’s how you share knowledge, who you invite to participate. And then these things become organic over time. A lot of clusters have come up through academia and innovation first, and then attracted the business people. We should be interested in deepening the clusters in Oxbridge, Paris, and so on, and making them beneficial at the broader European level.

Do you think a unified Europe is a realistic and necessary goal?

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.

There’s no silver bullet to fix this, but it starts with political parties and institutions getting serious about radical renewal and connecting with people broadly. New faces, new voices, and new ways of interacting with people. Over time, that builds social cohesion, and less extreme, polarizing, and toxic outcomes.

The political forces in the center need to get their act together. They have to get radical about their approach to break through to people. We need a lot of institutional change in the democratic and political setup, and I see it starting to take shape.

Let Innovation Grow

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Issue 1

Let Innovation Grow

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Philippe de la Chevasnerie is Founder & CEO of papernest.com, a European scaleup which simplifies utilities and subscription management for households and small businesses. Founded in 2015, papernest has grown rapidly to over 900 employees. The platform helps more than 1.5 million users gather, subscribe, and cancel services across France, Spain, and Italy which, understandably, means that Philippe supports a more unified Europe.

5 Min Read

“It would be great if Europe could act more as one entity and not 27 different states.”

What do you think Europe can do to promote further growth?

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.

And I do think we would benefit from a shift in mindset. We can’t do everything: increase wealth, work less, defend ourselves, manage the climate transition, and more. If we want to take the top position, we will have to make hard choices. We need to decide on our priorities and encourage people to push themselves towards them.

Is political change needed to facilitate this?

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.

Right now we need 27 different licenses just to operate across Europe, which is a huge hurdle. On top of adapting to different languages, cultures, and client bases, you also have to deal with local regulations.

How can Europe change its reputation for over-regulating?

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.

We’re trying to build a complex system to avoid just executing the obvious initiatives (instead of mainly taxing oil, gas and coal, governments create very complex layers of incentives to reduce emissions instead of relying on price signals). Regulations become very complex, and ultimately useless.

What opportunities do you think will emerge from the current economic and political volatility?

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.

Be very willing to adapt. It’s about risk taking and the willingness to try new things. We had to pivot almost right away when we launched.

Finally, create a great team. A small team of highly engaged, hard-working people will really drive efficiency. We have to be proud of working hard and giving a lot for the business to succeed.

Open Models, Distilled Data

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Issue 1

Open Models, Distilled Data

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Phelim Bradley is CEO of Prolific, a technology company building the biggest pool of quality human data in the world – and the ultimate platform to access it. Phelim is also a Venture Partner at Pioneer Fund, and worked in genomic medicine and computational biology before founding Prolific.

5 Min Read

“We’re going to see models that excel in specific niches, and can truly bring the same level of expertise as experienced employees. That means training models on much more focused data sets.”

Has AI investment and enthusiasm peaked, and do you think we’re likely to see AI fatigue soon?

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.

What do you think the next steps are for artificial intelligence?

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.

But the biggest change we’re working on involves more investment in domain experts and specialists. Large-scale models like GPT are good for broad tasks but aren't perfect for every use case. When training the latest AI models or conducting research, general data isn't enough, and you need responses from people with specific expertise or characteristics.

We’re going to see models that excel in specific niches, and can truly bring the same level of expertise as experienced employees. That means training models on much more focused data sets. And it also means consolidation – infusing AI into industry tools and using real user data from those, rather than broad internet scraping.

High-quality, targeted data from vetted participants leads to more accurate results and helps catch potential issues early. Companies like Carnegie Mellon and Layer 6 have used targeted participant pools to test and improve their AI models.

Does this mean we’ll see an end to LLMs?

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.

What role does journalism and its “hype machine” play in AI’s next steps?

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.

The real challenge is making sure AI systems are deployed responsibly, which requires attention to data quality and diversity of feedback and input. Transformative change often comes in waves of innovation that are more focused on practical applications and specific use cases. These may generate less hype, but can have significant impacts if not deployed responsibly.

How do you focus business strategy in an industry that’s evolving so quickly?

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.

But this requires a culture of customer obsession. Because it’s not up to us to decide which data is best, we need to understand and solve customers’ problems, whatever they are.

From Curiosity to Core Tool

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Issue 1

From Curiosity to Core Tool

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Dali Kilani is Co-Founder and CTO at FlexAI, delivering AI compute by rearchitecting infrastructure at a systems level. He’s also an angel investor and brings experience from Nvidia, Lifen, and BCG.

5 Min Read

“There are dozens of companies similar to ours in Silicon Valley. We’re a bit special here, and that opens doors.”

What stage of AI investment and enthusiasm are we at right now?

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.

Things have to plateau in certain use cases, but there are plenty of dimensions where we’re not good enough yet. Things like AI software developer agents are coming. We’re never done. If you give researchers more compute, they’ll find greater things to do.

What are the advantages of building your business in Europe?

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.

There’s also a lot of institutional support. There’s this rich mix of VC community, government, partners, and academia. For deeptech that’s incredibly important. Their doors are more open here than elsewhere.

Finally, it pays to be in a small pond – for now. There are dozens of companies similar to ours in Silicon Valley. We’re a bit special here, and that opens doors.

What does it mean to be an AI infrastructure provider?

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.

Full solutions and tackling use cases completely is where the game is played. Nvidia is now the leading networking and data center, with the best software stack, and they actually built their own systems. You could spend $50 million dollars with Nvidia today to build your AI stack, and not spend a single dollar with anybody else. That’s where the future is, and that’s what we’re focused on.

Are the climate change concerns with AI legitimate?

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.

And then there’s actually using AI to discover new climate tech. Schneider is doing this already here in France. We’re also seeing investment in nuclear energy for AI among the biggest players. The market is incentivized to be more efficient because energy is expensive.

The key thing is that AI is still so new and developing so quickly that the climate footprint today is much higher than it will be eventually. And one of the key imperatives in developing this tech is to make it more efficient. There’s already a huge emphasis on this today, and that will continue.

Scaling Verticals with Deep Expertise

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Issue 1

Scaling Verticals with Deep Expertise

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Nabil Toumi is Co-Founder and CEO of Presti, a pioneering startup revolutionizing product photography for the furniture industry through generative AI and diffusion models. Presti provides tailored, high-quality imagery solutions that significantly reduce production time and costs. Previously, Nabil held various roles as a data scientist and analyst, including at Uber.

4 Min Read

“AI tech isn't just a plug-and-play solution. You have to train models to have deep expertise in order to be effective in complex domains.”

What’s the biggest misconception people have about building an AI company today?

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.

For example, here at Presti, we've run over 1000 model trainings before landing on the right one that achieved the results that really worked for our customers in the furniture industry. And that’s because, if you want to build something relevant, you need to really solve a big problem that provides clear value for your customers. I think this always comes with deep expertise in the domain you're working in.

The AI ‘hype machine’ is in full swing, but you’re in the trenches building. What’s something you think isn’t talked about enough?

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.

We’re seeing a shift toward more specialized AI applications. Do you think the era of general-purpose AI is coming to an end?

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.

How do you stay ahead in such a fast-moving industry?

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.

The second thing, on the product side, was to create something bespoke with a targeted UX and feature set for that industry that really meets their needs. It's not just about the AI tech, but the user experience, too.

And finally, on the commercial side, being very focused enables you to engage in good storytelling for your users, where you can help them to recognise themselves and their needs. That really allowed us to build a strong network within a specific industry, which makes you way more relevant than if you created a horizontal solution.

If you had to do it all again from scratch, would you still build Presti in Europe?

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.

Eliminating the Threat

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Issue 1

Eliminating the Threat

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Gianni Cuozzo is Founder and CEO of Exein, embedding better cybersecurity into IoT devices and hardware. He’s also Chairman of Aspisec, and has worked with NATO on cyber defense.

5 Min Read

“Today you have people making conscious, calculated changes to code and functions. In the future, this will be done by agents… which will only make cybersecurity a bigger trend and concern.”

What’s the main driver behind the current rise in cybersecurity attacks?

Our world is so much more connected today than in previous eras. And specifically through “internet of things” (IoT) devices. From an attacker’s standpoint, it’s heaven.

It’s not that the number of attackers has increased. There are easier and more distributed attack vectors, and the architecture is more open. There’s a really close relationship between web technology and embedded systems.

The other issue is the asymmetry between attackers and defenders. Most defenders have standards, and most attackers do not.

It’s not only about money. Before, most of the attacks were about stealing money, credentials, or information. Now, some of the attacks in the current geopolitical climate are about destroying systems. These will obviously have a major impact on all our lives. We’re not only talking about standard criminals – there are also state-sponsored attacks happening this way.

Today you have people making conscious, calculated changes to code and functions. In the future, this will be done by agents. No human will have time to read and verify all the data and code that they will generate. And we’ll see lower-quality code in the future. Which will only make cybersecurity a bigger trend and concern.

Nowadays we have generative AI that can search through massive data and find bugs, which also creates opportunities for hackers. In the past, it took attackers time and effort to find weaknesses in code. GenAI can do it at scale far more easily – thousands of websites at a time.

What are the most pressing cybersecurity challenges facing tech companies right now?

It’s a very hard, and very expensive, problem to tackle. It requires lots of testing and retesting. It’s become very complex to build secure systems. Everything works perfectly until someone exploits it, and attackers don’t follow the same mentality as an engineer within a company.

Your engineers can do the right things; using updated licenses and software and following best practices. The problem is, the last thing you want to do in software is make changes. The goal is for everything to run stably. Often, in the time between testing and production, the libraries you’ve relied on which were good before are no longer good enough.

And no company is built up of phishing technicians. You have marketers, sales, and other roles who aren’t native cybersecurity experts. It’s an incredible issue for companies monitoring and using a large number of devices.

What can companies do to defend themselves?

There are a range of pressure tests you can run for your business. We do phishing testing, ‘red team’ testing, and also physical entry testing – seeing how easy it is for a person to enter your building and access important data.

We’ve seen large banks hacked because someone physically connected to their local networks. Hackers told a good story and the security people let them in. It was a sophisticated attack from a human perspective, but very simple technically.

I would also encourage every company to run bug bounty programs. You offer a bounty to any hacker who can identify weaknesses and bring them to you. First, this is much cheaper than the cost of a real, malignant attack. Both in terms of money and reputation. But you also put these guys on your side.

Budgets and software on their own don’t solve issues. Most software doesn’t work – they’re just products to make more money. The only real option is a well-educated workforce, and a continued dedication to reducing cyber attacks.

A Pan-European Platform?

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Issue 1

A Pan-European Platform?

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Robin Wauters is Founder of Profoundo, a boutique communications agency for deep tech companies. He was a journalist at TechCrunch and The Next Web, before founding Tech.eu. Here he explains how Europe might build a new tech media ecosystem.

5 Min Read

“If you’re in media and want to be a high-quality content supplier, it always has to hit the mark. It’s a very high bar.”

What were the circumstances that led to you establishing Tech.eu?

I was a journalist for Techcrunch and the Next Web. They did (and still do) a great job covering the global tech scene on a broad level. But I felt a lot of excitement around the European ecosystem, and nobody was covering it properly.

There was good local journalism for each local cluster. You could find great coverage of the Polish tech scene in Polish, or the German ecosystem in German. But nothing handling the broader European story, and not enough English-language coverage of these clusters.

When we launched Tech.eu, there were English language publications covering specific European markets. We wanted a pan-European one.

I wanted to tell positive stories and talk to people and investors who were doing things nobody else was doing. There were really exciting things happening, and I didn’t think people were speaking to that.

Why do you think tech journalism is struggling in Europe?

The inherent problem with building media companies is unfixable. We can still deliver high-quality journalism in niches, and build services around those. But it’s very difficult for large media companies, because there’s just so much to cover. This was a long time coming, long before the internet.

There’s also this struggle over the notion of quality. What is high-quality journalism? Everybody wants it, but we all define it differently, and only a very small percentage will actually pay for it. They dictate the terms, and the media companies don’t any more. So investing in high-quality journalism is difficult, because the business model is so hard.

If you’re in media and want to be a high-quality content supplier, it always has to hit the mark. It’s a very high bar. And you need to pay good people, which brings us back to the business model. How do you encourage people to pay for it?

The market in Europe is tougher than the United States, because we’re very fragmented – nations and languages are different. Even for an English-only publication, you still need sources and insights that maybe don’t speak or read great English. So that’s a challenge.

I’m proud that we built Tech.eu on top of me actually visiting places like Moldova and Riga. We didn’t get a huge audience or respect from it, but I learned a lot about the ecosystem and the entrepreneurs who became well known now. And you can’t do that from behind your computer. You have to go and attend things. But again, who’s going to pay journalists to do that?

Are there other key challenges to overcome?

I miss generalist media with multiple viewpoints. But human nature and the changing discourse has made it difficult to maintain a balanced, informed view. It’s very hard to listen instead of speaking all the time. And newer generations are very critical, but also very siloed in how they consume media.

For 15 years, Twitter was my go-to. Not so much now. It’s not really that the platform has changed, it’s that the conversations have. The inputs have changed, which changes the output.

AI is already changing the media business profoundly. It’s not just about content generation. I can create avatars, do podcast interviews, and write copy without doing it myself, with maybe 5% human input. So there’s a race to the bottom in terms of content. But now’s the time to invest more in the AI tools that actually support high-quality journalism, not the ones that propel the race to the bottom. I fear we’ll have thousands of low-level media companies, and a few at the top, and nothing in the middle.

What could a better business model look like?

I’m optimistic about the ways we can bring money in. You don’t have to rely only on subscriptions and advertising. Things like market intelligence reports and events. I don’t think we’ll ever stop craving interactions and human connection. But to succeed in European tech, I think you need to be pan-European.

Lessons in Sustainable Tech

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Lessons in Sustainable Tech

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Matteo Vanotti is CEO of xFarm Technologies, a tech company focused on digitalizing the agri-food sector, providing innovative tools to support farmers and stakeholders to manage their businesses.

5 Min Read

“To manage all this complexity, digital technologies are the only solution to keep track of what is happening and start making data-driven decisions.”

In your experience, do farmers take sustainability seriously?

Absolutely. In Europe, one in twenty farmers disappears every year due to a lack of economic sustainability. And climate change is a huge driver of economic instability. 95% of farmers work outdoors, fully impacted by climate change. The frequency of bad climate events has certainly increased in recent years. Rain has been much more concentrated in a few major events, rather than distributed throughout the year, which has bad impacts for the soil, yield and farm maintenance. These trends only seem to be increasing at the moment, so the only real solution is to adapt.

Farming efficiency is directly correlated to climate and sustainability. That’s the answer to making farming more sustainable ecologically – to be more economically sustainable too. If you’re efficient with resources, you are also sustainable from an economic perspective.

To what extent can technology help to address these challenges?

Technology is not a definitive solution, but it can be an ally. To try to anticipate issues and mitigate risk. Most of the time, it’s all about making the right decision based on last-minute changes, like the weather, market trends and input costs. Clearly, adapting agronomic practices with things like regenerative farming – a trend at the moment focusing on restoring the natural fertility of the soil – is another way to mitigate harm. Good practices like regenerating the soil will also have a positive climate impact, as more fertile soils will require less fertilizers and better manage climate events. To manage all this complexity, digital technologies are the only solution to keep track of what is happening and start making data-driven decisions.

Farming is one of the last industries to be digitized. Only one in ten farmers uses technology to be more efficient. We can create a baseline and work with farmers to improve practices, methods, and get much more information. We can optimize the use of inputs like water and feed, too

Irrigation, for example, is fundamental to farming and quite a complex topic. How much water should you give to each individual plant in different fields and with different soil? That’s very hard to estimate and forecast. Today, with sensors and satellites, we can have real-time data and really know exactly how much water is needed and when. That means farmers can actually plan ahead and forecast resources as well. On average, farmers save 20-40% on water usage this way, and are much more strategic about where they put water.

And of course, using less water today helps to prepare better for drought, which is one of the main issues impacting Europe over the past two or three years.

We also help farmers with fertilizer use. Fertilizers have one of the highest carbon impacts for farms. So we use satellites to monitor the health of each field, and then can create “prescription maps” to treat specific areas. These maps are sent via cloud to the tractors, which can then adjust the amount of fertilizer spread per square metre, based on which parts of the field need it most. We can optimize by 5-20% the amount of fertilizer used, which then has a huge impact on carbon emissions.

How do consumers help to drive change?

Marketing and advertising has a real contribution here. Customers are really buying along sustainable lines, and this will continue.

We saw something similar with organic production a decade or so ago. Sustainability is now a major topic in food production. So we’ve moved from organic production to sustainable farming and supply chains. Putting a label is not enough. Changes need to be made in the field, and data is the right way to create transparency with the end customer, giving them the right tools to make sustainable choices when they’re buying their groceries.

Looking to the Stars

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Looking to the Stars

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Hélène Huby is a rocket scientist, engineer, and Founder and CEO of The Exploration Company, which exists to make space exploration more affordable and sustainable. Hélène was previously a VP and Head of Innovation at Airbus, and Program Director at ArianeGroup.

5 Min Read

“If I weren’t optimistic about Europe, I wouldn’t have founded this company here. I would have just moved to the US.”

Europe used to be a leader in space. How did it lose its status & what can it do to get it back?

In Europe, we’ve lacked ambition in space for quite a while. We haven’t had a structured European space strategy for more than 25 years. 10 years ago India was way behind us, and now they’re five years ahead because they have a very clear space strategy and focus.

Our cooperation with the US hasn’t been one of equal contribution. We’ve partnered in a junior role, building backup systems, but not the most complete or complicated pieces of technology. So every year we invest billions into reproducing the technology we already know and understand, without developing new ideas.

SpaceX arrived with a different industrial setup and approach, and all the big players in Europe haven’t been able to adapt. It’s like when the internet arrived and changed everything. It’s a completely different way of designing, developing, and funding technological innovation.

Do you think Europe can become a leader again?

Absolutely. If I weren’t optimistic about Europe, I wouldn’t have founded this company here. I would have just moved to the US.

But I could see more and more countries wanting to send astronauts into space, and to build new space stations. And we can count on one hand the number of vehicles that can actually go into space and bring astronauts back safely. So why not build one here in Europe?

We have very good competencies here in Europe. The history of Airbus proves we can achieve things when we cooperate between countries. And there are hundreds of space startups in Europe. It’s a real space renaissance.

I would love to see a European capsule take Europeans into space. Every rocket that takes off is a miracle of technology. We can see with our own eyes what we can achieve when we work together with the same goal, and I’d like the whole world to see what Europe can achieve through our space program.

What mindset and investment shift is needed to let European space startups take off?

If you want to go fast, you have to take risks and shortcuts. Perhaps it’s going to fail, but you’re going to learn so much in the process. We foster this in the company by putting huge pressure on planning.

We built our first two capsules alone, very fast. But our clients aren’t used to such quick decision making yet, so we’re not completely there yet in Europe. There’s a big gap between what the top leaders say and the operational levels, but I believe we will all get there together as long as we share the same goal and strategy.

In space, the biggest risk is technical execution. A mistake can cost us months. We therefore use a software method – start small, learn fast, and iterate. First, it was a baby capsule: 9 months, $2 million. And we did it. Then we did a teenage capsule: 2 years, $20 million. So now we have a lot of trust in our ability to do the full thing and stick to our cost budgets.

We went to the German and French agencies within the first three months, asking them to buy a little piece of our mission. The alternative is they continue to give crazy money to SpaceX, rather than invest in a European alternative. They’re taking a risk, but if we succeed it’s a huge win. As long as we respect each other and value relationships, and have the same goals, it will happen.