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Mint
20-05-2025
- Business
- Mint
The tech industry is huge—and Europe's share of it is very small
Europe lacks any homegrown alternatives to the likes of Google, Amazon or Meta. Apple's market value is bigger than the entire German stock market. The continent's inability to create more big technology firms is seen as one of its biggest challenges and is a major reason why its economies are stagnating. The issue is even more urgent with the prospect of higher tariffs threatening to further curb economic growth. Investors and entrepreneurs say obstacles to tech growth are deeply entrenched: a timid and risk-averse business culture, strict labor laws, suffocating regulations, a smaller pool of venture capital and lackluster economic and demographic growth. Thomas Odenwald, a German tech entrepreneur, left Silicon Valley in January of last year to join Aleph Alpha, a Heidelberg, Germany-based startup that aimed to go head-to-head with artificial intelligence leader OpenAI. Odenwald had spent nearly three decades working in California but hoped he could help build a European tech giant to compete with the Americans. He was shocked by what he saw. Colleagues lacked engineering skills. None of his team had stock options, reducing their incentive to succeed. Everything moved slowly. After two months, Odenwald quit and returned to California. 'If I look at how quickly things change in Silicon Valley…it's happening so fast that I don't think Europe can keep up with that speed," he said. Aleph Alpha has since said it would move away from building a large-scale AI model and focus instead on contract work for government and businesses. The company said more than 90% of employees participate in its stock option program. Having largely missed out on the first digital revolution, Europe seems poised to miss out on the next wave, too. The U.S. and China, flush with venture capital and government funding, are spending heavily on AI and other technologies that hold the promise of boosting productivity and living standards. In Europe, venture capital tech investment is a fifth of U.S. levels. Marc Andreessen, the U.S. tech investor, posted a meme on his X account that showed an image of big AI players like OpenAI and Chinese rival DeepSeek fighting for dominance. At a nearby table, a figure labeled with the European Union flag sat apart, staring at an image of a plastic cap tethered to a drinks bottle—a new legal requirement in Europe aimed at encouraging recycling. The message: Europe is focusing on the wrong battles. 'This is an existential challenge," wrote Mario Draghi, the former European Central Bank president who was tasked by the European Union's top official to help diagnose why Europe's economy is stagnating. In a report published last September, Draghi pinpointed the lack of a thriving tech sector as a key factor. 'The EU is weak in the emerging technologies that will drive future growth," he wrote. Only four of the world's top 50 tech companies are European, despite Europe having a larger population and similar education levels to the U.S. and accounting for 21% of global economic output. None of the top 10 companies investing in quantum computing are in Europe. The problems go deeper than just tech and reflect a broader truth about Europe: It isn't creating its share of new, disruptive companies that shake up markets and spur innovation. Mario Draghi after presenting his report on European competitiveness to the European Parliament in Strasbourg, France, last year. Over the past 50 years, the U.S. has created, from scratch, 241 companies with a market capitalization of more than $10 billion, while Europe has created just 14, according to calculations from Andrew McAfee, a principal research scientist at the MIT Sloan School of Management and co-founder of AI startup Workhelix. New companies and industries—think autos replacing horse and buggies—allows a country to produce more goods with the same amount of workers, a key driver of prosperity. Europe is dominated by old-school industries like autos and banks that extracted productivity gains long ago. The typical company in the top 10 publicly traded U.S. firms was founded in 1985, while in Europe, it was in 1911, according to the International Monetary Fund. By the late 1990s, when the digital revolution got under way, the average EU worker produced 95% of what their American counterparts made per hour. Now, the Europeans produce less than 80%. The EU economy is now one-third smaller than the U.S.'s and is stuck in low gear, growing at a third of the U.S. pace over the past two years. Digital winter Europe has world-class research universities and a deep pool of engineering and scientific talent, much of which populates top U.S. firms. Spotify and fintech firms Revolut and Klarna are success stories. Venture capital arrived relatively late, but big U.S. venture-capital firms have set up shop in Europe in the past decade, including Sequoia Capital, Lightspeed, Iconiq and NEA. 'Europe is a much smaller market, but that doesn't mean it doesn't have great opportunities," said Luciana Lixandru, a partner at Sequoia Capital based in London. Europe had a promising start. At the start of the digital revolution in the 1990s, the region boasted several leading semiconductor companies (Netherlands-based ASML, Britain's ARM), software giants (Germany's SAP) and the dominant player in mobile phones (Finland's Nokia). The World Wide Web was invented by a Brit, Tim Berners-Lee, working at a European research facility. The computer center at the European Organization for Nuclear Research (CERN) in 2019—three decades after Tim Berners-Lee invented the World Wide Web at the facility. A big reason why Europe is now behind can be summed up as a lack of speed. Entrepreneurs complain that everything takes longer in Europe: raising money, complying with local regulations, and hiring and firing workers. 'In Germany a lot of people are just too cautious," said Karlheinz Brandenburg, the German engineer who helped invent the MP3 digital audio compression format. German consumer-electronics companies didn't think the invention was important and didn't invest enough in it, he said, and then Apple seized on the invention in the early 2000s to sell nearly half a billion iPod players. Brandenburg is now seeking €5 million ($5.6 million) in financing for a next-generation headphones startup. 'What is different in America is the speed of almost everything," said Fabrizio Capobianco, an early tech entrepreneur from Italy who lived for decades in Silicon Valley. 'Americans make decisions very fast. Europeans need to talk to everybody—it takes months." Capobianco, who returned to Italy three years ago, is now building a startup factory in the Italian Alps to scout out European tech companies. The prize for the winners: a one-way ticket to Silicon Valley. 'I don't think you can replicate Silicon Valley" in Europe, said Capobianco. He wants other European entrepreneurs to follow his example: implant themselves in America's tech hub and manage teams of engineers located in Europe, where wages and living costs are lower. That inevitably means that the highest-value jobs will be in the U.S., Capobianco said. Most European startups find it so difficult to expand at the same pace as their U.S. counterparts that they typically move to the U.S., are bought by U.S. companies, or partner with them. One of the U.K.'s largest startups, delivery company Deliveroo, recently agreed to sell its business to U.S.-based DoorDash for $3.9 billion. 'Europe is a much smaller market, but that doesn't mean it doesn't have great opportunities,' said Luciana Lixandru, a partner at Sequoia Capital in London. Even Europe's hottest AI firms are linking up with American firms rather than competing against them. London-based DeepMind was bought by Google parent Alphabet in 2014. Paris-based Mistral AI, which has raised over $1 billion in the race to build large AI models, has signed distribution deals with Microsoft, Google and Amazon. In Europe, most business financing still comes from banks, which generally require physical collateral—a building, perhaps—in the event of losses. Other forms of financing include risk-averse public-pension funds. Early venture capital investors also demanded terms that left founders hamstrung, say entrepreneurs. 'There are a lot of scattered, small amounts of capital, and then you have these very large, slow-moving, bureaucratic, quasi-government agencies. And you don't have very much in the middle—the more dynamic endowment capital that is in the U.S.," said Hussein Kanji, an American tech investor who founded Hoxton Ventures, a London-based venture-capital firm. Complex regulations Scaling up quickly in Europe is hard. The U.S. is a large integrated market, while Europe has dozens of countries with their own language, laws and taxes. Labor laws slow down worker mobility by making it harder to hire and fire workers. (There is often a three-month notice period in Europe for leaving a firm, and in some cases a six-month noncompete clause, jokingly known in Britain as 'gardening leave.") Until the past year or two, stock options in most European nations were little used because they were taxed as income before they vested. Taxes are higher, and regulations designed to corral big business become a costly and time-consuming headache for startups. It is easier for large AI companies in the U.S. or China to move to Europe than 'growing out of Europe and to have to invest from the start to satisfy a much more complex regulatory framework," said Sebastian Steinhäuser, chief strategy and operating officer at German software giant SAP. Europe's love of regulation is one reason why Han Xiao started to think about moving his Berlin-based AI startup to the U.S. He and two friends founded their company, Jina AI, five years ago after studying in Germany, aiming to apply machine learning to search information in unstructured data for companies. 'When Germans talk about AI, the first topic is ethics and regulation," whereas investors in the U.S. and China focus on innovation, Xiao said. Engineers in Berlin are also hard to find, he said. Xiao's attempts to fire underperforming workers have landed in court. His 17 employees tried to form a union. 'When Germans talk about AI, the first topic is ethics and regulation,' said Han Xiao. Xiao initially raised about $7 million from American and Chinese venture-capital firms and SAP's U.S. arm. His latest $30 million funding round was led by Silicon Valley investment firm Canaan Partners. The European market for AI technology is very small, Xiao said, with local clients adopting the technology slowly. After spending November and December in Palo Alto, Xiao decided to make the move to the U.S. European businesses spend 40% of their IT budgets on complying with regulations, according to a recent survey by Amazon. Two-thirds of European businesses don't understand their obligations under the EU's AI Act, which came into force last summer, the survey found. Meta delayed the launch of its latest AI model in Europe by nearly a year because of EU regulations. It began rolling out a limited version in March that doesn't include features like image generation or editing. Apple also postponed its new AI features for iPhones in Europe until recent weeks. Software company Bird, one of the Netherlands' most successful startups, said recently it plans to move its main operations out of Europe to the U.S., Dubai and other locations due to restrictive AI regulation. 'Stop regulating, Europe. We might be the first, but we won't be the last (to leave)," Robert Vis, the company's founder, wrote on his LinkedIn page. Culture matters European cities crowd the top spots on quality of life rankings, far ahead of their American counterparts. That lifestyle might contribute to less appetite for risk, along with a culture of equality that frowns on naked ambition. 'I get a lot of pitch decks that say, 'This could be a $50 to $100 million company,' and that doesn't really interest me," said Chris Hill, a Santa Monica, Calif., native who lives in London and manages a fund for EdenBase. He also notes that pubs in London's financial district are usually full at 2 p.m. on Thursdays. The rise of venture capital in London could eventually create an entrepreneurial ecosystem where money, talent and ideas are circulating quickly, said Sebastian Mallaby, a fellow at the Council on Foreign Relations whose book 'The Power Law" details how Silicon Valley built an entrepreneurial culture. In some cases, though, old habits might die hard. The Draghi report, said McAfee at MIT, did a great job diagnosing Europe's lagging tech sector, but then urged governments to spend more public money spurring the sector, missing the point that it was private money that was absent—most likely due to regulation and other problems. Said McAfee: 'That's when I went from nodding my head in agreement to banging it on the table." Write to Tom Fairless at and David Luhnow at
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Business Standard
06-05-2025
- Business
- Business Standard
Mideast titans step back from AI model race as US, China dominate
Within months of ChatGPT's release in late 2022, research labs in the United Arab Emirates claimed to have developed credible rivals. At the top of the list was Falcon, a popular open-source artificial intelligence system built with government support, and Jais, a model named for the country's highest mountain peak. The 'future of AI is not a distant dream, but a present reality,' Peng Xiao, chief executive officer of Emirati tech conglomerate G42, said in a statement in 2023 shortly after the firm launched Jais. But today, the UAE's dream of competitive, homegrown AI models remains far off. Falcon is significantly behind leading options from US companies in user numbers and public rankings. G42, meanwhile, recently pulled resources from Jais and is instead focused on building bespoke features on top of AI models from other companies, including OpenAI. Also Read Two-plus years into the generative AI frenzy, the global race to develop ever more sophisticated models increasingly looks like a competition between two countries. A handful of US firms continue to lead in AI development by spending billions on chips, data centers and talent to build the best and biggest models. China, meanwhile, is rapidly catching up and flooding the market with low-cost, open-source models to expand its reach. Most other nations, even wealthy ones like the UAE, are lost somewhere in the middle. A growing number of once promising AI ventures in the Middle East and Europe have fizzled or all but given up. Germany's Aleph Alpha, hailed at one time as Europe's rival to OpenAI, made a similar decision to G42 last year. Britain's Stability AI, an early AI model pioneer, has petered out after management issues. Even companies like France's Mistral, backed by significant venture funding and championed by the country's government, has shown little evidence of strong commercial traction or developer interest. In the Middle East, as in other markets, companies are rethinking whether the cost of building a cutting-edge AI model from scratch is worthwhile. Jais could be a competitive 'frontier model' if G42 continues to invest, said Kiril Evtimov, an executive running its cloud unit, Core42. 'But is that the right business strategy for us to capture the market? Probably the answer is no.' In 2023, the UAE launched a new firm, AI71, touted as a commercial vehicle for Falcon, a model developed by a government research arm. AI71 ended up following G42 and Aleph Alpha in making AI tools for specific business uses relying on multiple models, including Falcon, according to a spokesperson. While Falcon remains the most competitive offering from the UAE, it has struggled to keep up with advances from open-source alternatives from Meta Platforms Inc. and China's DeepSeek. In 2023, the Technology Innovation Institute (TII), the entity behind Falcon, touted the AI system's first-place ranking in open-source models on Hugging Face, a closely-watched barometer for the industry. As of last week, Falcon did not rank in the top 500 on the platform's leaderboard. A representative for TII said Falcon now has more than 55 million downloads. That's a small fraction of Meta's family of Llama models, which have been downloaded more than 1 billion times. The representative said integrations with cybersecurity, robotics and cloud companies will be announced soon. 'The value of a model lies not only in its initial benchmark performance, but in how it contributes to and enables broader innovation over time,' the representative said in a statement. G42, meanwhile, has pursued other ways to get into the current AI boom beyond model development. Its data center business is expanding in the Gulf region and MGX, an investing fund the company co-formed, has backed US AI developers OpenAI and xAI. Some countries are still trying to challenge the US and China on AI development. In January, India's government said it would support 18 different proposals to build foundational AI models, which a minister pledged would 'compete with the best of the best.' Saudi Arabia's AI agency also paired with International Business Machines Corp. last year to offer its homegrown national model, ALLaM, via the tech company's cloud services. Nations pursue these so-called sovereign models to have more control over how the AI systems are trained, either to influence how they work or lessen dependence on foreign tech, Michael Bronstein, a professor of AI at the University of Oxford, said at the Machines Can See conference in Dubai. But he said the prevalence of open-source models means these approaches have little odds of remaining competitive. Some of these models were also pitched as ways to better represent languages and populations unmet by Silicon Valley. OpenAI and its peers trained their models mostly on the internet, which heavily skews toward English. But an effective tool for Arabic doesn't require making a large language model from scratch, said Nour Al Hassan, CEO of Tarjama, a translation provider based in Dubai. A new startup her company incubated, recently released an AI system that Al Hassan said was created by fine-tuning a range of large models, an approach she said is better suited for price-sensitive corporate clients. 'You don't need such massive models to do a specific task for a bank,' she said. G42's Jais was also designed to power chatbots in Arabic. In September, G42 released Nanda, a Hindi language model, as part of its expansion efforts in India. The company and its research partners will continue to update these two models, according to Andrew Jackson, who runs G42's AI unit, Inception.
Yahoo
10-02-2025
- Business
- Yahoo
AI's English focus puts many countries at a disadvantage. A new EU project aims to fix that for 32 languages
An ambitious new AI project has begun to take shape in Europe, with the aim of developing open-source AI models that support the region's 24 official languages and more—while also complying as much as possible with its thicket of digital legislation. The OpenEuroLLM project, which commenced work at the start of the month, has a budget of just €37.4 million ($38.6 million): a pittance compared with the sums being invested in other AI-related projects like the $100 billion first tranche of the U.S.'s Stargate AI infrastructure project. Although participating companies such as Germany's Aleph Alpha and Finland's Silo AI are also contributing their researchers' time to an equivalent value, the bulk of the funding comes from the European Commission. EU-funded projects don't tend to move fast, and this one has a three-year road map in a sector that's currently undergoing significant evolution each month. But organizers and participants tell Fortune that it could be possible to deliver an intermediate model within a year—and the effort will be worth it. 'Most model development efforts that have worldwide visibility focus on the English language,' said Yasser Jadidi, chief research officer at Aleph Alpha. 'It's a consequence of most of the internet text data that is available and accessible being in English, and it puts other languages at a disadvantage.' For people in places like Sweden or Turkey (the OpenEuroLLM project is also targeting the tongues of eight countries that have applied for EU membership, so that the project encompasses a total of 32 languages) the lack of AI models that understand the intricacies of their languages can be a serious problem. For a start, it makes it harder for local companies and public authorities to adopt the technology and start providing new services. 'It's first and foremost a commercial question,' said Peter Sarlin, the CEO of Silo AI, Europe's largest private AI lab, which was acquired by AMD last year and is participating in OpenEuroLLM. 'Are there models that are performant in that specific low-resource language, be it Albanian or Finnish or Swedish or some other, that allows companies within that region to eventually build services on top?' The issue also has consequences for evaluating the accuracy and safety of AI models in the local context, Jadidi said. Indeed, Aleph Alpha's role in the project is chiefly to provide AI-model evaluation benchmarks that aren't simply machine-translated from English, as most are. The OpenEuroLLM project may have relatively meager funding, but it isn't starting from scratch. Most of its participants have already been involved in a separate scheme called High Performance Language Technologies (HPLT), which started two years ago with a budget of just €6 million. The original proposal was for HPLT to deliver AI models, but then OpenAI's ChatGPT changed the AI landscape and the organizers pivoted to creating a high-quality dataset that can be used to train multilingual models. The HPLT dataset is currently being 'cleaned' of errors, and it will form the basis of OpenEuroLLM's work. OpenEuroLLM will create a base model trained on a dataset of all the European languages. Once that's done, yet another EU-funded project, called LLMs4EU, will fine-tune it for various applications. Apart from cash, the EU is also providing computational resources to all these schemes. Europe is not the easiest place for AI companies to do business. Quite apart from the AI Act that is gradually coming into force, placing all sorts of reporting responsibilities on model providers and their customers, there's also copyright and competition law to consider—and the General Data Protection Regulation (GDPR), which places strict limits on the personal data that AI companies can use. These laws have had real effects on AI's European progress, with Meta delaying the rollout of Meta AI because of GDPR limits, and Apple also delaying the deployment of Apple Intelligence because of unspecified antitrust issues. (Apple Intelligence will come to EU iPhones in limited form in April, while Meta has started offering some Meta AI features to European wearers of its smart glasses.) As far as OpenEuroLLM's organizers are concerned, these laws are manageable. 'We believe we can live with all of them,' said Jan Hajič of Charles University in Czechia, who is co-leading the project with Sarlin. Hajič said the participants had already dealt with the copyright and most privacy issues when developing the HPLT dataset. 'The GDPR could be a problem, but that's something we are trying to get around with pseudonymizing the data, meaning that if we encounter people's names it gets deleted,' he said, while acknowledging that the necessary automation in this process may not have a 100% success rate. 'Our goal is to do things in such a way that they will not clash with the European regulation in any way,' Hajič said, adding that this could be a draw for companies wanting to target EU markets. For high-risk use cases that will require a lot of reporting to the EU authorities under the AI Act, the open-source approach will be essential for the transparency it allows, he argued. The OpenEuroLLM project has 20 participants including companies, research institutions, and high-performance computing clusters like Finland's Lumi. This setup could be seen as a liability with the potential for diverging priorities, but Aleph Alpha's Jadidi argued that open-source projects often include a wide array of participants without being dragged down. 'We have all the opportunity to ensure that a high amount of contributors is not a hindrance but an opportunity,' he said. This story was originally featured on
