Category: Industry

  • EU Breakup Risk and Productive Resilience

    EU Breakup Risk and Productive Resilience

    This piece is published in partnership with the French Institute for International and Strategic Affairs (IRIS).

    The U.S. administration criticizes the European Union for failings that often have real basis. However, the EU’s economic subordination to the United States and the embrace of its cultural crisis play a key role in Europe’s falling behind. In light of this paradox, these attacks are all the more destabilizing since the Trump administration’s economic demands – acquiesced to by Ursula von der Leyen – simultaneously hinder any possibility of Europe re-entering the technology race. Beyond transatlantic invective, this historical impasse makes the prospect of the EU’s breakup tangible. We must anticipate its potential effects through productive and intellectual resilience.

    The trade terms dictated by Washington first illustrate the technological impasse amid the transatlantic chaos. In exchange for unilateral tariffs of only 15%, the von der Leyen Commission has implemented a policy of accommodation towards the U.S. tech sector on most issues, with the exception of those related to social media content. The fact that these concessions are subsequently presented as a competitiveness policy unfortunately does not mitigate their long-term effects.

    The abandonment of technological autonomy follows a series of ill-conceived strategic choices. More than the lack of discussion, these bets have revealed a gap in scientific and industrial competencies. Examples include: the excessive gamble on hydrogen, the generalized transition to electric vehicles without competitive impact studies, later forcing a retreat, the semiconductor failure (with the costly reliance on technology transfers from Intel, now losing momentum). One could add the export of Germany’s energy transition shock, amplified by the abandonment over the past decade of gas import diversification projects, in favor of Nord Stream I & II. Concrete skills have been supplanted by bureaucracy, high-level events, and regulatory prose.

    We have imitated the excesses of U.S. governance, but omitted the scale of its research system, funding for technological programs, and the emergence of Big Tech within this framework. The aspect that inspires Europeans is more centered on the type of managerial hypertrophy that led to the decline of a company like Boeing.

    The crisis in European industry illustrates the exhaustion of a logic of extreme logistical optimization, at the expense of innovation and new industries. This has allowed us to benefit from very low costs in Asia and Central Europe while capitalizing on the prestige of legacy brands. The energy crisis and China’s technological leap – long presented as a promised land for European exports – have derailed this model.

    The fact that the United States seeks to anchor its reindustrialisation effort in the subordination of its vassals adds to these difficulties. Shortages of military equipment on the Ukrainian front have not only revealed the extent of industrial attrition in the EU and the US, behind the enthusiasm generated by the AI bubble at the same time. They have also accelerated the fracture within the Western bloc, leading Europeans to start redeveloping their military capabilities. However, this period of political turmoil seems ill-suited to long-term strategic planning and to averting nuclear risk, which motivated previous generations. Moreover, remilitarisation is largely benefiting US defence companies as evidenced by high-profile orders of F-35s.

    In reality, the level of deindustrialisation calls into question our very interpretation of GDP, given the activities that are now at the heart of developed economies, sustained by bubbles until they burst. At a time when many countries are developing, training engineers in large numbers, and deploying them for industrial expansion, we must soberly assess the value of our deindustrialised economies in the era of PowerPoint and circular funding.

    The euro crisis did not lead to genuine reconsideration. On the contrary, it was followed by a policy of monetary bubbles and, around 2017, the belief in an imminent leap forward for federal structures. A reindustrialization dynamic was even announced, although a more cautious analysis could only indicate the opposite trend. It is in this context that France’s situation has continually deteriorated on the financial and industrial front. The maxim that each crisis is an opportunity to complete a stage in the EU’s edification has accompanied the fading prospect of a stable, creative, and prosperous society.

    A fresh start for the European Union is hindered by the very nature of its falling behind, rooted in deep cultural trends, of which the bureaucratic drift and the educational crisis are central elements. Instead of remedies, we see numerous parties and movements of all kinds positioning themselves in a cultural war, the terms and theatrics of which are directly imported from the U.S. The Commission’s current concessions would, in a best-case scenario, delay a productive recovery by several years.

    Beyond Donald Trump’s invective, the long-term persistence of the EU can no longer be the sole working hypothesis in the face of looming financial shocks, productive and educational decline, and the outcome of the Russo-Ukrainian war. States and economic stakeholders must prepare for the possibility of a disruption in the European system within a decade.

    The focus, at this stage, should not be on making prophecies about the triggering factor, among various options: from the election of the Alternative für Deutschland (AfD) to the exit of certain Central European countries, potentially losing their status as net beneficiaries of the EU budget due to Ukraine’s integration – which might explain why Moscow does not oppose it.

    Rather, the task at hand is to undertake preparatory work to avoid a disorderly breakup. Such an event would have dire consequences for countries that, at that moment, would lack both a productive base and necessary resources. In a scenario combining breakup and lack of preparation, the trend illustrated by the EU-Mercosur agreement could, by that time, even lead to food supply difficulties. A resilience strategy must address these tangible risks.

    Anticipating the possible return of responsibilities to the national level, within a framework closer to an integrated customs union and a monetary coordination mechanism, could provide some impetus towards a productive strategy and an educational revival. As the level of mutual ignorance among Europeans has reached an alarming level, such an effort could even bring us together around more concrete objectives of good relations and stability.

  • Europe’s Trade Problem

    Europe’s Trade Problem

    I took part in Al Jazeera’s Inside Story discussion with Andy Mok and Ben Aris. Ailing European economies need to rebalance their trade relations with China and break out of their self-inflicted technological doom loop.

  • AI Bubble and Military Bottleneck: A Systemic Crisis

    AI Bubble and Military Bottleneck: A Systemic Crisis

    The financial bets on the revolutionary promises of generative AI have soared to dizzying heights. Circular funding among industry giants is proliferating, while structural limitations are emerging regarding the reliability and economic value of large language models (LLMs). From one bubble to another, this new frenzy points to the deeper disorganisation affecting Western economies in the deployment of capital and skills. In this respect, the simultaneous weakness in industrial capacity among Ukraine’s backers reflects a systemic crisis.

    An opinion piece by Rémi Bourgeot, economist and engineer, Associate Fellow at IRIS.

    While the world was waking up to the concrete potential of artificial intelligence with ChatGPT, the collapse of Silicon Valley Bank in early 2023 triggered the onset of a financial crisis. Technology stocks were hit hard. Venture capital funds were blamed for their risky financial schemes, particularly in the cryptocurrency space, which was hit by a series of scandals.

    These reservations were soon swept aside by a new wave of financial euphoria, this time centred on AI, but following similar patterns. Nvidia emerged as the big winner, with its graphics cards tailored to the requirements of giant neural network calculations. It effectively locked up the market with its proprietary platform, Cuda. The very notion of valuation ratios was overshadowed by the prospect of a radical transformation of human activity.

    It comes as no surprise that the intrinsic limitations of LLMs were overlooked during the initial phase of euphoria. Beneath the sweeping reactions of both AI apologists and staunch detractors, a more nuanced perspective emerged from discreet commentators, combining a technical grasp of neural networks with a philological intuition about the strengths and the limits of the syntactic logic captured by LLMs.

    OpenAI began by developing open, non-profit models, and its status remained hybrid for years. The prevailing idea was that LLMs would reach a qualitative tipping point, thanks to an explosion in size and compute resources. The confusing notion of AGI (artificial general intelligence) then served as a horizon for the most extravagant funding schemes.

    However, by 2024, the technical achievements of companies like Mistral in France and DeepSeek in China, with incomparably more limited resources, began to cast doubt on the idea that model deployment required the trillions of dollars mentioned by Sam Altman at OpenAI.

    The companies developing core AI models do not currently exhibit a real business model, beyond using investor funds to cover their expenses, particularly for the purchase of chips. On top of the issue of financial stability, the allocation of such resources to a particular technology must also be questioned. AI Pioneer Yann Le Cun has repeatedly emphasised the limitations of LLMs and called for efforts to be made on other types of models, which have been ignored by the bulk of investors. Instead, the bubble took on a new dimension, with massive funding from semiconductor companies like Nvidia to their own customers, like OpenAI.

    This latest bubble raises questions not only about this very industry, but more generally about the way the economy is funded. It seems increasingly difficult for developed countries to sustain industrial momentum beyond waves of financial and institutional frenzy that suggest magical thinking, or sometimes even mass hysteria.

    Meanwhile, the Ukraine war highlights the limitations facing Western industry in producing equipment. Production capacities for ammunition, armoured vehicles and electronic components have proven chronically inadequate to meet sustained and prolonged demand. Many factories capable of manufacturing critical components have been closed in recent decades. Supply chains are limited, often dependent on rare or offshore suppliers.

    This situation reveals a systemic failure centred on insufficient production, which goes beyond the defence industry. It results from a lack of strategic planning, particularly in terms of financing, energy supply and skills deployment. Reviving production requires restoring complex industrial chains and long-term profitability models. Otherwise, even massive investments will have no effect.

    Industrial strength does not come from stock market bubbles fuelled by the ecstasy of a post-physical digital nirvana. It requires careful interaction between businesses, research institutions and government agencies, based on long-term strategies and human skills. Behind the cutting-edge intellectual resources poured into LLMs, the bubble lays bare the erosion of industrial development strategies, exacerbated by failing educational systems and the relegation of scientific skills.

    Nevertheless, in light of the manufacturing rout epitomised by Boeing, the US policy focused on redeploying manufacturing and controlling energy costs is showing tentative signs of improvement. This is the case even in semiconductors, with TSMC establishing operations. Although financial shocks hamper in-depth reindustrialisation, the country is ultimately managing to assert its dominance in the digital field.

    The European Union, meanwhile, finds itself in a more precarious situation due to its technological retreat and the energy chaos stemming from Germany’s phase-out of nuclear power. By positioning itself as a faithful user of US technologies, it is undermining its industrial potential. In the dot com bubble of the late 1990s, Europe typically lagged behind during the upswing, endured the full brunt of the market crash, and ultimately failed to catch up on the technical front. In this respect, Ursula von der Leyen’s determination to cement the EU’s role as a digital and military vassal of the US for decades to come foreshadows a decline in living standards and political dislocation.

  • Competitiveness or Submission? Europe’s Dilemma

    Competitiveness or Submission? Europe’s Dilemma

    On Donald Trump’s orders, in exchange for unilateral tariffs of ‘just 15%’, the EU suddenly revises its digital regulations to open its market even wider to American Big Tech. But it’s all in the name of competitiveness…

    France 24 – 19 November 2025

  • Has Trump Killed Globalization?

    Has Trump Killed Globalization?

    A Fierce Struggle for Tech Dominance—Outside Europe.

    Le Débat du jour on Radio France Internationale, 5 November 2025

  • Rare Earths: China’s Nuclear Option

    Rare Earths: China’s Nuclear Option

    Donald Trump said after a summit in South Korea with his Chinese counterpart Xi Jinping that he had agreed to reduce tariffs on Chinese products to 47% in exchange for Beijing guaranteeing a supply of rare earths and buying American soybeans

  • Europe is selling out its future to Trump

    Europe is selling out its future to Trump

    “I was on France Info TV yesterday discussing how, behind the threat of chaos, Trump is successfully pushing a new paradigm of unilateral tariff protection. While these tariffs are relatively modest, they come with a long list of demands aimed at deepening his partners’ dependencies in digital, military, and energy sectors. Meanwhile, Europe is sacrificing its technological future to prop up its legacy industries.

    Click the image to access the video (in French).

  • Semiconductors Are the Achilles’ Heel of the AI Giants

    Semiconductors Are the Achilles’ Heel of the AI Giants

    The ultra-concentration in the design and production of semiconductors for AI, centred around Nvidia and TSMC, is fuelling the interest of digital giants, which are highly dependent in this regard. However, catching up looks to be a difficult task, despite the mobilisation of state actors.

    The explosion of artificial intelligence rests on two pillars of a different nature: on the one hand, the development of large language models such as GPT, and on the other, spectacular computing power with dedicated processors. These are designed in particular by the omnipresent giant Nvidia, and manufactured by a tight handful of actors, especially the Taiwanese company TSMC. AI models and semiconductors both require gigantic investments and cutting-edge expertise. However, these are two worlds that, although they cooperate closely, respond to very different requirements.

    In terms of model development, American digital giants such as Microsoft, Meta and Google have all the technological, economic and political resources to dominate the sector, both internally and through acquisitions/partnerships. This latter aspect even enables them to domesticate the diversification seen with the explosion of open source, i.e., models that are freely distributed and reusable by anyone. Although open source allows an entire AI ecosystem to exist, it cannot exactly be seen as David’s weapon against Goliath, as the giants themselves are deeply invested in it. Meta’s LLaMa language models are, for example, open source. Moreover, the financial weight and grip of Big Tech are such that we are seeing independent actors being drawn into their orbit one after the other. The French gem Mistral recently announced it was joining Microsoft’s fold, entrusting it with the distribution of its most advanced model, which will therefore be closed. The giants thus have ample means to maintain control over model development.

    Nevertheless, behind the domination of these behemoths, the importance of the processors that enable the training of these AI models should not be underestimated. It is in fact the crux of today’s technological warfare and lies in the hands of industrial giants of a different kind. The entire AI scene remains highly dependent on a semiconductor design and production chain that is incredibly concentrated, revolving around Nvidia and TSMC.

    A boom in demand for semiconductors dedicated to AI, and very few suppliers

    For digital giants, autonomy in terms of semiconductors remains a challenge in which it is difficult to position oneself. After years of investment, Nvidia holds a near-monopoly position in the design of semiconductors dedicated to AI. The American company designed 80% of this type of semiconductor worldwide last year.

    Once the design is completed, Nvidia outsources their manufacturing to Taiwan’s TSMC, one of only ten companies in the world capable of producing them. Nvidia is said to be “fabless”. In this industry, manufacturing a semiconductor requires a production line with specific characteristics (manufacturing equipment, testing and packaging). These new production lines are extremely costly. A brand-new factory (or foundry in the sector’s terminology) requires between 15 and 20 billion dollars and a minimum of two years of construction. Very few economic players can invest such colossal sums and overcome the entry barriers to the foundry market (“Fabs”).

    States are seizing the issue in the name of technological sovereignty

    Despite the enormity of the investments, some actors are entering or returning to this market, such as the American Intel or the Japanese Rapidus. Manufacturers already in the race, like TSMC or South Korea’s Samsung, are continuing to invest in an attempt to maintain their market shares. After the Covid-19 crisis and the subsequent semiconductor shortage, several states decided to relaunch their financial support for the sector. “Chip Acts” have multiplied to increase national semiconductor manufacturing capacity, bolster economic security and guarantee supplies for military use even in times of crisis. Among these countries are the United States in 2022 with the Chips and Science Act ($39 billion), the European Union with the Chip Act (€43 billion in 2023), Japan with the creation of the Rapidus conglomerate and a support plan ($100 billion for Rapidus and new TSMC factories over 2023–2027), China with the launch in 2023 of phase 3 of the Chinese government’s semiconductor fund ($46 billion for 2023–2027), and South Korea with a government plan of $7.3 billion. In the United States, the leverage effect of public subsidies in the sector is noteworthy. The $39 billion of the Chips and Science Act encouraged a wave of private investments amounting to $200 billion, spent by American and foreign companies on American soil.

    New entrants and a new scale of financing

    Until new factories produce more chips, supply will not be able to meet global demand for AI-dedicated chips. Hence a significant rise in prices. A Nvidia GPU (H100) can cost up to $40,000 per unit. Its availability is limited, because even with increased production volumes, the company still cannot meet market demand. Some users and buyers of Nvidia chips are concerned about being dependent on a single supplier. This is the case for Sam Altman, CEO of OpenAI, because the lack of AI chips risks hindering the development of his own company. Why not try to create one’s own industrial tool to restore this supply-demand imbalance? This is the logic of every new entrant in a booming sector. Sam Altman has been holding numerous meetings with manufacturers and investment funds over the past few months. In his initial estimates, he mentioned a (staggering) investment goal of $7 trillion to build a new segment of the semiconductor industry. The project is still ongoing. And Altman is not alone. Initiatives are springing up. Apple is working with TSMC to manufacture AI chips. The head of the Japanese group SoftBank, Masayoshi Son, wants to turn his group into an AI powerhouse. His latest project is to enable its subsidiary ARM to create a new AI chip division. A prototype will be tested in spring 2025, and mass production should begin in autumn 2025. For its part, Nvidia is maintaining its technological lead in a rapidly growing market. According to the Canadian research centre Precedence Research, the global market is expected to reach $100 billion by 2029 and $200 billion by 2032.

    This new type of shortage is prompting digital giants to position themselves in the segment, each in their own way. Faced with these ambitions, Nvidia continues tirelessly to position itself to do even better, notably better than what the giants will probably be able to achieve in designing AI-dedicated processors. The digital giants find themselves caught in an industrial vice that will be difficult to overcome. The prospect of balanced global competition in which all major regions manage to position themselves remains distant and uncertain. Beyond their own interests, the ultra-concentration of AI-dedicated semiconductors highlights a very real risk to industrial resilience across the entire chain, down to end users. In this regard, diversification is a major political issue.

    This piece was originally published by the French Institute for International and Strategic Affairs – IRIS.

  • Mistral Under Microsoft: Europe’s AI Catch-Up Challenge Remains Unresolved

    Mistral Under Microsoft: Europe’s AI Catch-Up Challenge Remains Unresolved

    Mistral AI’s move into Microsoft’s sphere has sparked political criticism in Europe. As a champion of open source, the company had recently advocated for a more flexible AI Act before announcing its shift to a closed model. Nevertheless, its technical success in developing foundational models with limited resources demonstrates Europe’s—and other global players’—potential to catch up. However, achieving true autonomy would still require overcoming a difficult economic equation that pushes the most promising startups into the arms of Big Tech.

    Mistral’s Success Highlights Europe’s Technical Potential in the AI Race

    Many observers had assumed Europe was destined to remain merely a user of American AI models for developing various applications. Technically, Mistral’s success confirms the opportunity for a relatively resource-efficient AI compared to Big Tech’s massive data usage and financial and human resources.

    In just a few months, Mistral managed to develop AI models that rival OpenAI, Google, and Meta in performance, with significant but far more limited resources than those of the American giants. This is particularly striking in terms of workforce, with its team of around thirty employees. This achievement not only showcases the team’s prowess but also sheds light on the nature of the technology driving the generative AI boom.

    Beyond new neural network architectures (like transformers), the spectacular progress in AI over the past decade has largely been due to the use of enormous amounts of data and computing power. While riding this wave of quantitative explosion, Mistral has also carved out a path for more refined AI engineering, allowing it to establish itself on the global stage in record time.

    Even amid an educational crisis and severe deindustrialization, it remains possible to mobilize skills from top-tier training programs to compete with global tech giants. Beyond the issue of European autonomy, this technical reality offers valuable lessons about the global AI race. Catching up and competing in AI is possible, provided there is sustained funding and market opportunities.

    Mistral’s Move into Microsoft’s Sphere Illustrates the Economic Challenge of Independent and Open AI

    After positioning themselves as champions of open, reusable models, Mistral’s leaders decided that their new, most advanced model would be closed—distributed through an agreement with Microsoft, which is also taking a stake in the company. The open-source approach had boosted Mistral’s appeal among developers, alongside other open models like Meta’s LLaMA, in contrast to the now radically closed model of the misnamed OpenAI.

    In fact, it was precisely this shift that led Elon Musk, who had been involved in OpenAI’s launch, to recently announce legal action against Sam Altman’s company. Beyond the irony of the billionaire’s outbursts, it is true that OpenAI, with its labyrinthine structure, reflects a gap between its original open-source and research-focused mission and its current purely commercial purpose. The issue of Big Tech’s grip on AI is particularly sensitive for Europe but is also relevant in the United States.

    Like OpenAI, Mistral’s agreement with Microsoft confirms its technical success and popularity. The French company is also launching a chatbot called “Le Chat,” modeled after ChatGPT. However, this partnership, for now, buries the dream of an independent, open-source European AI.

    Beyond the recent virulent attacks on the company’s leadership, we must question the European economic environment. The core issue remains the prospects for development, funding, and commercial opportunities needed to maintain a leading position in the digital sector. These challenges and the financial power of tech giants inevitably draw successful startups into their orbit. It is this economic aspect that has turned Mistral’s technical feat, which could have marked a turning point toward autonomy, into a strategic setback for Europe.

    Beyond Distrust of Lobbying, a Flexible Approach to AI Regulation Remains Essential

    The AI Act addresses an obvious need for regulation and risk management in AI. However, its complicated development has resulted in particularly convoluted agreement terms. Its creators had missed the generative AI revolution and embarked on a titanic adaptation effort last year.

    The idea of positioning Europe as the world’s digital regulator, with too little concern for the continent’s technological offerings, poses an existential risk to the European economy and its competitive autonomy. Moreover, with its difficult application to future technical developments, the AI Act risks serving the interests of Big Tech, which has the means to navigate these regulatory labyrinths. Mistral’s move into Microsoft’s orbit seems to confirm this.

    Mistral had strongly advocated at the end of last year for a loosening of the AI Act, particularly regarding open-source foundational models of generative AI. It is natural to think that the company had already considered its shift to a closed model in partnership with Microsoft. Nevertheless, the concessions made in response to objections from the French and German governments, defending their national companies like Mistral and Aleph Alpha, mainly concerned open source, which will thus benefit from greater flexibility. While Mistral’s reversal may be regrettable, its lobbying primarily resulted in a loosening of the AI Act that could, under certain economic conditions, encourage the emergence of future open-source competitors.

    This piece has initially been published by the French Institute for International and Strategic Affairs – IRIS.

  • The Industrial Revolution Will Outlive the Liquidity Bubble

    The Nasdaq has increased tenfold between the beginning of 2009 and the end of 2021, the S&P 500 a little more than five-fold. It was difficult to imagine, when the Fed started its ultra monetary stimulus (followed more or less belatedly by its various counterparts in the developed economies) that the world would go from one crisis management policy to another for more than a decade. The method of massive monetary stimulus has become, over the years, monolithic, inflating huge bubbles. (more…)