Digital Supercapitalism, AI and the Knowledge Economy

Data-Driven Geopolitics and the Rise of the Trillion Dollar Big Tech Company

Digital Supercapitalism

Robert Reich, who served as Secretary of Labour under President Bill Clinton, published Supercapitalism: The Transformation of Business, Democracy and Everyday Life (2007), reflecting on how capitalism has evolved in recent decades. Reich argues that since the 1970s, the US and other advanced economies have transitioned from ‘democratic capitalism’ to ‘supercapitalism.’ This new form of capitalism is characterised by intense competition, rapid innovation and a focus on consumer and investor interests at the expense of citizen interests. Reich attributes the rise of supercapitalism to technological advancements and deregulation, which have increased competition and given consumers and investors more choices and power. He argues that there’s an increasing tension between our roles as consumers/investors and our roles as citizens. While we benefit from lower prices and higher returns as consumers and investors, we may suffer as citizens from the negative externalities of corporate behaviour. He also documents the decline in worker bargaining power, contributing to wage stagnation and increasing income inequality, and he explores how corporations have gained more influence over the political process, often at the expense of individual citizens’ interests.

Reich was writing nearly two decades ago, before the release of Chat-GPT and the generative AI revolution that has transformed US and global capitalism, and that has led to the AI boom in unicorns, with some 21 companies adding $21 billion to the value of the Crunchbase Unicorn Board in 2023. While Reich’s Supercapitalism provides a framework for understanding the evolution of modern capitalism and its impact on society, politics and everyday life, the core of digital supercapitalism and the rise of Big Tech has developed only since the publication of his book even though many of his ideas remain relevant to discussions about the role of corporations in society, income inequality and the challenges facing modern democracies in an era of global capitalism. In view of this, the dynamism of digital supercapitalism must be acknowledged not just as the dominant sector raising productivity but as a force that reshapes American capitalism with its global reach and its ability through digital twinning and other means to spread its amplifying effects across the the global economy.

The concept of digital supercapitalism also tends to solidify and be enhanced through an understanding of supercomputing and the manufacture of a superchip like Nvidia’s Challenger superchip. Supercomputers are essential for training large AI models and processing vast amounts of data as they enable faster development of AI technologies, more complex simulations and modelling and real-time processing of enormous datasets. This computational power accelerates the pace of AI innovation, driving the AI development of digital supercapitalism, including its oligarchical structure that outsizes the modern state. These technological advancements could enhance digital supercapitalism through the development of faster innovation cycles with quicker development and deployment of AI models leading to rapid iteration and improvement of AI-driven products and services. They also increase market concentration and increase new AI applications enabling more sophisticated AI in areas like autonomous vehicles, robotics and personalised medicine. The increase in data processing capabilities increases the ability to process and derive insights from even larger datasets in real-time analysis of complex systems (e.g., financial markets and climate models).

While powerful chips might democratise some AI capabilities, they could also centralise power in the hands of those who control this technology, thus demonstrating the continued usefulness of Reich’s analysis and leading to geopolitical tension surrounding the competition between nations for supercomputing and AI chip supremacy with tech embargoes and sanctions of chip exports. Applying Reich’s analysis the widening gap between AI-capable and AI-limited entities and increased concerns about AI safety with more powerful systems with the potential for job displacement accelerating as AI capabilities expand and the erosion of democracy by footloose Big Tech companies. Under AI supercapitalism, Nvidia-like digital superchip technologies provide the computational backbone that enables the rapid advancement and deployment of AI systems, potentially accelerating many of the trends associated with supercapitalism in the digital age.

The Shift from Knowledge to Data

The evolution of the knowledge economy into what can be termed a ‘data economy’ marks a significant shift in how value is created and captured. While the knowledge economy emphasised human expertise and intellectual property, the data economy places primacy on the collection, analysis and application of vast amounts of data. This shift is driven by advancements in data storage, processing capabilities and artificial intelligence. Companies now derive insights and create value not just from structured data but also from the enormous volumes of unstructured data generated by users, IoT devices and digital interactions. The implications of this shift are profound. It has led to the rise of new business models centred around data monetisation, personalised services and predictive analytics. It has also raised important questions about data privacy, ownership and the ethical use of personal information. Moreover, this transition has begun to reshape the nature of work and skills valued in the economy. While deep domain knowledge remains important, the ability to work with data, understand AI systems and derive actionable insights from complex datasets has become increasingly crucial across industries.

The shift from a knowledge-based economy to a data-driven paradigm represents a fundamental transformation in the fabric of our economic and technological landscape. This transition is not merely a change in tools or methodologies but a reimagining of how value is created, captured and distributed in the modern world. In the era of the knowledge economy, human expertise and intellectual property reigned supreme. Companies and individuals derived their competitive advantage from specialised skills, patents and proprietary information. However, the dawn of the data economy has ushered in a new value system, one where the ability to collect, analyse and leverage vast amounts of data has become the primary driver of innovation and economic growth.

This seismic shift is propelled by remarkable advancements in data storage, processing capabilities and artificial intelligence. The exponential growth in computing power, epitomised by supercomputers, has enabled organisations to handle and make sense of data volumes that would have been unimaginable just a few decades ago. Moreover, the proliferation of IoT devices and digital interactions has created an ever-expanding ocean of data, both structured and unstructured, waiting to be tapped for insights. In this new paradigm, companies are no longer limited to deriving value from traditional sources. Instead, they can unlock hidden patterns and create innovative solutions by analysing the digital footprints left by users, the operational data from smart devices and the myriad interactions in the digital realm. This has given rise to novel business models centred on data monetisation, hyper-personalised services and predictive analytics.

The implications of this shift are profound and far-reaching. On one hand, it has democratised access to information and enabled businesses to offer more tailored products and services. On the other, it has raised critical questions about data privacy, ownership and the ethical use of personal information. The concentration of data in the hands of a few tech giants has accelerated the trend towards supercapitalism, potentially exacerbating economic inequalities. This transition is reshaping the nature of work and the skills valued in the economy. While deep domain knowledge remains important, there’s an increasing premium on the ability to work with data, understand AI systems and derive actionable insights from complex datasets. This has created new opportunities but also poses challenges for workforce adaptation and education systems.

The shift from knowledge to data is not just a technological trend; it’s a fundamental reorganisation of economic principles. As we progress further into this data-driven era, the interplay between supercomputing, the potential emergence of superintelligence and the intensification of supercapitalism will likely become even more pronounced. This convergence promises unprecedented opportunities for innovation and efficiency but also demands careful consideration of its societal impacts and ethical implications. This data-driven transformation is a key component of digital supercapitalism. In this new economic landscape, we’re witnessing extreme market concentration in the digital sphere, with data becoming the primary driver of value creation. AI-driven optimisation of business processes, rapid market dynamics and near-instantaneous global transactions are becoming the norm.

The economic implications of this shift are substantial. Some projections suggest the potential for dramatic productivity increases, possibly leading to 3-5% annual growth in advanced economies. We’re also seeing a shift from physical to digital assets as stores of value, and the rise of platform economies that could capture 20-30% of global corporate profits by 2030. The market structure is evolving rapidly, with further consolidation of ‘Big Tech’ potentially leading to 5-7 companies controlling 40-50% of global digital economy value. This concentration of power raises important questions about market competition and regulatory oversight. In the labour market, we may see an acceleration of job displacement due to AI and automation, potentially affecting 20-30% of jobs by 2030. Simultaneously, there’s likely to be growth in the gig economy and remote work, possibly reaching 30-40% of the workforce in developed economies.

As the world navigates this transition, it’s crucial to strike a balance between harnessing the power of data for economic growth and protecting individual rights and societal values. The future prosperity and equity of our digital economy will depend on how well we manage this delicate balance in the years to come. The challenges are significant, but so too are the opportunities for innovation, efficiency and new forms of value creation in this data-driven era of digital supercapitalism.

The Rise of the Trillion-Dollar Big Tech Company

The landscape of global economics has been dramatically reshaped by the meteoric rise of Big Tech companies. As of 2024, we stand at the precipice of an unprecedented economic concentration, with six US companies poised to join the exclusive $3 trillion market capitalisation club. This development will represent a staggering $18 trillion of the estimated $30 trillion US economy, a concentration of wealth and power unparalleled in modern history.

Fortune’s Will Daniel reports that Nvidia, Microsoft and Apple have all surpassed the $3 trillion market capitalisation mark, and Google and Amazon are following close behind in the $2 trillion range. These five tech giants are worth more than $14.5 trillion and make up 32% of the S&P 500. In 2002, total market capitalisation was $11.1 trillion. Daniel does not include Meta Platforms at a market cap of close to $1.5 trillion, pushing the total value of these six companies in 2024 to $16 trillion, over half the S&P market cap. The fact is that these AI companies are growing faster than other sectors. This year, Nvidia surged from a $2 trillion market cap to a $3 trillion in under 100 days, and Daniel quotes securities tech analyst Dan Ives that, a year from now, he predicts three $4 trillion market cap companies. That percentage increase is staggering at 25% for the Big Tech sector in only a year, even though the Tech sector is quite variable and individual companies have experienced even stronger growth. The six US Big Tech sector comprises roughly half the world’s 975 companies with a total market cap of $29.9 trillion.

These tech giants have leveraged network effects, economies of scale and data-driven innovation to achieve exponential growth. Their business models, often based on digital platforms and services, have allowed them to scale rapidly with relatively low marginal costs. The COVID-19 pandemic further accelerated this trend, as digital transformation became a necessity rather than a choice for businesses and consumers alike. The implications of this concentration are far-reaching. These companies now wield enormous influence over markets, innovation trajectories and even public policy. Their vast resources allow them to invest heavily in cutting-edge technologies like artificial intelligence and quantum computing, further entrenching their dominance. This raises critical questions about market competition, antitrust regulations and the future of innovation in a landscape dominated by a handful of tech behemoths.

The Rise of Big Tech in China

Parallel to the US tech boom, China has witnessed its own surge of tech giants. Companies like Alibaba, Tencent and ByteDance have grown to rival their Western counterparts in scale and influence. This rise is part of China’s broader strategy to transition from a manufacturing-based economy to a high-tech, innovation-driven one. Largest Chinese companies by market capitalisation reveal that Tencent takes first place ($434.91B) amongst banks (ICBC, Agricultural Bank, China Construction, Bank of China), PetroChina, China Mobile, with Alibaba ($179.68B) at eighth place, Xiaomi ($52.74) at 29th place, Baidu ($31.46B) at 43rd place, SMIC ($27.90B) at 51st place and WuXi AppTec ($15.55B) at 95th place. By comparison with the US Big Tech, the equivalent Chinese companies are much younger and much less dominant in a market capitalisation dominated by banks, energy and industrial companies. In terms of market capitalisation, Chinese Big Tech is still only a comparatively small fraction of the Chinese economy and less than a tenth the size of US Big Tech, although there are major differences in market areas.

The Chinese market is dominated by tech giants like Alibaba, Tencent, Baidu and ByteDance. These companies have a strong grip on the domestic market, with less international presence compared to their US counterparts. US companies like Apple, Microsoft, Amazon, Alphabet (Google), Meta (Facebook) and NVIDIA dominate globally. While both countries have tech giants, US companies generally have a more global reach. Chinese companies dominate their enormous domestic market but face challenges expanding internationally due to geopolitical tensions and regulatory differences. As of 2024, the largest Chinese tech companies have market caps in the hundreds of billions, with a few approaching or exceeding $500 billion. US Big Tech companies generally have higher market capitalisations, partly due to their global presence and the maturity of US financial markets.

Chinese companies are strong in e-commerce, mobile payments, social media and gaming, and rapidly advancing in AI, particularly in areas like facial recognition and natural language processing, whereas US companies are leaders in search engines, cloud computing, operating systems and global social media platforms. While there’s overlap, Chinese companies tend to excel in areas with strong domestic demand, while US companies often lead in enterprise solutions and global consumer products.

In China, there are closer ties between tech companies and the government. Chinese tech giants navigate a more complex relationship with their government, which can both support and constrain their growth. They are subject to sudden regulatory crackdowns and expected to align with national strategic goals, whereas US companies have more of an adversarial relationship with the government, facing antitrust scrutiny but generally operating with more independence.

In terms of data access and AI development, Chinese companies benefit from access to a vast pool of user data due to the large population and fewer privacy restrictions, which aids in AI development, particularly in areas like facial recognition. In the US access to global data but face more stringent privacy regulations, especially in markets like the EU. China is rapidly catching up in R&D spending, with a focus on applied technologies and is strong in areas like 5G, digital payments and e-commerce innovations. The US still leads in many cutting-edge areas, particularly in fundamental research and areas like quantum computing and advanced semiconductors. While the gap is narrowing, US companies still generally lead in breakthrough innovations, with Chinese companies excelling in rapid application and scaling of technologies. At the same time, China is facing challenges in global expansion due to geopolitical tensions and security concerns in Western countries but, nevertheless, making significant inroads in developing markets, particularly in Asia and Africa. By comparison the US experiences a well-established global presence but is facing increasing scrutiny and regulation in various markets. While US companies have a more established global footprint, Chinese companies are rapidly expanding their international presence, especially in emerging markets. In addition, Chinese tech giants have more thoroughly integrated financial services into their ecosystems, creating ‘super apps’ that are less common in the US market.

While both Chinese and US Big Tech companies are dominant forces in the global digital economy, they operate in different regulatory environments and have distinct strengths and challenges. The Chinese tech sector is rapidly evolving and, in some areas, may be overtaking their US counterparts, particularly in domains like mobile payments and certain AI applications. However, US companies still maintain a lead in global reach, market capitalisation and many cutting-edge technologies. The ongoing competition between these tech giants is shaping the future of the global digital economy and technological innovation.

China’s tech sector has benefited from a large domestic market, government support and a regulatory environment that has, until recently, allowed for rapid growth. The Chinese government’s initiatives like ‘Made in China 2025’ and the push for technological self-reliance have further fuelled this growth. Recent regulatory crackdowns and geopolitical tensions have introduced new challenges for Chinese tech giants. Despite these hurdles, they continue to innovate and expand, particularly in areas like artificial intelligence, 5G and e-commerce. The rise of Chinese tech companies has not only transformed China’s economy but has also intensified global competition in the tech sector, leading to what some call a ‘tech cold war’ between the US and China.

Supercomputing, Superintelligence and Supercapitalism

The advent of superchips and supercomputing capabilities has been a key enabler of supercapitalism – a form of hyperspeed, data-driven capitalism. These technologies have dramatically increased the speed and scale at which economic activities can be conducted, from high-frequency trading in financial markets to real-time supply chain optimisation. Superchips, with their immense processing power and energy efficiency, have made it possible to run complex AI models and process vast amounts of data in real time. This has enabled companies to make more informed decisions faster, optimise operations on a grand scale, and create highly personalised products and services.

Supercomputing, once the domain of scientific research and government agencies, has become increasingly accessible to large corporations. This has allowed them to tackle previously intractable problems, simulate complex scenarios and gain competitive advantages through superior data analysis and predictive capabilities. The combination of these technologies with AI has led to a form of capitalism that operates at unprecedented speed and scale. Markets react in milliseconds, products are personalised in real-time, and entire business strategies can be simulated and optimised before implementation. This has further concentrated power in the hands of those with access to these technologies, potentially exacerbating economic inequalities.

The evolving landscape of the 21st century is witnessing an unprecedented convergence of technological prowess and economic transformation, epitomised by the intertwining concepts of supercomputing, superintelligence and supercapitalism. This narrative explores the intricate relationships between these forces and their profound implications for our future. At the foundation of this technological revolution lies supercomputing. These incredibly powerful machines, capable of processing vast amounts of data at mind-boggling speeds, are pushing the boundaries of what’s computationally possible. From unravelling the mysteries of climate patterns to accelerating drug discovery, supercomputers are the engines driving innovation across multiple sectors. Their exponential growth in processing power is not just an academic curiosity but a catalyst for real-world breakthroughs.

As supercomputers evolve, they pave the way for the next frontier: superintelligence. While still theoretical, the concept of AI systems surpassing human intelligence across virtually all domains looms on the horizon. The potential of superintelligence is both awe-inspiring and daunting. On one hand, it promises solutions to some of humanity’s most pressing challenges. On the other, it raises profound ethical questions and existential concerns about the future of human agency and purpose. The computational might of supercomputers and the potential of superintelligence are not developing in a vacuum. They are both driving and being driven by the emergence of supercapitalism – an intensified form of capitalism turbo-charged by advanced technologies. In this new economic paradigm, data has become the new oil, fuelling unprecedented market concentration and the rise of trillion-dollar tech behemoths. AI-driven optimisation of business processes and hyper-efficient market dynamics are reshaping industries at breakneck speed.

This triumvirate of super-forces creates a self-reinforcing cycle. Supercomputing provides the raw power needed to develop increasingly sophisticated AI systems, potentially leading to superintelligence. These advanced AI systems, in turn, optimise economic processes, accelerating the trend towards supercapitalism. The wealth generated by supercapitalism then funds further advances in supercomputing and AI, completing the loop and driving the cycle forward with increasing momentum. The implications of this technological and economic revolution are far-reaching. While it promises rapid progress and potential solutions to global challenges, it also threatens significant societal and economic disruptions. The concentration of power in the hands of a few tech giants raises concerns about inequality and democratic governance. The potential for AI-driven job displacement could reshape labour markets in ways we’re only beginning to understand.

As we enter the new era of supercapitalism, the need for thoughtful consideration and proactive policymaking has never been more crucial. Harnessing the benefits of these super-forces while mitigating their risks will require new regulatory frameworks, economic models, and, perhaps, even a fundamental rethinking of our social contracts. The story of supercomputing, superintelligence and supercapitalism is still being written. Its final chapters will depend on our collective choices and our ability to navigate the opportunities and challenges of this brave new world. As we move forward, we must strive to ensure that the fruits of this technological revolution are shared equitably and that our pursuit of progress doesn’t come at the cost of our humanity.

Exponential Growth of Key Strategic Digital Technologies

The final piece of this puzzle is the exponential growth trajectory of key strategic digital technologies. Technologies such as artificial intelligence, quantum computing, 5G (and soon 6G) networks, blockchain and the Internet of Things are not developing in isolation but are converging and amplifying each other’s capabilities. Artificial Intelligence is seeing explosive growth across various domains. From natural language processing to computer vision, AI is becoming more sophisticated and finding applications in virtually every industry. The development of large language models and generative AI has opened up new frontiers in content creation, problem-solving and human-machine interaction.

Quantum computing, while still in its early stages, promises to revolutionise fields like cryptography, drug discovery and complex system optimisation. Its potential to solve certain types of problems exponentially faster than classical computers could lead to breakthroughs in various scientific and economic domains. The rollout of 5G networks and the development of 6G technology will enable faster, more reliable connectivity, paving the way for innovations in areas like autonomous vehicles, smart cities and the metaverse. This exponential growth and convergence of technologies are creating new markets, disrupting existing industries and reshaping the global economic landscape. It’s driving innovation at an unprecedented pace but also raising concerns about technological unemployment, digital divides and the ethical implications of these powerful technologies.

The interplay of AI, supercapitalism and the evolving knowledge economy is reshaping our world in profound ways. The rise of trillion-dollar tech giants, the shift to a data-intensive economy, the advent of supercomputing and the exponential growth of digital technologies are creating a new economic paradigm. This paradigm offers immense opportunities for innovation and growth but also presents significant challenges in terms of economic inequality, market concentration and the ethical use of technology. As we navigate this new landscape, it will be crucial to harness these technologies for broad-based economic benefit while addressing the societal and ethical challenges they present.

Geopolitics of AI Chip Development

AI covers a great range of different activities, including Cloud, cybersecurity, data analysis and visualisation, data warehousing and other companies that specialise in e-commerce, energy, environment, fintech, healthcare, manufacturing, robotics and transportation. All these AI companies depend on the development of high-quality chips that are manufactured by a handful of companies around the world including those responsible for high-end AI chips TMSC and Nvidia.

The geopolitics of chip development are heavily influenced by competition for technological supremacy, national security concerns and economic interests. Major players like the US, China and the EU invest heavily in semiconductor research and development, aiming to dominate the industry. Issues such as trade disputes, intellectual property rights and supply chain vulnerabilities add complexity to this landscape. Countries often use chip development as a strategic tool to enhance their technological capabilities and influence global markets.

Semiconductors are ubiquitous and the necessary basis for AI and the digital economy, a key driver of national wealth, productivity, global security and the next wave of global competitiveness. The next generation of advanced semiconductors less than 5nm that can contain a million transistors with very large integration depends upon massive investment with some $25 billion to establish a foundry. The geopol­itics of the manufacture of semiconductors revolves around the fact that China now produces 25% of all semiconductors and is growing fast, while about 75% of advanced semiconductors are produced in East Asia (South Korea, Japan, China), most notably one Taiwanese company, the Taiwan Semiconductor Manufacturing Company (TSMC), accounting for 90% of all advanced semiconductors. This has caused much consternation in Washington. In 2021, global sales in semiconductors reached well over half a trillion dollars, with the US accounting for 46% of the global market, yet, as Erika Morphy reports: ‘The share of modern semiconductor man­ufacturing capacity located in the US has eroded from 37% in 1990 to 12% today, mostly because other countries’ governments have invested ambitiously in chip manufacturing incentives and the US government has not.’ The US lead is slipping and is not assured, while China’s development has been phenomenal. Both the design and fabrication of semi­conductors are the key drivers of the electronics industry, with annual consumer sales of nearly three trillion and tech sales, especially for networks and communications devices, an estimated $5 trillion, fuelling the astonishingly rapid growth in e-commerce and the digital economy. In this growth scenario, semiconductors are projected to reach $726.73 billion by 2027.

An event that foretells the future of accelerated computing was the release of Nvidia’s Blackwell platform, which powers a new era of generative computing and an AI platform shift. Jensen Huang, CEO of Nvidia, suggests, ‘Generative AI is the defining technology of our time. Blackwell is the engine to power this new industrial revolution. Working with the most dynamic companies in the world, we will realise the promise of AI for every industry.’ The Blackwell GPU architecture features six transformative technologies for accelerated computing which will enable breakthroughs in data processing, engineering simulation, electronic design automation, computer-aided drug design, quantum computing and generative AI. The new Blackwell GPU, NY Link and Resilience Technologies enable trillion-parameter-scale AI models. New tensor cores reduce inference operating cost and energy by up to 25 times, driving the marginal cost of accelerated computing to zero and encouraging adoption by every major cloud provider, server maker and leading AI company.

Blackwell’s six revolutionary technologies enable AI training and real-time LLM inference for models scaling up to 10 trillion parameters, including the world’s most powerful chip packed with 208 billion transistors, second-generation transformer engine, fifth-generation NVLink to accelerate performance, RAS engine dedicated for reliability, availability and serviceability, Secure AI to protect AI models and customer data without compromising performance with new encryption protocols and Decompression engine. The Nvidia GB200 Grace Blackwell Superchip connects two B200 tensor core GPUs to the Grace CPU, which is connected to Quantum-X800 Infiniband to deliver advanced networking at speeds up to 800Gb/s. The GB200 is a key component of a multi-node, liquid-coiled rack system for the most intensive workloads. It combines 36 superchips and 36 Grace CPUs interconnected by NVLink that provide up to 30 times performance increase over previous models. The platform acts as a single GPU with 1.4 exaflops of AI performance and 30TB of fast memory.

Blackwell-based products will be available later in 2024 to partners AWS, Google Cloud, Microsoft Azure and Oracle Cloud Infrastructure as well as Nvidia’s Cloud Partner program with many cloud companies. BG200 will also be available on an AI platform co-engineered with leading cloud service providers that gives developers dedicated access to the infrastructure and software needed to build and deploy advanced generative AI models.

Nvidia was founded in 1993 and has been dedicated to developments in accelerated computing, and is now the world’s third-largest company. Its invention of the GPU in 1999 sparked the growth of the PC gaming market and ignited the era of modern AI, and now fuels industrial digitalisation across markets: ‘Nvidia is now a full-stack computing infrastructure company with data-centre scale offerings that are reshaping industry.’ Blackwell GPUs are being heralded as the engine to power a new industrial revolution across all industries, working with the most dynamic companies in the world, representing 100 T in value. While the impact of competition and technological development, as well as Blackwell’s reliance on third parties to manufacture, assemble and test new products, and changes in global economic conditions will affect future progress, the path for a new era driven by generative AI technologies is now clear.

Nvidia’s Blackwell Superchip is a game-changer that underwrites and accelerates development and breakthroughs by the world’s largest data centre operators, including Amazon, Microsoft, Alphabet’s Google and Oracle, concentrating an ecology of generative AI that revolutionises all industries and services through digital twinning across the market spectrum. The new range of chips will update chatbot applications, speed up robots for industrial use, create humanoid robots, enable Chinese EV vehicles, transform healthcare, improve education and provide more accurate weather forecasting through Earth-2APIs to address climate change extreme weather events. While generative AI weapons making was not mentioned, the chips will also be used in military technology.

Nvidia’s release of the new Blackwell Superchip and platform focuses attention on the geopolitical effects of a new industrial revolution that can increase productivity, harness innovation in accelerated computing across cloud computing companies, and have spread effects to a whole raft of industries and services.

Silicon Valley’s Conservative Politics

Carole Cadwalladr argues that the tech elite of Silicon Valley has signed up to advance Trump’s presidential bid with Elon Musk to donate $45 million per month to his campaign – a pledge further strengthened by Trump’s choice of J.D. Vance, ‘a tech bro.’ as his running mate. Cadwalladr writes: ‘Vance has said he wants to deregulate crypto and unshackle AI. He’s said he’d dismantle Biden’s attempts to place safeguards around AI development.’ Peter Thiel was an early supporter in 2016, and now he is joined by the likes of venture capitalists Marc Andreessen and Ben Horowitz, as well as ‘the Winklevoss twins and investors and podcast hosts Chamath Palihapitiya and David Sacks.’ This creates a new billionaire entrepreneurial class that enters a complex relationship with a non-liberal strong state.

Cadwalladr is not alone in making these assertions but may be astray in characterising Vance’s attitude to Big Tech. A number of commentators have described Vance as a ‘neoreactionary,’ and he has described himself as a member of the ‘postliberal right.’ strongly influenced by Curtis Yarvin, the founder of the ‘Dark Enlightenment’ neoreactionary (NRx) movement, Christian nationalist Rod Dreher, Patrick Deneen, the conservative political thinker who holds liberalism has failed America, as well as the entrepreneur Peter Theil, sociologist William Julian Wilson, economists David Autor and Raj Chetty, political adviser Oren Cass and Israeli philosopher Yoram Hazony. Thiel, the conservative tech billionaire, had a strong effect on Vance when he was still at Yale Law School and assisted his bid to become a senator and bankrolled his venture firm, Narya Capital. Vance has been very close to Big Tech, and, while he has paved the way for Silicon Valley in Washington, he is on record as criticising its ‘parasitic’ effects on the economy in favour of antitrust regulation favouring smaller tech companies.

Shifting alliances in tech and US politics is taking place with alleged support from prominent tech figures for Trump’s 2024 campaign, as described by Cadwalladr, suggests a significant shift in Silicon Valley’s political alignment. Historically, the tech industry has been associated more with liberal or libertarian ideologies. This potential realignment could reflect growing dissatisfaction with regulatory efforts by Democratic administrations or alignment with certain Republican economic policies. In this analysis, we must take into account the complexity of J.D. Vance’s position. While Cadwalladr portrays him as pro-deregulation, his actual position appears more complex. Vance’s self-identification as ‘postliberal right’ and his association with neoreactionary thought suggests a more critical view of both liberal democracy and unrestrained capitalism. His support for antitrust regulation of Big Tech companies aligns with a broader conservative movement to challenge the power of these corporations.

The influence of neoreactionary thought and the mention of Curtis Yarvin and the ‘Dark Enlightenment’ movement is significant. Neoreactionary philosophy often advocates for a return to more authoritarian forms of government, viewing liberal democracy as inherently flawed. This aligns with the notion of a ‘non-liberal strong state’ mentioned in my analysis. Yet, there are tensions within Conservative ideology. Vance’s intellectual influences represent a diverse range of conservative thought, from Christian nationalism (Dreher) to economic conservatism (Thiel) to critiques of liberalism (Deneen). This eclectic mix reflects the ongoing debates within American conservatism about the role of the state, the market and traditional values.

In the coming months, it is useful to keep an eye on the Tech Elite’s political strategy. The alleged financial support from tech billionaires for Trump’s campaign could be seen as a strategic move to influence policy. However, it’s worth considering whether this support is unanimous within the tech community and what motivations might drive individual actors. Such support also has implications for tech regulation and innovation. The potential alliance between certain tech elites and a Trump administration could have significant implications for tech regulation. While there’s a push for deregulation in areas like cryptocurrency and AI, there’s also a paradoxical call for stronger antitrust measures against big tech companies. Any analysis should pay attention to global implications. The involvement of tech billionaires in US politics could have global ramifications, given the international reach of many tech companies. How might this affect international tech policy, data governance and digital sovereignty debates?

In this medley, we must examine the role of media and information. Cadwalladr’s reporting itself is part of a larger narrative about the intersection of tech, media and politics. The inclusion of podcast hosts and investors in the list of Trump supporters highlights the growing influence of alternative media platforms in shaping political discourse in America. The support of venture capitalists and successful entrepreneurs for a particular political candidate raises questions about the future direction of the US economy. How might this alliance shape economic policy, particularly in areas like innovation, labour markets and wealth distribution?

Finally, further consideration should be given to the concept of a ‘non-Liberal strong state.’ How might a state that is both ‘strong’ (implying centralised power) and ‘non-liberal’ (potentially challenging individual rights and free markets) interact with a tech industry that has traditionally thrived on innovation and disruption? The concept of a ‘non-liberal strong state’ interacting with the tech industry presents a fascinating and complex scenario that merits deeper analysis. A strong, non-liberal state might attempt to guide technological innovation towards specific national goals or priorities. This could lead to increased funding and support for certain types of research and development, potentially accelerating progress in areas deemed strategically important. However, it might also stifle innovation in areas not aligned with state objectives. Such a state might implement a more stringent regulatory framework for tech companies, potentially limiting their autonomy. This could manifest as stricter controls on data collection and usage, algorithmic transparency, or content moderation. While potentially protecting citizens, this could also hinder the agility and experimental nature that has driven much tech innovation. The state might forge closer ties with select tech companies, creating a system of preferred partners who align with state interests. This could lead to the emergence of ‘national champion’ companies, like what we see in countries like China. While this might provide these companies with significant resources and market access, it could also reduce competition and potentially lead to monopolistic practices.

A non-liberal strong state might exert greater control over information dissemination, potentially using tech platforms as tools for narrative control. This could significantly impact social media companies and search engines, potentially requiring them to adjust their algorithms or content policies to align with state interests. In extreme cases, the state might move to nationalise certain key technologies or companies deemed too important to remain in private hands. This could dramatically reshape the tech landscape and alter the incentives for innovation and entrepreneurship. The state might impose strict data localisation laws, requiring tech companies to store and process data within national borders. This could fragment the global internet and create challenges for companies operating internationally. A strong state might exert influence over the tech workforce through immigration policies, education directives, or even direct placement of workers in key positions. This could affect the traditionally open and global nature of the tech talent pool. The state might implement a more protectionist intellectual property regime, potentially limiting the free flow of ideas that has been crucial to tech innovation. Conversely, it might also weaken IP protections in favour of state or national interests.

A non-liberal state might remove certain ethical constraints on technological development, potentially accelerating progress in controversial areas like AI, genetic engineering, or surveillance technologies. This could lead to rapid advancements but also significant societal and ethical challenges. The state could use access to its domestic market as leverage to influence the behaviour of tech companies, both domestic and foreign. This could lead to companies self-censoring or altering their products to maintain market access. In pursuit of technological independence, the state might push for the development of domestic alternatives to foreign technologies, potentially leading to a more fragmented global tech ecosystem.

The interaction between a non-liberal strong state and the tech industry would likely be characterised by a complex balance of cooperation and tension. While the state might provide resources and direction that could accelerate certain types of innovation, it could also stifle the open, disruptive nature that has been key to the tech industry’s success. This scenario raises fundamental questions about the relationship between technological progress and political systems. Can significant technological advancement occur within a more controlled, state-directed environment? Or does true innovation require the freedoms associated with liberal democracies? It prompts us to consider the global implications. How would such a system in one major nation affect the global tech ecosystem? Would it lead to a more fragmented, competitive international landscape, or might it prompt other nations to adopt similar approaches? This analysis highlights the complex and evolving relationships between technology, politics and ideology in contemporary America. It suggests a potential realignment of power that could have far-reaching consequences for governance, innovation and the future of liberal democracy.

In the past, the political leanings of Silicon Valley have been predominantly liberal, known for its tech industry and innovative startups, and has generally leaned towards liberal and progressive political views. However, some venture capitalists in the tech industry express conservative viewpoints, advocating for less regulation, lower taxes and a free-market economy. These views are often driven by business interests and the desire to foster innovation without governmental constraints. There is some evidence that a Trump/Vance administration would free up AI regulation although Vance is strong on breaking up the Big Tech companies to limit monopolistic tendencies and to encourage the growth of smaller companies in the name of competition.

Silicon Valley’s political landscape is complex and multi-faceted, reflecting a blend of progressive ideals and a libertarian streak that aligns with some conservative principles. The conservative politics in Silicon Valley, though less visible, play a significant role in shaping the debate and policies affecting the tech industry. The notion of Silicon Valley’s conservative politics supporting the Trump/Vance ticket indicates a significant shift from the typically progressive leanings of the tech community. This change reflects a complex interplay between the region’s tech-driven economy and broader national political trends.

Despite the prevailing progressive ethos, there is a notable minority within Silicon Valley that aligns with conservative or libertarian ideologies. This diversity is sometimes overshadowed by the dominant liberal narrative but becomes evident during significant political events or campaigns. This trend of supporting conservative politics within Silicon Valley is a topic of ongoing analysis and debate, reflecting the evolving political and economic landscape in which technology companies operate. While Donald Trump isn’t traditionally associated with tech-friendly policies, figures like J.D. Vance have positioned themselves as tech-savvy conservatives who understand the industry’s concerns. Some in the tech sector worry about increased government regulation of the industry under liberal administrations, and conservative tax policies often appeal to high-earning tech executives and investors. Further, some in Silicon Valley have become critical of what they perceive as excessive ‘wokeness’ or political correctness in tech culture. This analysis highlights the nuanced political dynamics within Silicon Valley, suggesting a landscape that is influenced by both economic self-interest and broader cultural reactions to national political trends. The tech industry’s engagement with conservative politics is part of an ongoing debate about the future direction of regulation, taxation and cultural norms in the tech sector. The evolving political dynamic within Silicon Valley could have far-reaching consequences, not only within the tech industry but across multiple sectors of American and global society, as these companies play increasingly pivotal roles in economic, social and political arenas.

Concluding Note

This column has explored the transformative realm of supercapitalism in the digital age, highlighting how the intersection of technology and global economics is reshaping our world. By tracing the shift from traditional knowledge-based economies to modern data-driven paradigms, we have seen how industries and market dynamics have been fundamentally altered. This evolution has not only fostered the rise of trillion-dollar Big Tech companies in the West but has also paralleled the rapid emergence of comparable tech giants in China.

Through detailed examination, it has delved into the exponential growth of strategic digital technologies such as supercomputers and advanced chip technologies. These innovations are crucial in maintaining and expanding technological supremacy and have become pivotal in driving sector-wide innovation. The critical role of AI chips and their development was specifically highlighted, underpinning the technological prowess of these corporate giants. The geopolitical implications of these developments are profound. The race for computational dominance has not only reshaped international relations but has also recalibrated global economic strategies, illustrating the increasing entanglement of technological advancement with geopolitical power.

This column has attempted to provide a comprehensive overview to illuminate the intricate relationships between technological advancement, economic power and global politics in the era of digital supercapitalism. As we move forward, the ongoing interactions between these domains will continue to challenge traditional economic structures and international relations, necessitating a re-evaluation of strategies in the face of rapidly advancing digital technologies. This era of supercapitalism demands a nuanced understanding of how technological capabilities can be harnessed and managed to sustain global economic stability and growth. The backing of conservative politics may also reflect a cultural counter-reaction against what some in Silicon Valley perceive as an overemphasis on political correctness and progressive social policies. This could affect corporate culture and policies, potentially leading to a more varied political discourse within tech companies. With a conservative approach, there could be a faster pace of innovation due to fewer regulatory hurdles. However, this might also lead to increased scrutiny from other global regions with stricter regulations, affecting international operations and competitiveness. The political stances of major tech hubs like Silicon Valley have global implications, affecting everything from international data agreements to cybersecurity policies. A conservative Silicon Valley might align differently on international issues compared to a more liberal one, possibly impacting US relations with other tech-heavy nations and US foreign policy imperatives to contain and slow China’s economic development.

Digital supercapitalism refers to a modern economic system characterised by the dominance of digital technologies and big tech companies that leverage data and connectivity to drive value creation and accumulation at unprecedented scales. This concept extends the traditional notion of capitalism by emphasising the critical role of digital innovation in economic and social structures. Digital supercapitalism represents a fundamental shift in the structure and dynamics of the global economy, driven by the rapid evolution of digital technologies. As such, it requires careful consideration of its implications for economic policy, regulation and society at large to ensure that the benefits of digital innovations are widely distributed and that challenges are effectively managed.

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Full Citation Information:
Peters, M. A. (2024). Digital Supercapitalism, AI and the Knowledge Economy: Data-Driven Geopolitics and the Rise of the Trillion Dollar Big Tech Company. PESA Agora. https://pesaagora.com/columns/digital-supercapitalism-ai-and-the-knowledge-economy/

Michael A. Peters

Michael A. Peters (FRSNZ)  is a New Zealander and is currently Distinguished Professor at Beijing Normal University and Emeritus Professor University of Illinois Urbana-Champaign. He was awarded a Personal Chair at the University of Auckland in 2000 and became a Research Professor at the University of Glasgow (2000-2006) before being appointed Excellence Hire Professor at Illinois and Professor of Education at the University of Waikato. He has Honorary Doctorates from Aalborg University, Denmark and SUNY, New York.

Michael was Editor-in-Chief of Educational Philosophy and Theory for 25 years and is currently Editor of Beijing International Review of Education (Brill). He is the founding editor of Policy Futures in Education (Sage); E-Learning & Digital Media (Sage); Knowledge Cultures (Addleton); Open Review of Educational Research (Taylor & Francis); Video Journal of Education and Pedagogy (Brill) and on the board of many other journals and book series.

Michael has written over 120 books and many journal articles on a wide range of topics and has worked with and mentored many younger scholars. He was given the Social Science and Humanities Leader in China Award in both 2022 and 2023 (Research.com) and is ranked 1st in China and 5th in Asia for Education and Educational Philosophy and Theory (AD Scientific Index, 2023). He is also ranked in the World’s Top 2% of Scientists by Stanford University. His recent works includes two books on the apocalyptic and post-apocalyptic philosophy to be published in 2024.