This Bismarck Brief will contribute to our exclusive upcoming AI 2026 Bismarck Strategic Report, which will feature in-depth analysis of the state of the artificial intelligence sector and technology, together with a comprehensive profile of key players. Upgrade or subscribe now to receive full access and never miss a report.

Gas turbines are types of internal combustion engines that convert chemical energy from natural gas into mechanical rotation that a generator then converts into electricity. Gas is the world’s second-largest energy source for power generation, behind only coal: in 2025 gas power plants worldwide generated around 7000 terawatt-hours (TWh) of electricity, compared to around 10,500 TWh for coal plants.1 Such power plants are especially important in regions such as the United States where, due to the fracking revolution, natural gas remains cheap and abundant, and also in many European countries where regulatory factors have combined to drive coal and nuclear power plants out of operation. Similar U.S. regulations mean that the recent significant increase for U.S. electricity demand, which was close to stagnant for two decades, and is driven primarily by AI data center construction, will be met through burning natural gas, driving rapidly expanding demand for gas turbines.

Read more

This Bismarck Brief will contribute to our exclusive upcoming AI 2026 Bismarck Strategic Report, which will feature in-depth analysis of the state of the artificial intelligence sector and technology, together with a comprehensive profile of key players. Upgrade or subscribe now to receive full access and never miss a report.

Cerebras is a U.S. semiconductor company that, in 2019, made computing history by successfully creating the physically largest-ever computer chip.1 An Nvidia H100 chip, first released in 2022, is roughly 814 square millimeters large—small enough to sit on a fingertip. In comparison, Cerebras’ “Wafer-Scale Engines” are over 46,000 square millimeters in size, well over fifty times larger than Nvidia’s chips and large enough to be held with both hands. The idea behind building massive computer chips is very simple: electrical signals between transistors on a single large chip must move far less distance than signals moving across many smaller chips connected with external networking components, making a single chip not just faster and more powerful but also more economical, using less electricity. Cerebras used a novel design to circumvent existing semiconductor design and manufacturing constraints, and says its chips are twenty times faster than Nvidia’s chips at running AI models, allowing instantaneous responses with no wait-time for users; its chips have won a major customer in OpenAI, which agreed to buy $20 billion of Cerebras chips in April 2026.2

Read more

This Bismarck Brief will contribute to our exclusive upcoming AI 2026 Bismarck Strategic Report, which will feature in-depth analysis of the state of the artificial intelligence sector and technology, together with a comprehensive profile of key players. Upgrade or subscribe now to receive full access and never miss a report.

With a market capitalization of over $2 trillion (TSM), Taiwan Semiconductor Manufacturing Company (TSMC) is the most valuable semiconductor manufacturing company in the world as of May 2026.1 The company is considered a chip “foundry” that does not design any computer chips but only manufactures them on contract for other companies, including “fabless” semiconductor companies like Nvidia and AMD. TSMC singlehandedly dominates global production of the world’s most advanced and computationally powerful computer chips and its dominance has not just held but grown in recent years: its share of global foundry revenue has grown from 59% in 2020 to 72% as of late 2025—with second-ranked Samsung dwarfed in comparison with a market share of just 7%—and its market share reaching even higher with greater chip sophistication.2 At present, the entire leading edge of artificial intelligence technology is dependent on TSMC’s manufacturing capabilities as well as its ability to scale up production quickly, and by extension so are the fortunes of many of the world’s most valuable companies including Nvidia and Apple.

Read more

The recent growth in optimism about artificial intelligence technology has led to a boom in demand for the computing power or “compute” that these new AI algorithms require for training i.e. development and inference i.e. usage. The high compute demands for AI are met through chips like Nvidia’s “graphics processing units” (GPUs), which are capable of processing vast amounts of computations in parallel. While GPUs and their equivalents from other companies like AMD or Google can be purchased and run on a company’s own premises in what is now commonly called a “data center” or “compute cluster,” the financial costs and organizational complexities of building such data centers, maintaining them, and inevitably upgrading them with new and more powerful chips are prohibitively high even apparently for well-funded frontier AI labs like OpenAI or Anthropic. As a result, many companies and individuals choose instead to rent compute from “cloud computing” providers like Amazon Web Services (AWS) or Microsoft Azure and, alongside these large and established companies, a number of smaller and newer “neocloud” companies have arisen to meet demand specifically for remotely renting out AI compute.

Read more

With annual profits of over $80 billion, Meta Platforms (formerly Facebook) is the seventh-most profitable company in the world and the eighth-most valuable with a market capitalization of over $1.5 trillion (META).1 Meta earns these profits from just under $200 billion in annual online advertising revenues from its globally dominant social media platforms: Facebook, Instagram, and WhatsApp. As of December 2025, Meta claimed 3.58 billion daily active users across its social media platforms.2 This is roughly 45% of the entire human population. Meta founder and CEO Mark Zuckerberg has made it a goal for the company to produce frontier artificial intelligence models at the cutting edge of capabilities, competitive with AI labs like OpenAI or Anthropic. With AI capabilities premised to a large extent on access to enough computing power or “compute” from advanced semiconductors from companies like Nvidia, Meta’s financial firepower makes it a key contender to examine in the AI race.

Read more

This Bismarck Brief will contribute to our exclusive upcoming AI 2026 Bismarck Strategic Report, which will feature in-depth analysis of the state of the artificial intelligence sector and technology, together with a comprehensive profile of key players. Upgrade or subscribe now to receive full access and never miss a report.

Cohere is a Canadian artificial intelligence company founded in 2019 by Aidan Gomez, Nick Frosst, and Ivan Zhang. Gomez was one of eight co-authors of the seminal 2017 paper by Google researchers introducing the transformer architecture that underpins large language models (LLMs) today, and both Gomez and Frosst come from the tradition of knowledge in AI and computer science centered around Nobel Prize winner Geoffrey Hinton at the University of Toronto, which also produced OpenAI cofounder and former chief scientist Ilya Sutskever. Cohere has also tried to attract research talent by establishing its research arm, Cohere Labs, as an independent non-profit with the freedom to collaborate across academia and industry to publish its research. This move came as the major U.S. labs increasingly became closed off and stopped publishing any meaningful academic research.

Read more

This Bismarck Brief will contribute to our exclusive upcoming AI 2026 Bismarck Strategic Report, which will feature in-depth analysis of the state of the artificial intelligence sector and technology, together with a comprehensive profile of key players. Upgrade or subscribe now to receive full access and never miss a report.

Since its founding in early 2023, the U.S. artificial intelligence company xAI has rapidly become one of the world’s leading AI labs and one of the world’s most valuable privately-owned companies. After its most recent January 2026 fundraising round, xAI is believed to be valued at more than $230 billion, making it the third-most valuable private AI lab after OpenAI and Anthropic.1 Headquartered in Palo Alto, California, xAI’s core staff as of 2025 numbered roughly 300 people.2 Founded by Tesla, SpaceX, and OpenAI founder Elon Musk, who is currently 54 years old, xAI merged with X (formerly Twitter) in March 2025, resulting in a combined corporation that is approximately 59% owned by Musk personally.3 In Musk’s own words, the mission of xAI is to “understand the true nature of the universe,” and the company plays an increasingly prominent role in Musk’s constellation of companies.4

Read more

This Bismarck Brief will contribute to our exclusive upcoming AI 2026 Bismarck Strategic Report, which will feature in-depth analysis of the state of the artificial intelligence sector and technology, together with a comprehensive profile of key players. Upgrade or subscribe now to receive full access and never miss a report.

ByteDance, best known as the creator of the popular short-form video app TikTok, is also one of China’s largest cloud computing providers, hosts ByteDance Seed—one of the country’s largest frontier AI research labs—and owns the AI assistant app Doubao. The Doubao app is their main consumer product and had over 170 million monthly active users in China as of October 2025, meaning they have the most active users in the country, ranking above DeepSeek’s app’s 145 million monthly active users.1 ByteDance has the advantage of being able to train its multimodal models on user-submitted videos from TikTok and its Chinese equivalent, Douyin. Douyin, however, is not just a social media platform but also the third largest e-commerce platform in China.2 ByteDance’s stated aim is to integrate AI agents into every facet of how people interact with the internet and offer an immersive consumer entertainment, e-commerce, and social media experience within their own “super-app” ecosystem, something the company’s founder Zhang Yiming, who de facto still leads the company, believes will fundamentally transform user retention and satisfaction.

Read more

This Bismarck Brief will contribute to our exclusive upcoming AI 2026 Bismarck Strategic Report, which will feature in-depth analysis of the state of the artificial intelligence sector and technology, together with a comprehensive profile of key players. Upgrade or subscribe now to receive full access and never miss a report.

With a market capitalization of approximately $1.5 trillion (TSLA) as of January 2026, the U.S. electric vehicle manufacturer Tesla is by far the most valuable auto maker in the world as well as one of the most valuable companies overall.1 Elon Musk has served as CEO of Tesla since 2008, during which time the company has, more than any other, spearheaded the rise of electric vehicles as a viable commercial product and alternative to traditional internal combustion engine (ICE) vehicles. Tesla has also spearheaded another major shift in the design of automobiles: the liberal integration of software and electronics to improve the driving experience for Tesla drivers, which, for many years now, has been expected to culminate in fully autonomous self-driving vehicles with no need for human drivers or intervention. This outcome would be tantamount to an economic revolution in personal, public, and commercial transportation, by eliminating the need for costly and rote human labor in the form of driving.

Read more

This Bismarck Brief will contribute to our exclusive upcoming AI 2026 Bismarck Strategic Report, which will feature in-depth analysis of the state of the artificial intelligence sector and technology, together with a comprehensive profile of key players. Upgrade or subscribe now to receive full access and never miss a report.

Andrej Karpathy is a computer scientist, AI researcher, and expert in computer vision who was a founding member of OpenAI and then head of Tesla’s Autopilot driver assistance and self-driving car program from 2017 to 2022, where he was responsible for building the team and technology that today powers Tesla’s autonomous driving capabilities. Self-driving vehicles promise to be one of the most immediate and consequential areas where AI progress will obsolete human labor in the physical world. Whereas Google’s Waymo and other self-driving efforts have attempted to scale up safe autonomous taxis using multiple types of redundant sensors and extensive reference mapping of the environment, Elon Musk has instead pursued a “vision-only” approach focused on achieving self-driving AI software perceptive enough to maneuver vehicles using only cameras. Karpathy was handpicked by Musk to build this technology for Tesla and largely succeeded.

Read more

This Bismarck Brief will contribute to our exclusive upcoming AI 2026 Bismarck Strategic Report, which will feature in-depth analysis of the state of the artificial intelligence sector and technology, together with a comprehensive profile of key players. Upgrade or subscribe now to receive full access and never miss a report.

Corporate investments in artificial intelligence, especially in the construction of a new generation of data centers built to provide computational power or “compute” for generative AI, have driven over one-third of the United States’ GDP growth in the first nine months of 2025.1 These new data centers will also substantially increase both peak and total electricity demand, after two decades in which power demand was nearly flat, and grew at well under a 1% compound annual growth rate.2 Today, the entire U.S. data center sector draws a total of less than 15 gigawatts (GW) of power, but the pipeline of new data centers under construction will, if all planned facilities right now are completed, add 140 GW of new load to the current total U.S. peak demand of 760 GW, an increase of almost 20%.3

Read more

This Bismarck Brief will contribute to our exclusive upcoming AI 2026 Bismarck Strategic Report, which will feature in-depth analysis of the state of the artificial intelligence sector and technology, together with a comprehensive profile of key players. Upgrade or subscribe now to receive full access and never miss a report.

Ilya Sutskever is one of the world’s leading AI scientists. As of December 2025, he is the CEO of Safe Superintelligence (SSI), a startup he co-founded upon his departure from OpenAI in May 2024, where he was also a co-founder and worked for over eight years as Chief Scientist. Under his technical leadership, OpenAI, which began as a small non-profit, became the world’s leading generative AI company with a sizable lead over its competitors in both technology and paying user base, a lead it still retains today.

Read more

This Bismarck Brief will contribute to our exclusive upcoming AI 2026 Bismarck Strategic Report, which will feature in-depth analysis of the state of the artificial intelligence sector and technology, together with a comprehensive profile of key players. Upgrade or subscribe now to receive full access and never miss a report.

John Carmack is an American software engineer and video game developer who cofounded the game studio id Software, whose game series including Doom, Quake, and Wolfenstein have been widely credited with not just popularizing but laying the technical groundwork for fast-paced video games utilizing three-dimensional graphics in the 1990s, in particular the “first-person shooter” (FPS) genre. Carmack was the lead programmer on these series and has been credited with developing multiple techniques that made it possible to smoothly render computationally-intensive graphics. Carmack’s early software work thus helped to drive adoption of specialized, high-performing computer chips called graphics processing units (GPUs), designed by Nvidia. Decades later, Nvidia’s powerful GPUs have become the standard for developing and using computationally-intensive artificial intelligence software, and, since 2022, Carmack has in turn devoted his time to running his own AI research lab aiming to build artificial general intelligence (AGI).

Read more

This Bismarck Brief will contribute to our exclusive upcoming AI 2026 Bismarck Strategic Report, which will feature in-depth analysis of the state of the artificial intelligence sector and technology, together with a comprehensive profile of key players. Upgrade or subscribe now to receive full access and never miss a report.

It is rare for someone to be a competent researcher as well as able to navigate sometimes cutthroat corporate politics. Because he can do both, currently 49-year-old Demis Hassabis is one of the most influential technologists working on artificial intelligence today. Hassabis is currently CEO of Google DeepMind, an organization with notable research capabilities demonstrated by their many technical firsts spanning over a decade of AI research. Such research capacity is surprisingly rare in the crowded field of giant companies eagerly contending to lead the AI industry, perhaps matched by only a few other exceptions such as OpenAI and DeepSeek. For example, under Hassabis, DeepMind built the program AlphaFold to predict protein structures, for which Hassabis was awarded the 2024 Nobel Prize in Chemistry and was knighted in the United Kingdom.

Read more

This Bismarck Brief will contribute to our exclusive upcoming AI 2026 Bismarck Strategic Report, which will feature in-depth analysis of the state of the artificial intelligence sector and technology, together with a comprehensive profile of key players. Upgrade or subscribe now to receive full access and never miss a report.

Z.ai, known as Zhipu AI until 2025, is a Chinese artificial intelligence startup founded in 2019 by Tang Jie and Li Juanzi, both professors at Tsinghua University, Chinese paramount leader Xi Jinping’s alma mater and one of China’s most prestigious universities. Alongside companies like DeepSeek and Moonshot AI, it is one of the leading AI startups in China, known primarily for the “GLM” series of open-source large language models (LLMs) with low costs of inference i.e. usage and high performance, especially on coding and “agent” tasks. The company is headquartered in Beijing and reportedly employs around 500 people, with a core research team of between 100 to 200 staff members.1 It is led by CEO Zhang Peng, an AI researcher and Tsinghua alumnus, and was one of the first companies in China to build a large language model before the viral release of OpenAI’s ChatGPT in November 2022.

Read more

This Bismarck Brief will contribute to our exclusive upcoming AI 2026 Bismarck Strategic Report, which will feature in-depth analysis of the state of the artificial intelligence sector and technology, together with a comprehensive profile of key players. Upgrade or subscribe now to receive full access and never miss a report.

Alibaba is the second-most valuable technology company in China, with a market capitalization of nearly $400 billion (BABA) as of November 2025 and approximately $130 billion in revenues in 2024.1 Although it is primarily an e-commerce company that has been dubbed “China’s Amazon,” it today also hosts an elite artificial intelligence research lab and is one of China’s major providers of cloud computing services i.e. remotely renting out access to servers for computing and data storage, and building the large data centers to do this. Tongyi Lab oversees the development of the Qwen series of large language models (LLMs), which have become some of the most popular models in China for businesses, academics, and consumers. Almost all the Qwen models are released on highly permissive open-source licenses, allowing individuals to download them and external providers to offer them to customers without paying Alibaba. The models are also winning customers outside of China for their very low costs of inference i.e. usage and high performance: for example, Airbnb CEO Brian Chesky recently revealed that Airbnb’s customer service chatbot is largely powered by Qwen models.2

Read more

This Bismarck Brief will contribute to our exclusive upcoming AI 2026 Bismarck Strategic Report, which will feature in-depth analysis of the state of the artificial intelligence sector and technology, together with a comprehensive profile of key players. Upgrade or subscribe now to receive full access and never miss a report.

Sundar Pichai has been the CEO of Google since 2015 and the CEO of Google’s parent holding company Alphabet since 2019. With a market capitalization of nearly $3.5 trillion (GOOG) as of November 2025, Google is the fourth-most valuable company in the world.1 With yearly earnings of some $140 billion, it is also the most profitable company in the world besides Saudi Aramco. Google’s massive revenues overwhelmingly come from its core business in online search advertising, which makes up nearly 80% of its revenues as of 2024.2 Google is also a major player in the ongoing race to develop and commercialize artificial intelligence technology. Through the Gemini series of models and others, the company directly competes with AI labs like OpenAI, Anthropic, or xAI. At the same time, Google is also a major provider of remote computing and data storage capacity i.e. “cloud computing,” which requires the building and operation of large data centers full of high-end computer chips, that are also necessary to develop and offer AI models to users. Through Waymo, the company is also a leading contender in the nascent market for self-driving taxis. As CEO, Sundar Pichai is responsible for coordinating and overseeing these myriad moves in AI.

Read more

This Bismarck Brief will contribute to our exclusive upcoming AI 2026 Bismarck Strategic Report, which will feature in-depth analysis of the state of the artificial intelligence sector and technology, together with a comprehensive profile of key players. Upgrade or subscribe now to receive full access and never miss a report.

Microsoft is the second-most valuable company in the world as of October 2025, with a market capitalization of approximately $3.8 trillion (MSFT).1 The U.S. software conglomerate is also the single largest investor in and backer of OpenAI, the world’s leading artificial intelligence company and the most valuable privately-held company in the world with a valuation of $500 billion.2 Since 2019, Microsoft has cumulatively invested over $13 billion into OpenAI in exchange for a special albeit evolving partnership with the company, which has included provisions such as rights to use OpenAI’s intellectual property and a privileged ability to sell access to computing power and data storage to the company from its “cloud computing” platform Microsoft Azure.3 Microsoft is uniquely capable of funding big-budget investments into technology thanks to its diverse and highly profitable business empire spanning a range of basic software and hardware services, which have today made it the fourth-most profitable company in the world with yearly earnings estimated at $123 billion.4

Read more

Many of our world’s most formidable live players including Elon Musk, Sam Altman, and Bill Gates, as well as many cornerstone institutions of our society ranging from investment banks to the U.S. government, are betting their own economic and strategic futures on rapid near-term advancements in artificial intelligence technologies. The potential consequences of such breakthroughs are furthermore so profound that they merit close analysis in and of themselves. If achieved, such advances in AI will provide intelligence “too cheap to meter,” and through it unlock all other possible technological advancements as well as deliver unimaginable material wealth. AI pioneers such as Nobel laureate Geoffrey Hinton further believe such artificial intelligences will ultimately pose a remarkable risk to humanity, possibly even heralding the end of our time as the dominant species on Earth.1

While not everyone believes in the alternatively catastrophic or utopian transhumanist-inspired visions held by the technologists driving these developments, it is on some level a moot point, because these dizzying possibilities unlocked by AI have already captured the imaginations of the world’s most powerful economic and political institutions. Indeed, since the viral launch of ChatGPT by OpenAI in November 2022, we have witnessed three years of an escalating, almost all-of-society effort to harness the potential of AI for massive economic returns. The potential promise of AI to ameliorate or solve deep-seated problems like deindustrialization, demographic decline, or debt-funded entitlements is simply too tempting to ignore, and thus the question of AI touches on every facet of our society.

Already in June 2024, major corporations, tech giants, and utilities were set to spend around $1 trillion on capital expenditures such as data centers, chips, and the power grid to support them in the coming years.2 These expenditures were all financed with an unprecedented leveraging of financial resources from the richest people in the world, sovereign wealth funds, investment banks, and investment holding companies such as SoftBank, even with the backing of governments. So far, as of October 2025, the investment shows no signs of slowing down, with many more hundreds of billions of dollars invested. It is not just Silicon Valley software engineers or Wall Street financiers who are now asking themselves what their AI strategy is, but policymakers in Washington, party officials in Beijing, military planners in Moscow, civil servants in Brussels, and leaders hungry for development and growth from Paris and London to Abu Dhabi and New Delhi.

This immense spending has been facilitated by vast capital reallocation, which is perhaps best measured in the spectacular rise of the valuations of both publicly and privately traded companies tied to the industry. Such companies include those that are manufacturing and developing advanced chips such as TSMC, AMD, or Nvidia. It also includes companies building supporting infrastructure and data centers such as Amazon or Oracle, and of course AI labs themselves that are making mathematical and theoretical advances in AI such as OpenAI, DeepSeek, Meta, Google, xAI, Mistral, and Anthropic. It includes companies speculated to benefit from advances in AI via new hardware like humanoid robots or self-driving cars too, such as Tesla, Figure, or Xiaomi. Nearly all relevant companies span multiple categories as they try to organize the entire emerging technological stack, from silicon to inference, to their own advantage, and make deals to help finance themselves and secure further investments.

These valuations continue to reach new heights. Nvidia became the first company in history to reach a market capitalization of $4 trillion in early July 2025. By the end of July, Microsoft had become the second company to pass that milestone. Companies such as Alphabet, Amazon, Meta, and Oracle all hit their own all-time highs denominated in trillions of dollars. Is it so unthinkable now that one of these companies will soon become the first $10 trillion company? And one of the founders or executives of these companies the first trillionaire? These spectacular valuations are correlated with each other much more deeply than just a shared bet on a technological gold rush.

There are significant multi-billion-dollar cross-investments and complicated mutual ventures undertaken by these major infrastructure providers. Just last month, for example, Nvidia announced it will invest up to $100 billion dollars into their customer OpenAI, as the leading AI lab also deploys huge amounts of Nvidia systems.3 Nvidia CEO Jensen Huang then in turn publicly expressed surprise when, not long after, OpenAI signed a multi-year chip supply deal with his competitor AMD, where OpenAI was given the option to buy up to a 10% stake in the chip supplier.4 OpenAI CEO Sam Altman has stated more such deals are in the works, with OpenAI already investing in their suppliers such as Nvidia, AMD, Oracle, and Broadcom.

This brave new world of data center financing, where sellers are subsidizing buyers, has raised concern from financial observers for how seemingly circular some of the deals are. Many of the commitments that collectively run into the trillions of dollars that are now being made are paid for not with revenue but with increases in the value of publicly or privately traded stock, appreciations driven by the announcements of the deals themselves.5 The AI industry has now grown to such an extent that it is likely propping up the world’s largest economy. Without these technology-related categories, U.S. GDP growth in the first half of 2025 reportedly would have been just 0.1% on an annualized basis rather than the 4% it recorded.6 The dollar value contributed to GDP growth by AI data center buildout has reportedly surpassed U.S. consumer spending for the first time ever.7

If, absent our great bet on AI growth, the U.S. economy is already in a recession, this means Western policymakers have a strong incentive to continue supporting further investment into AI, regardless of the technical, financial, or economic fundamentals, just to continue propping up favorable economic figures lest they face severe consequences. In that sense, nearly every asset class has come to be correlated with AI. What does risk diversification even mean in such a macroeconomic environment?

Many Silicon Valley insiders and outside observers have now raised the possibility that we are in a potentially devastating global financial “AI bubble.” Amazon founder Jeff Bezos recently stated that there is in fact an AI bubble, driven by a lack of investor discernment between good and bad ideas, but that it is an industrial bubble, where society will ultimately benefit from the legitimate innovations and infrastructure created.8 It is important to add that even if he is correct in making this distinction it would be of little consolation to hasty investors who stand to lose billions. Either way, bubbles do not pop themselves, but rather just keep growing—and, of all the power players in the world today, in whose interest is it to pop this possible bubble? The answer to this question could easily be the most valuable piece of financial information in recent history.

Those seeking to protect their wealth or seize new growth opportunities will have to go beyond financial sector best practices, textbook answers, and press releases, instead pursuing investment strategies based on completely new thinking. While you might not think you’re interested in AI or that it is irrelevant for your business, family office, or policy work, this societal and economic phenomenon of AI is certain to affect you and your interests. You ignore it at your own risk—and that is even assuming it does not result in new science, advances in robotics, greater automation in manufacturing, and transformations in the military balance of power, all of which are perhaps much likelier outcomes than utopia or catastrophe.

I believe technological breakthroughs in AI and their consequences merit close strategic analysis based on exceedingly accurate rather than incomplete or misleading information. Unfortunately, with so many interested parties trying their best to shape narratives and markets—as well as mislead competitors—the epistemic commons cannot be relied upon. Because of this, I am convinced that today, more than ever, navigation-grade analysis should be made available to the hundreds of key live player decision-makers who help steer our civilization to a better future.

We at Bismarck Analysis have been closely following and advising key players in the development of artificial intelligence since our founding in 2017, five years before the AI boom began in earnest. Through our firm’s near-decade of strategic consulting and research commissioned by top AI industry insiders, many of whom have since become household names, our firm has developed unparalleled, deep expertise across technology, economics, politics, business, and strategy to deliver accurate analysis that does not overlook the implications of any of those aspects, something truly unique among the research organizations and consulting firms in any industry today.

Our confidential work for our private clients over the years has reviewed the entire semiconductor manufacturing supply chain from optics through chip design, the geopolitical dynamics of AI competition and cooperation, the likely energy fundamentals of an AI revolution and their consequences, the key scientists working on AI technology, and the financial interests and flows funding the sector. Both top investors and CEOs have relied on us to guide their investment, philanthropic, business, and political strategies.

Our more publicly-accessible work, namely Bismarck Brief, is moreover already a trusted and relied-upon wealth of knowledge and intelligence on the AI landscape. We have already examined multiple players in every layer of the AI technological stack, including energy, minerals, semiconductor manufacturing, chip design, software, hardware, and the AI labs themselves. This was not done through trend-chasing or by happenstance, but it instead came about through following a systematic, multi-year research plan aimed at mapping out and forecasting the technological landscape of one of the most important developments of our era. Over the course of the coming months, we will continue to methodically investigate the key organizations and live players relevant to AI, releasing some of these as case studies to our Bismarck Brief subscribers, which you can read at our new AI 2026 segment.

More importantly, because of the immense importance of accurate information about and deep analysis of these developments, we will for the first time ever offer an exclusive annual comprehensive report going even further beyond the scope of our Briefs, titled AI 2026: Bismarck Strategic Report. At an estimated final length of between 225 to 275 pages, this industry-grade document will feature all of the information and analysis a live player needs to navigate this new AI-driven world:

• In-depth case studies of all the world’s frontier AI labs, including both U.S. giants like OpenAI, Anthropic, and Google as well as Chinese upstarts like DeepSeek and Moonshot AI.

• Player profiles of all the key figures in the AI boom, such as Sam Altman, Demis Hassabis, Bill Gates, Mark Zuckerberg, Larry Ellison, and Elon Musk—examining their personal ideologies, backgrounds, capabilities, and goals.

• Up-to-date data presentation and analysis on data center construction, electricity consumption, and energy build-out potential in the U.S., China, Europe, and Arab Gulf states.

• List and evaluation of key AI scientists and living traditions of knowledge advancing the field, also reviewing the relative strength of different countries’ mathematical traditions to help gauge where new AI researcher talent is likely to come from in the near future.

• Analysis of key players providing capital to fund AI development, including major cloud providers like Microsoft and AWS, venture capitalists, and governments.

• Analysis of all key players in the semiconductor design and manufacturing stacks including Nvidia, TSMC, ASML, and Carl Zeiss, as well as rising Chinese domestic challengers and others.

• Overview of key domains where progress in AI is expected to have near-term transformative impact, including robotics, autonomous vehicles, and drone warfare.

• Analysis of geopolitical implications of various AI scenarios, examining impacts on the balance of power between the U.S., China, Europe, Russia, and other states.

• An opening first-principles analysis as well as a concluding letter to live players by our founder and president Samo Burja, synthesizing and summarizing key recommendations for executive decision-making and providing grounding in the big picture takeaways.

This new annual strategic report will feature our signature crisp style and analysis, extensive sourcing for further reading, and custom-made charts, tables, and graphics to aid understanding. The report will be delivered on July 15, 2026 to help set the next year’s strategic goals. Similar comprehensive reports have been previously reserved for our most valued clients such as corporate partners and high-net worth individuals, or have been very rarely released publicly such as our white papers on nuclear nonproliferation (2018) and machine tools manufacturing (2020).

In order to purchase access to AI 2026: Bismarck Strategic Report, simply upgrade or become a paid subscriber to Bismarck Brief at the new AI 2026 tier using the button below:

Subscribe to AI 2026

Subscribers will also receive full access to our catalog of 200+ Briefs investigating the world’s most strategically relevant live players, institutions, and industries, as well as new Briefs in their inbox over the coming weeks and months—including Briefs that will contribute to the final AI report—every Wednesday at 2pm GMT sharp. To get the most value from our ongoing and methodical research, do not delay, but make sure to subscribe immediately and never miss a word. Those already subscribed at the previously-named Client tier will of course receive complimentary access to AI 2026 and do not need to take any action.

If you are interested in hiring us for additional customized research and in-depth strategic consulting on AI, please contact us here or reply to this email. If you do not wish to purchase access to the full AI 2026 report, but you wish to become a paid subscriber to Bismarck Brief, click the button below and simply subscribe at the monthly or annual rates:

Subscribe now

I look forward to hearing the thoughts of our sophisticated and intelligent readership on this unprecedented and unique investigation into the economic and political landscape of artificial intelligence.

Sincerely,

Samo Burja

Founder and President, Bismarck Analysis

This Bismarck Brief will contribute to our exclusive upcoming AI 2026 Bismarck Strategic Report, which will feature in-depth analysis of the state of the artificial intelligence sector and technology, together with a comprehensive profile of key players. Upgrade or subscribe now to receive full access and never miss a report.

Moonshot AI is a Chinese artificial intelligence startup founded in March 2023 by currently 33-year-old CEO Yang Zhilin, a leading researcher in the field of natural language processing and the development of the transformer architecture that underpins recent advances in large language models (LLMs), through widely-cited papers such as XLNet and Transformer-XL. Through its flagship Kimi series of models, the company develops both open-source and paid models that have become notable for their high performance and cost-efficiency. The company’s Kimi K2 model, for example, performed extremely well both on benchmarks and in practice for generating code as well as when it is used as an “agent” performing multiple tasks in sequence, becoming the world’s leading open-source model following its release in July 2025.1 The company has raised at least $1.2 billion at a valuation of over $3 billion as of late 2024, including from multiple of China’s tech giants, making it one of the best-funded AI startups in China.2 Moonshot employs around 300 people and is based in Beijing, with an office in Shanghai.3 In Chinese, the company’s name translates as “Dark Side of the Moon.”

Read more