Rockbridge Network Emerges as Power Center of Trump’s Second-Term Administration
Founder JD Vance, Now U.S. Vice President, Eyes 2028 Presidential Run
Treasury Secretary Scott Bessent Tipped as Potential Next Fed Chair

The powerful new conservative force in the United States, known as the Rockbridge Network, is tightening its grip on American politics. A complex web of key figures from the Trump administration and investment heavyweights is exerting massive influence across American society. At the center of it all is JD Vance, the U.S. Vice President and founder of Rockbridge, who is reportedly aggressively positioning himself for a presidential bid in the next election.

Rockbridge Played a Key Role in Trump’s Re-election

According to sources in both U.S. and Korean political circles, the political fundraising group Rockbridge is emerging as a central force of power in Washington. Founded in 2019 by Vice President Vance and conservative columnist Christopher Buskirk, Rockbridge aimed to build a political base for a new conservatism to replace the fading traditional Republican establishment.

Membership is exclusive—USD 25,000 grants access to events, while lifetime membership costs USD 1 million. The group spends approximately USD 75 million annually on political activities, including candidate support, shaping public opinion, and voter outreach.

Rockbridge made its name during last year’s U.S. presidential election. In April, Trump’s campaign was cash-strapped and facing a cornered position in the GOP primaries, as traditional donors like the Koch network supported Ron DeSantis and Nikki Haley. That’s when Rockbridge stepped in, injecting large sums of money into Trump’s campaign and recommending Vance as the running mate. Donald Trump Jr., a Rockbridge member, brokered the connection.

Notable Influence of Rockbridge Members

Rockbridge’s ability to exert such influence stems from the heavyweight names within its ranks. At the center is Peter Thiel, founder of Palantir and longtime mentor to Vance, often described as the network’s “puppet master.” Elon Musk, Tesla CEO and head of the Department of Government Efficiency (DOGE) in Trump’s second term, is also a member. Other prominent figures include the Winklevoss twins, who donated USD 1 million worth of Bitcoin to Trump; hedge fund titan Rebekah Mercer; White House Chief of Staff Susie Wiles; Secretary of State Marco Rubio; Treasury Secretary Scott Bessent; Health and Human Services Secretary Robert F. Kennedy Jr.; and Director of National Intelligence Tulsi Gabbard—all current members of Rockbridge and influential figures in the administration.

These figures are leaving their mark across the U.S. political landscape. Trump Jr., although holding no official title in the second Trump administration, has been instrumental behind the scenes, assisting with appointments and lobbying globally to expand Rockbridge’s reach.

Vice President Vance is rapidly solidifying his power. He made headlines in March when he interrupted a meeting between Presidents Trump and Volodymyr Zelenskyy of Ukraine, telling Zelenskyy to “thank America” in a stern tone. The moment symbolized a shift from America’s global policing role to an “America First” stance.

Vance’s ambition clearly points toward the next presidential election. Many believe he intends to inherit Trump’s political mantle and carry forward the “Trumpism” agenda. One foreign policy expert commented, “Rockbridge is a powerful alliance of America’s new economic elite and political power—and Vance stands at its center. If their plans come to fruition, Vance will become the standard-bearer of America’s new conservatism.”

Treasury Secretary Bessent Tipped for Fed Chair

Scott Bessent, Rockbridge member and Treasury Secretary, is a strong contender for the next Chair of the Federal Reserve. According to a June 10 report by Bloomberg, Trump’s advisors are backing Bessent for the role. The Fed Chair is nominated by the President and confirmed by the Senate, with a four-year term. Jerome Powell’s term ends in May next year.

Bessent, a respected figure on Wall Street, is spearheading key initiatives in the Trump administration, including U.S.–China trade negotiations and tariff policies. His expanded role has reportedly won Trump’s deep trust. Even in a power struggle with Elon Musk over the acting IRS commissioner position, Trump sided with Bessent.

Steve Bannon, former Trump strategist, praised Bessent, saying, “He proved during the volatile early months of Trump’s presidency that he could deliver on the promises. He’s not just competent—he’s someone global markets can trust.” Tim Adams, President of the Institute of International Finance (IIF), added, “Given the global financial community’s trust in him, Bessent is undoubtedly a strong dark horse candidate.”

Other potential Fed Chair candidates include former Fed Governor Kevin Warsh, whom Trump recently praised as “highly regarded.” However, Arthur Laffer, former University of Chicago professor and close Trump advisor, commented, “Bessent is excellent, but already has a major role and isn’t primarily a monetary policy expert. I told the President Kevin Warsh would be perfect for this position.” Additional names being floated include Kevin Hassett (former Chair of the White House Council of Economic Advisers), Fed Governor Christopher Waller, and former World Bank President David Malpass.

Meta Seeks to Acquire 49% Stake in Scale AI
Plans to Establish Superintelligent AI Research Lab Using Scale AI Talent
Major Overhaul Underway Following Weak Performance of AI Model 'LLaMA'

Meta, which owns the generative AI model "LLaMA," is planning a massive investment in Scale AI, the leading company in AI training data. Meta aims to establish a new "Superintelligence Lab" based on Scale AI's talent. Superintelligence refers to the next stage in AI development that surpasses human-level artificial general intelligence (AGI). As Meta falls behind Google and OpenAI in large language model (LLM) development, this move is seen as a strategic pivot to reclaim AI leadership.

Meta Seeks 49% Stake in Scale AI, Negotiating to Bring in CEO

According to reports from the Wall Street Journal, CNBC, and other foreign media on June 11 (local time), Meta is finalizing a USD 14 billion investment deal with Scale AI, led by CEO Alexandr Wang. Meta is also negotiating to bring Wang on board to lead AI research. Some forecasts suggest the investment may reach USD 15 billion or more. If completed, this would mark Meta’s largest external investment ever.

Through the deal, Meta will acquire a 49% stake in Scale AI. CEO Wang and key staff are expected to join Meta and lead the company’s new "Superintelligence Lab." Superintelligence refers to AI systems that exceed human cognitive abilities, going beyond AGI, which targets human-level intelligence.

Rather than acquiring Scale AI outright, Meta’s large-scale equity investment mirrors the strategies of Google and Microsoft, which have secured AI startup talent through partnerships or partial acquisitions. A similar example is OpenAI's recent acquisition of AI hardware startup "io," which brought on former Apple design legend Jony Ive.

This new lab is also seen as part of a broader restructuring within Meta’s AI division. The company has faced internal leadership conflicts, staff departures, and product failures. Although Meta launched its AI chatbot based on the LLaMA LLM series, the latest "LLaMA 4" model was delayed and failed to generate significant buzz. The next flagship model, "Behemoth," has also been postponed due to performance concerns. As a result, most of the 14 researchers leading Meta’s core AI efforts have reportedly left the company. Meta hopes that bringing in Wang will help it reassert itself in the AI race.

Data Labeling Becomes Crucial—Scale AI in High Demand

Founded in 2016, Scale AI rapidly grew by specializing in data labeling. The startup was initially backed by Y Combinator, the top Silicon Valley accelerator then led by OpenAI CEO Sam Altman. Scale AI built a business model that paid workers to label data for sale to AI developers. Initially, its major clients were autonomous vehicle companies, but its business surged as OpenAI ramped up LLM development, heavily relying on Scale AI for data labeling.

With the explosion of interest in ChatGPT in 2022, Scale AI saw a significant boost in business. Meta also became a client. Now, most major AI players—including OpenAI, Google, and Microsoft—are Scale AI customers, a testament to its technical edge and market dominance. As demand surges, the company's valuation has risen from USD 14 billion in 2023 to USD 25 billion in 2024, with revenue expected to more than double.

CEO Alexandr Wang became a billionaire as the company grew. In 2021, at age 24, he was named the world’s youngest self-made billionaire. As of April 2025, Forbes estimates his net worth at USD 3.5 billion. Wang is recognized for his extensive network within the AI industry. He once lived with Sam Altman during the COVID-19 pandemic and is well-connected across startups, big tech, and even government circles. He has attended elite gatherings like the Sun Valley Conference and was present at Donald Trump's inauguration in January 2025.

"It’s Not About Models, It’s About Data"—The Coming Data War in AI

Industry analysts say Scale AI’s rising value reflects the growing importance of data across all sectors—from IT to fashion and beauty—as companies incorporate AI into their operations. While technical innovation is crucial, high-quality, well-labeled data is increasingly recognized as the key to building smarter AI.

Data labeling plays a critical role in developing sophisticated AI tools. Often performed by low-wage workers in countries like Kenya and India, this labor-intensive task involves manually categorizing data—like identifying people or vehicles in autonomous driving footage or marking disease areas in medical X-rays. These workers typically earn USD 1.50–2 per hour, leading to criticisms of exploitation, though many in the industry argue that such labor is essential due to the massive volume of data required for training.

Labeling data is both time- and cost-intensive. Market research firm Cognilytica estimates that preparing and processing data accounts for 80% of an AI project’s total time. Other reports say labeling can take up 60–80% of development costs. The need for human oversight stems from AI’s current limitations in interpreting complex visual and audio content. As one tech insider noted, "A human can instantly recognize if a video is violent, but AI still struggles to make that distinction."

With tech giants like Meta turning toward superintelligent AI, the pace of AI evolution is expected to accelerate further. AI is already advancing from narrow AI (ANI), which handles specific tasks like voice recognition, toward AGI, capable of general cognitive functions. The next step is superintelligence—AI with intellectual capabilities surpassing humans.

Prominent experts like Nobel laureates Geoffrey Hinton (Physics) and Demis Hassabis (Chemistry, and CEO of DeepMind) predict that superintelligent AI could emerge within the next 10 years.

Incheon Airport Corporation Eyes Entry into European Airport Market
Overseas Operations Thrive in Indonesia and Beyond
Investment and Development Projects Underway in the Philippines and Uzbekistan

Incheon International Airport Corporation is going all out in the bidding race for the operating rights to an airport in Montenegro, Eastern Europe. The corporation has made a bold move by offering a higher fixed concession fee than its rival bidder, Corporación América Airports (CAAP), a Luxembourg–U.S. joint venture. If successful, this bid would significantly accelerate Incheon International Airport Corporation’s overseas expansion efforts, which have been ongoing since the early 2000s.

Incheon International Airport Corporation and CAAP Compete for Montenegro Airport Project

According to aviation industry sources on June 11, Incheon International Airport Corporation (IIAC) is ramping up its efforts to win the bid for the Montenegro Podgorica and Tivat Airport Development and Operation PPP (Public-Private Partnership) Project. The project involves expanding and operating Podgorica International Airport, the capital’s main airport, and Tivat International Airport, near the popular tourist destination of Kotor, under a 30-year concession. Both airports are currently operating beyond their annual capacity of 1 million passengers, making expansion essential.

IIAC’s main competitor is Corporación América Airports (CAAP), a Luxembourg–U.S. joint venture. The two bidders are employing markedly different strategies in a tight race. According to local Montenegrin media outlet Vijesti, which cited sources familiar with the bidding process, IIAC offered a fixed fee of USD 100 million and a variable concession of 35% of annual revenue. In contrast, CAAP proposed a slightly higher fixed fee of USD 101 million, but with a much lower variable share of 17%.

The evaluation of the airport concession bids is expected to conclude next month. The original assessment deadline, set for June 9, was recently extended. On June 9, Montenegrin Prime Minister Milojko Spajić announced on social media after a cabinet meeting that “the government unanimously accepted the bidding committee’s recommendation to extend the technical proposal review period by 30 days.” He added that the government, in cooperation with the International Finance Corporation (IFC) under the World Bank, would take more time to ensure the best decision in Montenegro’s national interest.

IIAC’s Global Push Since the 2000s

IIAC’s participation in the Montenegro airport bidding war is seen as a strategic move to further expand its global footprint. Since the opening of Incheon International Airport in 2001, IIAC has sought to diversify its revenue streams. Its first foray into overseas business came in 2009 when it won a USD 31.5 million airport consulting contract for the Erbil International Airport in Iraq.

For years, IIAC focused primarily on consulting services, transferring its operational expertise to overseas airports. However, things changed significantly in 2018, when IIAC was awarded the contract to operate Terminal 4 at Kuwait International Airport, becoming the first foreign entity to manage an international airport in Kuwait.

This success paved the way for a major breakthrough in 2021, when IIAC defeated major global airport operators, including Zurich Airport, to win a government-issued contract in Indonesia: the Hang Nadim International Airport (Batam Airport) Operation and Development Project. The USD 600 million PPP initiative involves IIAC taking a 30% equity stake in the airport operator and generating profits through a development-investment model.

Recognizing Batam’s strategic location, IIAC adopted a dual-track strategy to transform the airport into a key hub connecting Indonesia and ASEAN. This approach produced impressive results: Batam Airport's revenue, which was just USD 6.3 million at the time of acquisition, jumped to USD 1.54 million in 2023 and USD 17.0 million in 2024. Operating profits reached USD 2.20 million in 2023 and USD 2.35 million in 2024.

With a 30% equity stake in the airport, IIAC received approximately USD 430,000 in dividends last year alone—seven years ahead of the initially projected dividend timeline, originally expected around 2032.

Expanding Further into Southeast and Central Asia

Incheon International Airport Corporation (IIAC) continues to expand its overseas business portfolio actively. In 2024, IIAC secured its second investment-development project: the development and operation of Ninoy Aquino International Airport (NAIA) in Manila, Philippines, through a public-private partnership. Under the 25-year concession (2024–2049), the consortium—formed with San Miguel Corporation and other partners—will oversee the airport’s development, operation, and maintenance. IIAC holds a 10% equity stake, through which it will receive dividend income. The project is projected to generate approximately USD 26.6 billion in revenue over its duration.

In addition, in April, IIAC was named the preferred bidder for the Urgench Airport development project in Uzbekistan following an international competitive tender. This marks IIAC’s first entry into the Central Asian airport sector, with the project to be executed under a Build-Transfer-Operate (BTO) model, wherein a private developer constructs and operates the airport before transferring ownership.

If final negotiations—set to last three months—are successful, IIAC will invest approximately USD 145 million to construct a new passenger terminal with an annual capacity of 3 million travelers. IIAC will then operate the airport for 19 years, with actual operations expected to commence in 2029, following the completion of construction.

Because IIAC will retain full decision-making authority over the construction and operation phases, the project also allows for the involvement of South Korean construction and engineering firms. This structure not only enables strategic partnerships but is also expected to maximize the corporation's profitability.

Even at USD 29, a USD 446 Bag Won’t Sell
Luxury Brands Shaken by ‘China Risk’
Has China’s Luxury Boom Ended? Brand Value Plunges

The once-unwritten rule in China that “luxury goods are cheapest today” has become a thing of the past. Items that once flew off the shelves are now being offloaded at steep discounts—even in the secondhand market. This shift stems from China’s middle class drastically cutting back on luxury spending as it grapples with a dual burden of a real estate downturn and declining incomes.

However, this is not merely a symptom of weakened consumption—it also reflects the failure of sales strategies. Luxury brands, in their pursuit of short-term revenue gains, had focused overwhelmingly on expanding sales in the massive Chinese market. But analysts now argue that this approach has, in the long run, diluted brand value and prestige.

Luxury Brands in Distress: 90% Discounts, But No Buyers

On June 10 (local time), Reuters reported on the current state of a major secondhand luxury goods store in Beijing, stating, “The shadow of China’s economic downturn has reached the heart of the luxury empire.” On display was a Coach “Christie” handbag—once priced at USD 456—now marked down to just USD 31, still waiting for a buyer.

Nearby, a Givenchy G-Cube necklace, originally sold for USD 308, was priced at only USD 26—a staggering 93% discount. While standard markdowns in the luxury sector traditionally range from 30% to 40%, discounts above 90% are essentially considered clearance-level fire sales. And yet, even with these deep cuts, sales remain sluggish.

China’s secondhand luxury market saw rapid growth as consumers shifted toward used goods. However, that growth has been driven more by a surge in supply than by demand. Reuters cited a 2023 Zhen Consulting report stating the market grew by 20%, but the firm attributed this expansion primarily to a rise in sellers, not buyers.

China’s Demand Slump Hits Global Luxury Market

China was once one of the world’s largest luxury consumers, at one point accounting for a full third of global high-end sales. According to Bain & Company, China’s luxury market grew more than fourfold between 2011 and 2021, reaching a size of USD 66 billion. This boom fueled the rapid expansion of European luxury brands, which rode the wave of China’s consumer power.

Today, however, luxury stores across China are eerily quiet. As clear signs of economic slowdown take hold, consumers are tightening their wallets. Following the 2022 resurgence of COVID-19 and prolonged lockdowns in major cities like Beijing and Shanghai, China’s shift to a "With-COVID" policy has done little to revive consumer confidence. A slumping real estate market and rising unemployment have further dampened spending.

Roughly 70% of household wealth in China is tied to real estate. Years of falling property prices have left middle-class assets in disarray. Bloomberg Economics estimates that for every 5% decline in home prices, Chinese household wealth contracts by as much as USD 2.7 trillion. Youth unemployment is now over 15%.

As wallets grow lighter, many Chinese consumers have rushed to offload their once-coveted luxury goods in the secondhand market. According to Dashuai Consulting, the number of people trying to sell luxury items this year is up 30% from last year. New resale platforms like Enyu, Feiyu, and Ponhu have flooded the market—but the number of buyers has hardly changed.

A Growth Strategy That Backfired

This represents a worst-case scenario for luxury brands that spent the past decade chasing the “Chinese Dream.” The flood of products into the secondhand market is accelerating the erosion of brand prestige. In the past, luxury goods were a closed symbol system accessible only to a privileged few. Today, luxury has evolved into a mass consumer category—and a handbag that anyone can carry no longer functions as a “luxury” item.

This trend is especially pronounced among masstige brands—those that straddle the line between prestige and mass accessibility. Luxury brands can be segmented into three tiers: accessible luxury at the base, aspirational luxury in the middle, and absolute luxury at the top. However, the rise of masstige trends and widespread discount distribution channels in recent years have diluted the very concept of luxury. This explains why a Coach handbag sits unsold on a display shelf despite its rock-bottom price of USD 31.

To drive sales, many masstige brands resorted to oversaturating the market with limited editions, excessive logo use, and rapid expansion of offline stores in China. But these aggressive tactics ultimately backfired, damaging brand equity. The growing secondhand market has dealt the final blow. Items once priced at USD 2,194 are now being resold for just USD 219.40, demonstrating how the brand’s so-called “premium” can collapse in the face of market forces. What collapsed first wasn’t the price, but the credibility of the brand image.

In contrast, Hermès continues to thrive even during economic downturns by emphasizing exclusivity through high-end marketing centered on products like the Birkin bag. According to the Financial Times, Hermès has outperformed its rivals by focusing on a wealthy, tightly defined clientele. While other brands expanded their customer base during the pandemic through aggressive marketing and new “entry-level” products, Hermès doubled down on its core audience, generating steady demand. Notably, even in China, Hermès has avoided a sales slump. The brand’s strategy of selling only to verified prior buyers is widely regarded as a success.

ChatGPT Nears 800 Million Monthly Visits
AI Replacing Human-Centered Collaborative Structures
Concerns Grow Over Decline in Critical Thinking

With the rise of generative AI technologies like ChatGPT, traditional knowledge platforms built on collective intelligence, such as Wikipedia and Naver Knowledge-iN, are rapidly being pushed aside. While AI's summary-based response format enhances user convenience, it is also weakening collaborative models that reflect diverse perspectives and contextual depth. As information consumption shifts from exploration and discussion to instant answers and passive acceptance, the knowledge ecosystem appears to be undergoing a fundamental transformation.

Sharp Decline in Traffic to Traditional Knowledge Platforms

As of June 11, industry sources report that, for the first time, ChatGPT’s monthly web traffic has surpassed that of Wikipedia. While figures vary slightly depending on the data provider, numerous global market research firms—including the UK-based GWI—have confirmed that as of April, ChatGPT overtook Wikipedia in terms of monthly visits. In the U.S. specifically, ChatGPT's monthly traffic has steadily risen since its launch, reaching 780 million visits in April. In contrast, Wikipedia’s traffic dropped to 716 million, marking the beginning of a clear downward trend.

Wikipedia isn't alone in facing a user exodus. South Korea’s once-dominant Q&A platform, Naver Knowledge-iN, is also experiencing a similar decline. Once a bustling hub of user-generated questions and answers, both new question volume and participation rates are falling. According to Naver, the total number of questions on the platform dropped from 24.59 million in 2022 to 15.48 million in 2023. The downward trend has continued into 2024, with monthly questions falling from 1.25 million in January to just 930,000 in April.

Experts point to this shift as a prime example of how traditional knowledge platforms have struggled to adapt to changing UX (user experience) expectations. Platforms designed around the reliability and diversity of information are now perceived by modern users as overly complex and time-consuming. Especially in mobile environments, the dominant user behavior favors quick, concise answers with minimal clicks, further weakening the relevance of traditional platforms. KAIST computer science professor Jooho Kim explained, “Unlike platforms, AI can grasp the intent behind a question,” adding, “It’s like turning on a tap and having knowledge flow instantly.”

Community-Based Knowledge Models Under Strain

The developer community site Stack Overflow is also seeing similar disruption. According to the platform, only 16,207 posts were made between May 1 and 26 of this year—a dramatic drop from its 2023 monthly average of 65,787 posts, representing a 75% decline. Founded in 2008, Stack Overflow earned a reputation as a sacred space for developers to share and refine practical coding knowledge through peer Q&A.

Platforms like Wikipedia, Naver Knowledge-iN, and Stack Overflow are all built on the foundation of collective intelligence. Knowledge is developed and refined through the contributions, corrections, and debates of a broad base of users, each sharing their expertise and experience. This model goes beyond mere information sharing—it's a process of collaborative knowledge construction with high intrinsic value.

But AI is rapidly replacing that model. Chatbots and AI-powered search assistants based on GPT models are trained on vast amounts of human-generated data and can deliver polished, structured answers instantly. Users no longer need to scan through countless documents or forum posts in search of the best response. A single question now yields a singular, high-confidence answer. In short, knowledge creation and dissemination are shifting from “many-to-many collaboration” to “one-model response.”

Diversity and Trust — What AI Is Still Missing

Some experts warn that recent changes in the way people access information could severely limit both the diversity of perspectives and the interpretive depth available to users. Platforms like Wikipedia and Naver Knowledge-iN, for example, often offer a variety of answers to the same question, reflecting different viewpoints and encouraging users to think critically and form their own judgments. In contrast, AI typically provides a single response to a query, often without adequately explaining the reasoning or perspective behind it.

This raises concerns about the reliability of information. Generative AI generates answers based on pre-trained data, but that process is not immune to errors or bias. Particularly with complex topics or fact-sensitive issues, AI responses can sound authoritative while still containing inaccurate or misleading content. Unlike Wikipedia, where errors can be corrected by multiple editors, or Knowledge-iN, where incorrect answers may be challenged by other users, AI lacks a comparable verification mechanism—making its “one-shot” responses relatively vulnerable to unchecked misinformation.

Another key limitation lies in AI’s inability to foster debate, which is one of the core strengths of collective intelligence. Traditional platforms allow for the collision of competing interpretations, where users actively engage, defend their positions, and expand their understanding. AI, on the other hand, eliminates this dynamic, instead offering what it calculates to be the most statistically probable answer. While convenient, this design may inadvertently weaken users’ capacity for critical thinking. Even in an age of instant answers, there remains a vital need for space dedicated to discussion, dissent, and multilayered interpretation.

Planned USD 4 Billion Facility Investment Over Two Years
Expansion of Major Plants in Michigan and Beyond
GM CEO: "Supporting Jobs in the U.S."

As the United States shifts toward a protectionist economic model under President Trump’s revived trade agenda, global automakers are finding themselves at a crossroads. At the center of this transformation is General Motors (GM), which has announced a sweeping USD 4 billion investment—into its U.S. manufacturing operations. The move is widely interpreted as a direct response to the Trump administration’s 25% tariffs on foreign vehicles and auto parts, a policy aimed at reviving American industrial dominance.

GM’s decision is not only a defensive maneuver against rising import costs but also a signal to Washington of its willingness to align with the administration’s “America First” strategy. As automakers worldwide recalibrate their supply chains and production hubs, the U.S. auto sector is being fundamentally redrawn, with implications for global trade, domestic jobs, and the future of electric mobility.

GM Reconfigures U.S. Production Strategy

In a press release issued on June 10, GM revealed its plan to inject USD 4 billion over the next two years into expanding vehicle production across its American facilities. This significant investment will focus on increasing output of both electric vehicles (EVs) and internal combustion engine (ICE) models at three major plants in Michigan, Kansas, and Tennessee. With these upgrades, GM projects its annual domestic production to exceed 2 million vehicles.

A key part of the plan involves relocating production of two models currently assembled in Mexico—the Chevrolet Blazer and Chevrolet Equinox—to U.S.-based factories. The shift will not only expand production capacity for the Equinox in particular but also help GM reduce its exposure to the new import tariffs. In another significant shift, GM will revise its previous blueprint for a large, idle plant in Michigan. Initially designated for electric truck production, the facility will instead be transformed into a factory for SUVs and trucks beginning in 2027—vehicles that remain high-margin and popular among American consumers.

GM CEO Mary Barra reinforced the company’s vision, stating, “We believe the future of transportation will be led by American innovation and manufacturing expertise. Today’s announcement is a testament to our ongoing commitment to build vehicles in America and support American jobs.” This investment underscores GM’s dual strategy: future-proofing its product line while staying in step with a volatile policy environment.

Trump’s 25% Tariffs Trigger Industry-Wide Reactions

GM’s decision arrives in the wake of President Trump’s dramatic trade maneuver: a 25% tariff imposed on imported automobiles starting in April, later extended to include car parts. The administration’s goal is clear—pressure global automakers to reshore production and bolster American jobs. While the tariff on finished vehicles has thus far had minimal impact on domestic manufacturers, the inclusion of parts is a different matter altogether.

To cushion the blow, the administration introduced a temporary “tariff credit” mechanism. Vehicles assembled in the U.S. using imported parts are eligible for partial tariff relief—equivalent to 15% of the car’s value—until April 30 of next year. After that, the credit drops to 10% until April 30, 2027, at which point it will be eliminated entirely. For example, if a vehicle assembled in the U.S. is priced at USD 1,000, then the manufacturer will receive a USD 150 exemption from the 25% import tariff on components in the next cycle.

Still, the costs for automakers remain steep. CNN reports that roughly 50% of auto parts used in U.S. vehicle assembly are imported. Even with tariff credits in place, manufacturers are projected to face around USD 4,000 in additional costs per vehicle—expenses that will ultimately be passed on to consumers or offset by internal restructuring.

This policy landscape has created a dual incentive: either move production to the U.S. or pivot to higher-margin models that can absorb the tariff shock. For companies like GM, the calculus is clear—invest now or risk being priced out of the market later.

Global Automakers Reshape Their U.S. Strategies

GM is not the only automaker adjusting its sails. The entire global auto industry is reacting to the shifting American trade winds, and strategies vary by region and company.

In Germany, traditionally cautious manufacturers have begun moving aggressively. Volkswagen Group recently announced a landmark USD 5.8 billion investment in U.S.-based electric vehicle maker Rivian. The goal is to significantly expand EV production within the United States. Alongside this move, the company revealed plans to start local production of its Audi brand vehicles, which had previously been fully imported.

Japanese automakers are following suit, albeit more quietly. Toyota declared a staggering USD 13.9 billion investment in its battery manufacturing plant in North Carolina, positioning it as a strategic pillar for North American EV production. Honda has begun producing its Civic Hybrid and CR-V models in the U.S. and aims to increase its local sourcing ratio to over 30%, reducing dependence on foreign components. Nissan is expanding its Tennessee plant and preparing to shift some of its current production in Mexico to U.S. soil.

Hyundai Motor Group is pursuing what it calls “demand-customized production” in the American market. In 2024, Hyundai and Kia sold a combined total of 1,708,293 vehicles in the U.S., but many of their popular models—including the Elantra (136,698 units), Palisade (110,055 units), and Sonata (61,701 units)—were still manufactured in South Korea. That is likely to change. In a high-profile announcement at the White House on March 24, Hyundai Motor Group Chairman Chung Eui-sun committed to investing USD 21 billion over four years to establish a U.S.-based production system capable of building 1.2 million vehicles annually.

Some automakers are opting to adjust their product lineup rather than scale up U.S. production. The early casualties of Trump’s tariff war are affordable, entry-level models. Mercedes-Benz, for instance, is considering withdrawing its compact GLA SUV—which retails for USD 43,000—from the American market. Instead, the company plans to focus on luxury models such as the S-Class sedan, priced over USD 100,000. This shift underscores a broader industry trend: prioritizing high-margin vehicles that can better withstand the increased costs brought on by protectionist policies.

Micron Seizes the SOCAMM Market in Partnership with NVIDIA
Samsung Strikes Back with CXL and GDDR7
The Era of Customized Memory by Application and Chipset Has Arrived

The global memory industry is undergoing a seismic shift. For years, the battlefield was clearly drawn—Samsung Electronics and SK hynix reigned supreme, their rivalry centered around the high-performance High Bandwidth Memory (HBM) technology. These two South Korean giants shaped the direction of DRAM innovation, locking in market dominance. But in a move that may permanently alter the power structure of this so-called "DRAM Three Kingdoms," U.S.-based Micron Technology has entered the fray with a formidable new weapon: the SOCAMM (Small Outline Compression Attached Memory Module).

Micron’s announcement of SOCAMM’s commercialization not only upends the HBM-centric status quo but also introduces a radically different memory architecture into mainstream application. The timing is critical—artificial intelligence, large-scale computing, and real-time data processing are pushing conventional memory systems to their limits. Now, as industry demands diversify and technical bottlenecks multiply, the lines of competition are redrawn. In response, Samsung is deploying its CXL (Compute Express Link) memory to rebuild performance architecture, while also fast-tracking GDDR7 for graphic and inference-heavy applications. The battle for AI memory dominance has never been more complex—or more consequential.

SOCAMM and the Rise of a New Memory Architecture

Micron’s SOCAMM isn’t just an upgrade—it represents a conceptual shift in memory architecture. Scheduled to debut in NVIDIA’s next-generation AI accelerator GB300, SOCAMM will be deployed alongside HBM, creating a dual-memory structure tailored for the most demanding workloads. The GB300 platform combines NVIDIA’s Grace CPU and Blackwell Ultra GPU, designed for AI training, inference, and cloud datacenter workloads. When NVIDIA initiated the project, it tapped all three DRAM titans—Samsung, SK hynix, and Micron—to develop viable SOCAMM modules. Micron was the first to secure approval for mass production, a symbolic coup in the high-stakes memory war.

So, what makes SOCAMM revolutionary? Unlike conventional DRAM modules that connect through longer and more layered memory interfaces, SOCAMM links directly to the CPU or GPU, drastically reducing the distance and barriers between processor and memory. This architectural proximity eliminates data transfer bottlenecks and enables ultra-high-speed throughput, which is essential for high-performance computing (HPC), real-time video analytics, LLM (large language model) training, and autonomous vehicle systems.

In practical terms, SOCAMM allows the memory to sit next to the chip, processing data with minimal latency—solving a longstanding issue in conventional DRAM where physical distance and bus congestion limit performance. Furthermore, it operates with greater energy efficiency, superior heat dissipation, and lower power draw, making it an attractive option for data centers, edge computing environments, and AI server clusters that are increasingly sensitive to both performance and operational cost.

Another major advantage is its modular and flexible design. SOCAMM is compatible with existing motherboard infrastructure, unlike HBM, which requires specific packaging and thermal configurations. It combines cost-effectiveness with competitive performance, carving out a strategic "middle ground" in a market that often forces a choice between premium-grade performance and affordability. This makes SOCAMM ideal for a multi-tiered AI ecosystem, where not every workload demands HBM-class performance but still requires higher speed and reliability than standard DDR5.

Micron is leveraging its unique position—being able to produce both SOCAMM and HBM3E concurrently—to cover a broader swath of the memory demand curve. While Samsung and SK hynix remain focused on advancing HBM density and efficiency, Micron is betting on portfolio diversification to gain market share early. Should SOCAMM move from pilot projects to large-scale deployment, the memory market will shift from a single-tech dominance to a coexistence of heterogeneous architectures—each optimized for a different class of compute demand.

Samsung’s Strategic Pivot: Betting on CXL and GDDR7

In the face of Micron’s disruptive momentum, Samsung Electronics is doubling down on innovation—not by escalating the HBM arms race, but by pushing forward with CXL (Compute Express Link) memory technology. CXL is a next-generation high-speed interconnect that enables dynamic memory sharing between CPUs, GPUs, and other accelerators. It provides faster and more flexible data exchange, tackling one of the most persistent pain points in AI and HPC architecture: bandwidth bottlenecks.

Samsung envisions CXL as a central component of its future server ecosystem. Unlike traditional memory constrained by physical slots and rigid configurations, CXL memory allows modular and scalable connections across diverse compute resources. This flexibility is ideal for AI servers and cloud data centers, where workloads and performance needs change rapidly. CXL also supports memory pooling and tiering, which means systems can allocate memory dynamically depending on demand—boosting utilization rates and reducing idle resources.

Although the CXL market is still in its infancy, Samsung has made early and aggressive investments, positioning itself to lead as adoption scales. The company isn’t just developing memory modules—it’s attempting to reimagine the architecture of server infrastructure itself, separating memory from compute units and interlinking them in more efficient ways. While SK hynix and Micron continue refining performance in traditional memory formats, Samsung is exploring how to overcome the limitations of the motherboard itself.

At the same time, Samsung is preparing for the commercial rollout of GDDR7, a next-gen high-speed memory optimized for graphics and inference accelerators. GDDR7 outpaces GDDR6 by 1.4 times in speed and improves power efficiency by over 20%, making it indispensable for high-end gaming GPUs, AI graphic accelerators, and ultra-high refresh rate displays. Rather than promoting GDDR7 as a standalone solution, Samsung is integrating it into a modular strategy—pairing it with CXL and DDR5 to deliver custom-configured memory packages based on performance demands.

This strategic pivot—moving from single-tech competition to multi-tech coexistence—marks a profound shift in Samsung’s playbook. In a market fragmenting by application type, a singular memory solution is no longer viable. Samsung’s diversified portfolio aims to cover the entire performance spectrum, from ultra-high bandwidth to mainstream and specialized workloads.

A Fragmenting Market and the Road Ahead

The era of one-size-fits-all memory is over. As AI continues to evolve into various verticals—autonomous vehicles, generative AI models, edge analytics, immersive media—the memory needs of each workload diverge. What was once a unified race to build the fastest DRAM has turned into a multi-lane highway of innovation, with each manufacturer specializing in distinct directions. The DRAM "Three Kingdoms" are no longer battling for dominance over a single territory but are now mapping out new regions to claim.

This fragmentation presents both operational challenges and financial opportunities. Semiconductor companies must now maintain a wider product range, adapt to multiple interfaces, and support varying performance tiers—all while managing manufacturing cost and yield. However, the upside is considerable. Diversified demand creates new revenue streams and cushions companies from the volatility of any single product category.

Samsung’s recent commercial wins suggest that its diversified strategy is already paying off. The company was selected as the main supplier for NVIDIA’s flagship GeForce RTX 50 series and for the RTX PRO 6000D (B40), a budget-friendly AI accelerator tailored for the Chinese market. These contracts signal a strong rebound in profitability, particularly as AI demand spreads beyond hyperscale servers into consumer and enterprise-grade applications.

According to Kim Dong-won, a senior analyst at KB Securities, the increase in AI server deployments across industries is fueling demand for varied AI semiconductors, which in turn lifts the broader DRAM market. He notes that Samsung will increasingly benefit as the market shifts from a narrow HBM focus to a wider embrace of general-purpose memory solutions, including GDDR and DDR.

In the unfolding narrative of the DRAM Three Kingdoms, Micron’s SOCAMM has clearly opened a new front. Samsung’s push for architectural transformation through CXL, along with its upcoming GDDR7, marks a robust counteroffensive. SK hynix, meanwhile, continues to hold the crown in HBM supremacy—for now. But as memory technologies diverge to meet diverse computing needs, the future of this industry will not belong to a single ruler, but to those most adept at adapting to a multi-architecture world.