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Will China’s AI boom rewrite the global order?

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Chinese AI models are closing the gap with Western models, with a growing number of companies and organizations now integrating them into their operations. This poses not only a competitive threat to American and other Western firms, but also a geopolitical risk: if this trend gains global traction, it could give the Chinese Communist Party a conduit for spreading propaganda, disseminating fake news, and siphoning sensitive information worldwide.

China has already proven it can compete with the United States in AI, despite operating under restrictions imposed by the U.S. government’s semiconductor export controls. In January, DeepSeek unveiled its R1 model, which delivered performance comparable to models from OpenAI or Google but, according to the company, was trained at a fraction of the cost and computing power, and requires much less computing power to run. Since then, other Chinese AI companies, including Alibaba, Huawei, and Baidu, have launched models with similar characteristics.

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חוויית VR במרכז האקספו בהנגז'ו

VR experience at the Hangzhou Expo Center

(AFP)

These models are now gaining traction in a field that, until recently, was dominated almost exclusively by Western, particularly American, companies. According to the Wall Street Journal, international banks, public universities, energy companies, and other businesses, mainly in Europe, the Middle East, Africa, and Asia, are adopting models from DeepSeek or Alibaba as alternatives to American ones. This is partly due to lower operating costs, which offset the modest gap in capabilities. HSBC, the world’s fourth-largest bank, has begun internal tests of DeepSeek’s models, as has Britain’s Standard Chartered. Saudi Aramco, the world’s largest oil company, recently installed DeepSeek in its main data center. In Japan, AI startup Abeja chose to develop custom models for the Ministry of Economy, Trade and Industry using China’s Qwen models instead of those from Meta or Google.

OpenAI remains the dominant player in the field, with ChatGPT’s app reaching 910 million downloads, according to Sensor Tower. But DeepSeek is emerging as a serious rival, with its app already boasting 125 million downloads. On Latenode, a platform that helps organizations build custom AI tools, at least 20% of users now choose DeepSeek models.

One key reason for the success of Chinese models lies in their strategic priorities. American AI companies invest heavily in breakthroughs and the pursuit of artificial general intelligence. Chinese companies, by contrast, focus on developing practical, immediately useful applications designed to attract new users. This may be less ambitious than building superintelligence, but it is more relevant for businesses today. Chinese firms also benefit from releasing many models as open source, giving users greater control over implementation and customization.

The immediate casualties of this trend are American AI companies, which spend vast sums developing advanced models and rely on large business contracts to generate essential revenue. OpenAI, for example, has been expanding its operations abroad, opening offices in Europe and Asia this year. Unsurprisingly, American executives are among the first to raise alarms about the global spread of Chinese models. ““The No. 1 factor that will define whether the U.S. or China wins this race is whose technology is most broadly adopted in the rest of the world,” Microsoft President Brad Smith told the U.S. Senate recently. “Whoever gets there first will be difficult to supplant.”

Chinese dominance in AI could have far-reaching consequences. DeepSeek’s R1 model, for instance, censors content inconvenient to the Communist Party, refusing to answer questions about events such as the Tiananmen Square massacre and asserting that Taiwan is part of China. Modern AI chatbots are already emerging as replacements for traditional search engines like Google. When such bots are tightly regulated by Beijing, they can easily become channels for spreading propaganda and misinformation in the confident, authoritative tone typical of generative AI.

At the same time, these models can serve as powerful surveillance tools. Chatbots can build detailed personal profiles of users. If Chinese companies grant government access to this data, Beijing could conduct sweeping surveillance of individuals worldwide, including those in sensitive positions, mapping their identities, roles, and potential vulnerabilities, and helping to identify people who might be susceptible to pressure or blackmail.

On a geopolitical level, much of America’s global power today rests on the fact that the technological products and services the world uses are largely developed, manufactured, and operated by U.S. firms. If China wins the current AI race, the United States could lose a significant share of that leverage, while Beijing gains it.



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Tech Companies Pay $200,000 Premiums for AI Experience: Report

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  • A consulting firm found that tech companies are “strategically overpaying” recruits with AI experience.
  • They found firms pay premiums of up to $200,000 for data scientists with machine learning skills.
  • The report also tracked a rise in bonuses for lower-level software engineers and analysts.

The AI talent bidding war is heating up, and the data scientists and software engineers behind the tech are benefiting from being caught in the middle.

Many tech companies are “strategically overpaying” recruits with AI experience, shelling out premiums of up to $200,000 for some roles with machine learning skills, J. Thelander Consulting, a compensation data and consulting firm for the private capital market, found in a recent report.

The report, compiled from a compensation analysis of roles across 153 companies, showed that data scientists and analysts with machine learning skills tend to receive a higher premium than software engineers with the same skills. However, the consulting firm also tracked a rise in bonuses for lower-level software engineers and analysts.

The payouts are a big bet, especially among startups. About half of the surveyed companies paying premiums for employees with AI skills had no revenue in the past year, and a majority (71%) had no profit.

Smaller firms need to stand out and be competitive among Big Tech giants — a likely driver behind the pricey recruitment tactic, a spokesperson for the consulting firm told Business Insider.

But while the J. Thelander Consulting report focused on smaller firms, some Big Tech companies have also recently made headlines for their sky-high recruitment incentives.

Meta was in the spotlight last month after Sam Altman, CEO of OpenAI, said the social media giant had tried to poach his best employees with $100 million signing bonuses

While Business Insider previously reported that Altman later quipped that none of his “best people” had been enticed by the deal, Meta’s chief technology officer, Andrew Bosworth, said in an interview with CNBC that Altman “neglected to mention that he’s countering those offers.”





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A Recipe for Tech Bubble 2.0

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The tech industry’s history is littered with cautionary tales of irrational exuberance: the dot-com boom, the crypto craze, and the AI winter of the 2010s. Today, Palantir Technologies (PLTR) stands at the intersection of hype and hubris, its stock up over 2,000% since 2023 and trading at a Price-to-Sales (P/S) ratio of 107x—a metric that dwarfs even the most speculative valuations of the late 1990s. This is not sustainable growth; it is a textbook bubble. With seven critical risks converging, investors are poised for a reckoning that could slash Palantir’s valuation by 60% by 2027.

The Illusion of Growth: Valuation at 107x Sales

Let’s start with the math. A P/S ratio of 107x means investors are betting that Palantir’s revenue will grow 107-fold to justify its current price. For context, during the dot-com bubble, Amazon’s peak P/S was 20x, and even Bitcoin’s 2017 mania never pushed its P/S analog to such extremes. shows a trajectory that mirrors the NASDAQ’s 2000 peak—rapid ascents followed by catastrophic collapses.

Seven Risks Fueling the Implosion

1. The AI Bubble Pop

Palantir’s valuation is tied to its AI product, Gotham, which promises to revolutionize data analytics. But history shows that AI’s promise has often exceeded its delivery. The AI winters of the 1970s and 1980s saw similar hype, only to crumble under overpromised outcomes. Today’s AI tools—despite their buzz—are still niche, and enterprise adoption remains fragmented. A cooling in AI enthusiasm could drain investor confidence, leaving Palantir’s inflated valuation stranded.

2. Gotham’s Limited Market

Gotham’s core clients are governments and large enterprises. While this niche offers stability, it also caps growth potential. Unlike cloud platforms or social media, Palantir’s market is neither scalable nor defensible against competitors. If governments shift spending priorities—or if AI’s ROI fails to materialize—the demand for Gotham’s services will evaporate.

3. Insider Selling: A Signal of Doubt

Insiders often sell shares when they anticipate a downturn. While specific data on Palantir’s insider transactions is scarce, the stock’s meteoric rise since 2023 has coincided with a surge in institutional selling. This behavior mirrors the final days of the dot-com bubble, when executives offloaded shares ahead of the crash.

4. Interest-Driven Profits, Not Revenue Growth

Palantir’s profits now rely partly on rising interest rates, which boost returns on its cash reserves. This financial engineering masks weak organic growth. When rates inevitably fall—or inflation subsides—this artificial profit driver will vanish, exposing the company’s fragile fundamentals.

5. Dilution via Equity Issuances

To fund its ambitions, Palantir has likely diluted shareholders through stock offerings. The historical data shows its adjusted stock prices account for splits and dividends, but no splits are noted. This silent dilution reduces equity value, a tactic common in bubble-stage companies desperate to fund unsustainable growth.

6. Trump’s Fiscal Uncertainty

Palantir’s government contracts depend on political stability. With a potential Trump administration’s fiscal policies uncertain—ranging from spending cuts to regulatory crackdowns—the company’s revenue streams face existential risks.

7. Valuation Precedents: The 2000 Dot-Com Crash Revisited

Valuation metrics matter. In 2000, the NASDAQ’s P/S ratio averaged 4.5x. Palantir’s 107x ratio is 23 times higher—a disconnect from reality. When the dot-com bubble burst, companies like Pets.com and Webvan, once darlings, lost 99% of their value. Palantir’s fate could mirror theirs.

The Inevitable Correction: 60% Downside by 2027

If Palantir’s valuation reverts to a more rational 10x P/S—a still aggressive multiple for its niche market—its stock would plummet to $12.73, a 60% drop from its July 2025 high. Even a 20x P/S, akin to Amazon’s peak, would price it at $25.46—a 75% drop. This is not a prediction of doom; it is arithmetic.

Investment Advice: Avoid the Sizzle, Seek the Steak

Investors should treat Palantir as a warning sign, not a buy signal. The stock’s rise has been fueled by sentiment, not fundamentals. Stick to companies with proven scalability, sustainable margins, and valuations grounded in reality. For Palantir? The only question is whether it will crash to $12 or $25—either way, the party is over.

In the annals of tech history, one truth endures: bubbles always pop. Palantir’s 2023–2025 surge is no exception. The only question is how many investors will still be dancing when the music stops.

Data sources: Historical stock price summaries (2023–2025), Palantir’s P/S ratio calculations, and fusion of market precedents.



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