China gaining on U.S. in AI technology arms race- silicon, models and research
Introduction:
According to the Wall Street Journal, the U.S. maintains its early lead in AI technology with Silicon Valley home to the most popular AI models and the most powerful AI chips (from Santa Clara based Nvidia and AMD). However, China has shown a willingness to spend whatever it takes to take the lead in AI models and silicon.
The rising popularity of DeepSeek, the Chinese AI startup, has buoyed Beijing’s hopes that it can become more self-sufficient. Huawei has published several papers this year detailing how its researchers used its homegrown AI chips to build large language models without relying on American technology.
“China is obviously making progress in hardening its AI and computing ecosystem,” said Michael Frank, founder of think tank Seldon Strategies.
AI Silicon:
Morgan Stanley analysts forecast that China will have 82% of AI chips from domestic makers by 2027, up from 34% in 2024. China’s government has played an important role, funding new chip initiatives and other projects. In July, the local government in Shenzhen, where Huawei is based, said it was raising around $700 million to invest in strengthening an “independent and controllable” semiconductor supply chain.
During a meeting with President Xi Jinping in February, Huawei Chief Executive Officer Ren Zhengfei told Xi about “Project Spare Tire,” an effort by Huawei and 2,000 other enterprises to help China’s semiconductor sector achieve a self-sufficiency rate of 70% by 2028, according to people familiar with the meeting.
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AI Models:
Prodded by Beijing, Chinese financial institutions, state-owned companies and government agencies have rushed to deploy Chinese-made AI models, including DeepSeek [1.] and Alibaba’s Qwen. That has fueled demand for homegrown AI technologies and fostered domestic supply chains.
Note 1. DeepSeek’s V3 large language model matched many performance benchmarks of rival AI programs developed in the U.S. at a fraction of the cost. DeepSeek’s open-weight models have been integrated into many hospitals in China for various medical applications.
In recent weeks, a flurry of Chinese companies have flooded the market with open-source AI models, many of which are claiming to surpass DeepSeek’s performance in certain use cases. Open source models are freely accessible for modification and deployment.
The Chinese government is actively supporting AI development through funding and policy initiatives, including promoting the use of Chinese-made AI models in various sectors.
Meanwhile, OpenAI’s CEO Sam Altman said his company had pushed back the release of its open-source AI model indefinitely for further safety testing.
AI Research:
China has taken a commanding lead in the exploding field of artificial intelligence (AI) research, despite U.S. restrictions on exporting key computing chips to its rival, finds a new report.
The analysis of the proprietary Dimensions database, released yesterday, finds that the number of AI-related research papers has grown from less than 8500 published in 2000 to more than 57,000 in 2024. In 2000, China-based scholars produced just 671 AI papers, but in 2024 their 23,695 AI-related publications topped the combined output of the United States (6378), the United Kingdom (2747), and the European Union (10,055).
“U.S. influence in AI research is declining, with China now dominating,” Daniel Hook, CEO of Digital Science, which owns the Dimensions database, writes in the report DeepSeek and the New Geopolitics of AI: China’s ascent to research pre-eminence in AI.
In 2024, China’s researchers filed 35,423 AI-related patent applications, more than 13 times the 2678 patents filed in total by the U.S., the U.K., Canada, Japan, and South Korea.
References:
https://www.wsj.com/tech/ai/how-china-is-girding-for-an-ai-battle-with-the-u-s-5b23af51
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Big Tech’s $400 Billion AI Spending Spree:
Alphabet’s GOOGL, Microsoft, Amazon and Meta Platforms are set to spend nearly $400 billion this year on capital expenditures, largely to build their artificial-intelligence infrastructure. That is more than the European Union spent on defense last year. Those firms and others plan to boost outlays even more. Morgan Stanley projects $2.9 trillion in spending from 2025 to 2028 on chips, servers and data-center infrastructure. The investments, the bank says, will contribute as much as 0.5% of U.S. gross domestic product growth this year and next.
Companies are splurging because artificial intelligence promises to remake the lucrative tech market. The big tech companies want to be among the AI leaders. But AI requires intensive data-crunching, forcing tech companies to spend big on construction of new data centers.
The recently passed One Big Beautiful Bill Act is expected to drive the spending even higher. It provides tax relief for companies that frontload investments, freeing up cash flow to increase spending even more.
The infrastructure demands are so huge, though, that companies don’t have enough cash to pay for the investments, according to Morgan Stanley, which estimates a $1.5 trillion financing gap.
Nearly 100,000 of those companies workers have been laid off since 2022, according to tracking website Layoffs. Among them are software engineers, whose work is being rapidly replaced by AI.
The AI investments are “a tremendous hit on margins,” said Gil Luria, an analyst with D.A. Davidson. Tech-company cost cutting, he said, is meant to soften the bottom-line blow.
One risk for companies is whether their large investments will pay off. Luria said company profits haven’t kept pace with their spending spree to date, though he is optimistic that increased productivity will ultimately justify the spending.
Investors in AI startups like OpenAI aren’t pressing the profitability issue yet, content to pour in more money so long as valuations keep rising. Other investors, however, have warned that the AI boom has become a speculative frenzy.
Meta CEO Mark Zuckerberg is exploiting ennui inside Apple’s AI unit, poaching disaffected engineers with pay packages that can run into the hundreds of millions of dollars, say people familiar with them.
https://www.wsj.com/tech/ai/tech-ai-spending-company-valuations-7b92104b
Big Tech companies are engaged in an artificial-intelligence arms race, each building data centers at a blistering rate. All together, the four giants spent $95 billion on capex in the second quarter, and much more than that is in the pipeline.
The companies have been giving annual capex guidance. Microsoft, whose fiscal year ended this quarter, declined to issue a fiscal 2026 projection, but put out a big number—over $30 billion—for the current quarter’s investments. That would see expenses rise by 50% on the year, but Chief Financial Officer Amy Hood cautioned that the growth rate would moderate through the fiscal year.
By contrast, Meta isn’t slowing down. After raising its 2025 capex guidance last quarter and inching it up this past week, Chief Financial Officer Susan Li said on the earnings call that the company “expects to ramp our investments significantly in 2026.” This is exceptional because Meta is the only one from this group that doesn’t operate a cloud to rent out these AI servers; it’s all for its own use.
Amazon is also proceeding full steam ahead. It used almost every penny of its second-quarter operational cash flows for $31 billion of capex, and guided to around $60 billion for the second half, putting it on pace for a stunning $115 billion for the year. Amazon leads the pack here, but unlike the other AI contenders, its number is inflated by large retail investments for warehouses, vehicles, and robots.
Alphabet isn’t slowing down either, raising its 2025 capex guidance considerably. And though Apple spends much less—$3.5 billion in the quarter—that’s still 61% higher than last year.
https://www.barrons.com/articles/takeaways-big-tech-earnings-ai-68402f1a?mod=hp_WIND_A_3_2