The US Leads the AI Arms Race - For Now

China is in proof-of-concept phase while the US grows at scale.

I’ve been browsing the 2025 Tech Trends Report from CB Insights and their take on what this coming year has in store for the AI arms race. As of now, the US is still at the front, but the lead is narrowing. While the US continues to dominate in AI funding and talent, China is gaining fast, especially in the area of large language models (LLMs) and open-source innovation. Here’s a breakdown of the current landscape and what’s coming next.

The US Dominates AI Funding — But for How Long?

In 2023, US startups captured 71% of global AI equity funding — a significant share, considering how fragmented the AI landscape is across continents. Europe and Asia lag far behind with only 14% and 13%, respectively.

This massive funding influx has allowed US firms to build infrastructure, scale AI models, and drive research that is pushing the field forward. The lion’s share of this investment is funneled into areas like machine learning frameworks, cloud-based AI services, and, of course, the training of massive LLMs like GPT and its successors. The speed at which US companies like OpenAI, Google, and Anthropic have advanced in this field is a direct result of their ability to attract capital.

That being said, funding is just one piece of the puzzle. AI scalability, driven by cloud infrastructure and access to high-performance GPUs (like Nvidia’s A100), is also a critical factor. The US has a stronghold in both, but China's growing cloud infrastructure and its burgeoning AI hardware market may soon give it an edge.

Talent: Still Centered in the US, But China Is Catching Up

In addition to funding, the US has another advantage: AI talent. Over 40% of the world’s AI companies right now are based in the US, which creates a concentrated innovation ecosystem. This is no different from previous tech booms, where graduates from MIT, Stanford, Carnegie Mellon and the like produce world-class researchers in deep learning, computer vision, and NLP.

But China is making substantial strides. In 2023, Chinese universities and research institutions published nearly as many papers on AI as their US counterparts. This surge in academic output is backed by significant state and private investments in AI research. BAT are not just developing cutting-edge models, they’re also scaling up AI talent by offering competitive salaries and recruiting top-tier scientists from around the world.

China’s LLM Push: The Next Big Threat to US Dominance

China’s biggest challenge to the US’s AI lead is in the development of large language models (LLMs). While the US is home to some of the most well-known LLMs, including OpenAI’s GPT-4 and Google’s PaLM, China is catching up quickly with its own offerings.

Alibaba’s Qwen2, for example, has been making headlines as one of the top models on Hugging Face’s leaderboard. This model, along with others like Meta’s LLaMA-3 and Cohere’s Command R+, is pushing the boundaries of performance, particularly in natural language understanding and generation. What makes China’s strategy particularly interesting is its focus on open-source AI — a space where the US has yet to fully capitalize.

Chinese tech giants are actively building and investing in open-source LLMs to give developers and startups access to powerful tools without being locked into proprietary models like GPT-4 or BERT. This could fundamentally change the AI landscape by democratizing access to high-quality AI models, while also creating new competition for US-based companies.

The Infrastructure and Innovation Race: Who Has the Edge?

While the US still has the lead in AI funding and talent, China is focusing heavily on AI infrastructure to catch up. China’s growing dominance in AI-specific hardware, including AI chips designed by companies like Huawei and SMIC (Semiconductor Manufacturing International Corporation), gives it a potential advantage in training large models without relying on US-based providers like Nvidia.

Furthermore, China’s state-backed funding for AI startups and research centers is designed to foster rapid development of AI technologies at scale. The US has its private sector giants, but the Chinese government’s ability to direct large sums of investment into strategic areas — including AI models, hardware, and talent — could create a more resilient ecosystem in the long run.

Can the US Hold Its Lead?

The US is still leading in several key areas, particularly when it comes to capital and talent. However, China is closing the gap, especially in AI infrastructure and LLM development. Over the next 3-5 years, we’ll likely see both countries continue to pour significant resources into AI, creating a more competitive landscape.

This competition is particularly important for industries like healthcare, autonomous vehicles, finance, and national security, where AI will play a pivotal role in innovation and economic growth. The next big question: Can the US hold its lead in LLMs, or will China’s investments in open-source AI and hardware give it an edge?

As the arms race heats up, we’ll continue to see which country can truly dominate AI — and how this competition will shape the future of tech, global power dynamics, and innovation.