The United States is in a global technology race it can still win, but only if it stops getting in its own way.
At the All-In Summit, Eric Schmidt is sitting on a couch next to Chamath Palihapitiya.
That’s the message from former Google CEO Eric Schmidt, who frames the contest not as a matter of destiny, but of will. “I want America to win. I am here because of the American Dream… People took a chance on me. I want the next generation to have that,” he said. He underscores the intensity of the fight, pointing to China’s demanding “996” work culture as the baseline for the competition. His plea to “not screw it up” is a direct appeal to stoke the nation’s unique innovation ecosystem and “make it go faster and faster.”
New data from the 2025 Global R&D Funding Forecast (GFF) shows why his warning is so urgent. The report forecasts a historic crossover by 2026, when China’s R&D spending is set to exceed that of the U.S., the culmination of a two-decade climb that lifted China’s share of global R&D from 4% in 2000 to roughly a quarter today. Schmidt argues the competitive ground is already shifting: “I had thought that China and the United States were competing at the peer level in AI… They’re really doing something more different than I thought… The result is they’re very focused on taking AI and applying it to everything,” he said.
You remember, we’re up against the Chinese. The Chinese work-life balance consists of 996… they all do it. That’s who you’re competing against. – Eric Schmidt
One of his top worries is a potential U.S. blind spot. While American tech focuses on the ultimate prize of artificial general intelligence (AGI), he warns China is relentlessly applying AI to capture the commercial present. “We better also be competing with the Chinese in day-to-day stuff: consumer apps, robots,” Schmidt said. “I saw all the Shanghai robotics companies… they’re attempting to do in robots what they’ve successfully done with electric vehicles.”
His second warning concerns a platform-level risk to American influence. “China is competing with open weights and open training data, and the U.S. is largely… focused on closed weights,” he said. The consequence, in his view: “The majority of the world… are going to use Chinese models and not American models.”
Glossary
- AGI (Artificial General Intelligence)
- AI that can perform broadly across domains at or above human level; no verified AGI exists today. Definitions of the term also vary.
- LLM (Large Language Model)
- Neural network trained on large corpora to predict tokens; used for chat, coding, and search-adjacent tasks.
- Transformer
- Neural architecture built on self-attention; backbone of most modern LLMs.
- Open weights / Closed weights
- Open: model parameters are released for use/modification. Closed: weights are proprietary; access via API/product only.
- R&D intensity
- R&D spending as a share of GDP (country) or revenue (company); a standard innovation metric.
- PPP (Purchasing Power Parity)
- Price-level–adjusted currency conversion used to compare spending across countries.
- 996
- Work schedule: 9 a.m.–9 p.m., six days/week; deemed illegal by Chinese courts but still reported in parts of tech.
Yet the data also reveals the core of America’s resilience: its private sector. While China is poised to eclipse the U.S. in PPP-adjusted R&D spending firepower, the dynamic is different in the private sector. In 2024, U.S. companies maintained a nearly 2.5-to-1 R&D spending advantage over their Chinese counterparts. This is where Schmidt’s optimism is rooted, in the muscle of a private sector China cannot yet match. This advantage is powered by giants like Alphabet ($49.3B), and Apple ($31.4B), not to mention Amazon’s $88.5B in “technology and infrastructure” spending. As Schmidt puts it, this is the engine of American exceptionalism: “We’re chaotic, confusing, loud, but we’re clever… We allocate capital smartly… We should celebrate this… make it go faster and faster… Don’t screw it up, guys.”
