AI Race: Comes Down to Money-and Brains

EET: Despite the huge sums being poured into public and private sector AI development, some industry analysts argue still more investment is needed to keep pace with China — even if the AI goals of its “Made in China” technology initiatives remain mostly aspirational.

For example, Lux Research makes the case in a new report that the roughly $1 billion in U.S. investment in AI and quantum computing institutes won’t cut it when measured against the estimated $50 billion Beijing has pledged as part of the China Integrated Circuit Industry Investment Fund.

By comparison, western efforts represent small potatoes, the research firm asserts: “With private organizations like OpenAI raising $1 billion and Google spending more than $500 million each year on AI research, the question remains: Given the critical importance of these technologies to both national security and economic activity, why not invest more?”

More investment is likely coming, of course, via what congressional co-sponsors of the CHIPS for America Act call “real money.” In its present form, the CHIPS Act would allocate about $1.157 billion for U.S. AI research, according to a budget summary released by the American Institute of Physics.

Meanwhile, four U.S. companies — Accenture, Amazon, Google and Intel — are kicking in more than $160 million to help fund AI institutes to be launched next year by the National Science Foundation.

Industry watchers nevertheless insist those public-private efforts pale in comparison to China’s AI push. “We see China’s AI goals as well as the goals in other ‘Made in China’ technologies are becoming more aspirational and aggressive,” said Jerrold Wang, an analyst with Lux Research.

“The Chinese technologies in those fields are improving fast and China has become [a] top tier player in most of those fields, so the government’s targets are not just to catch up with the leading countries in the world, but to lead the world.”

Furthermore, Wang continued, “U.S-China economic friction make some of the U.S. technologies not available to the Chinese companies-like Huawei faces lockout from US chip technologies-which forces China to accelerate its internal R&D for developing the technologies comparable to or even more advanced than the global incumbent technologies.”

While China continues to spend its way to AI supremacy, it also leads in the number of technical papers published at AI research conferences. The same survey of papers published at the Conference on Neural Information Processing Systems also concluded that the current U.S. lead in AI research stems in large part from the ability of American companies and universities to attract and retain top China researchers.

Some things, it appears, money can’t buy.

Originally published at on September 10, 2020.