On November 13th OpenAI released a document showing five major pillars for American AI to succeed in the AI infrastructure arms race. Open AI’s VP of Global Affairs Chris Lehane presented their “blueprint for AI innovation” at an event at the Center for Strategic and International Studies. Lehane explained that OpenAI‘s vision is based on their belief that “we’re going to have a world that’s either going to be built on democratic AI or autocratic AI.”
Talk of “democratic AI” signals to the world that America has recognized that we have entered the era of the AI arms race – a race to build AI infrastructure that will determine which country controls the destiny of AI. It also reflects a growing recognition in US government circles that the stakes have been raised in this critical competition with China, to build the compute power and infrastructure stack that allows AI to be built and deployed.
The five pillars announced by Open AI speak of the need to build AI opportunity zones or “data center clusters”, to create a North American AI alliance to counter the China bloc, to attract capital (estimated at $175 B) through private and Government backing, and the need to expand US electricity and nuclear power capability.
Lehane explained why it is imperative to invest in AI infrastructure today: “If we build AI infrastructure, we’ll ensure that democratic AI prevails over autocratic AI. The U.S. version prevails over the People’s Republic of China version. And so the stakes could not be bigger. This is a time for us to build this infrastructure,” he observed.
Meanwhile, Meta has announced its making available its open-source AI model Llama, to U.S. government agencies working on defense and national security applications, and private sector partners supporting their work. Nick Clegg, Meta President of Global Affairs said: “Responsible and ethical uses of open source AI models like Llama will not only support the prosperity and security of the United States, they will also help establish U.S. open source standards in the global race for AI leadership.”
This move comes amid heightened fears of Chinese AI activity after reports that Chinese research institutions with government ties have used Llama to develop their own AI models for potential military purposes. Meta said this use of Llama is unauthorized. Its terms prohibit the use of the models for “military, warfare, nuclear industries or applications, espionage” and other activities subject to U.S. defence export controls. However, because Meta’s models are public, the company has limited ways of enforcing those provisions against China.
The Chinese researchers used an earlier Llama 13B large language model (LLM) to construct the military-focused AI tool. Meta has been under scrutiny for its open-source approach and the US could come down heavily to regulate the use of open-source AI models.
Most experts agree that the US currently maintains its edge in the AI race, although assessing the state of AI is much harder given that much of government-funded AI development efforts are classified. The US advantage is based on robust infrastructure, a superior talent pool, and access to high-end Graphical processor units (GPUs) which are critical to build and deploy AI projects.
America’s private enterprise dominance in AI large language model development gives it a key advantage over China.
Large language models developed by US companies like OpenAI and Anthropic are ahead of LLM development in other regions. But China is making fast progress on LLM development and leads the US in the number of AI patents generated. For now, Chinese data censorship and US sanctions on high-end GPU exports is keeping China a few steps behind in the race.
The AI race is not just about technology but also about ethics. The US and China rushing into a dangerous AI race would be reckless, and risk everything. But the fear of losing the war is also causing a no-holds-barred arms race that could have potentially disastrous effects. Already a lot of top industry people are voicing their concerns on the situation:
Scale AI CEO Alexandr Wang recently said on X: “the most devastating AI safety scenarios can be avoided if the US leads in AI but the US government is investing 3-10x less than China.”
Bindu Reddy, CEO of Abakus.AI, too, warns against over-regulation saying on X:
In the end, the winner of the AI race may be the country that does the best job of integrating both private and public resources, combining efficient markets with aggressive R&D policies. One thing is for sure: governments around the world need to take AI very seriously.
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