Eric Schmidt: Why America needs an Apollo program for the age of AI


First, more dedicated government AI supercomputers need to be built for an array of missions ranging from classified intelligence processing to advanced biological computing. In the modern era, computing capabilities and technical progress have proceeded in lockstep. 

Over the past decade, the US has successfully pushed classic scientific computing into the exascale era with the Frontier, Aurora, and soon-to-arrive El Capitan machines—massive computers that can perform over a quintillion (a billion billion) operations per second. Over the next decade, the power of AI models is projected to increase by a factor of 1,000 to 10,000, and leading compute architectures may be capable of training a 500-trillion-parameter AI model in a week (for comparison, GPT-3 has 175 billion parameters). Supporting research at this scale will require more powerful and dedicated AI research infrastructure, significantly better algorithms, and more investment. 

Although the US currently still has the lead in advanced computing, other countries are nearing parity and set on overtaking us. China, for example, aims to boost its aggregate computing power more than 50% by 2025, and it has been reported that the country plans to have 10 exascale systems by 2025. We cannot risk acting slowly. 

Second, while some may argue for using existing commercial cloud platforms instead of building a high-performance federal computing infrastructure, I believe a hybrid model is necessary. Studies have shown significant long-term cost savings from using federal computing instead of commercial cloud services. In the near term, scaling up cloud computing offers quick, streamlined base-level access for projects—that’s the approach the NAIRR pilot is embracing, with contributions from both industry and federal agencies. In the long run, however, procuring and operating powerful government-owned AI supercomputers with a dedicated mission of supporting US public-sector needs will set the stage for a time when AI is much more ubiquitous and central to our national security and prosperity. 



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