US Needs a National AI Strategy: A Sputnik Moment?

Written by: Stephen Hsu

Primary Source: Information Processing

The US needs a national AI strategy. Many academic researchers that could contribute to AI research — including to fundamental new ideas and algorithms, mathematical frameworks for better understanding why some algorithms and architectures work better than others, etc. — are not able to get involved at the real frontier because they lack the kind of curated data sets and large compute platforms that researchers at Google Brain or DeepMind have access to. Those resources are expensive, but necessary for rapid progress. We need national infrastructure platforms — similar to physics user facilities like an accelerator or light source or telescope — in order to support researchers at our universities and national labs doing work in machine learning, AI, and data science.

In contrast, China has articulated a very ambitious national AI plan which has them taking the lead sometime in the 2020s.

Eric Schmidt discusses these points in the video, declaring this a Sputnik moment:

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Stephen Hsu
Stephen Hsu is vice president for Research and Graduate Studies at Michigan State University. He also serves as scientific adviser to BGI (formerly Beijing Genomics Institute) and as a member of its Cognitive Genomics Lab. Hsu’s primary work has been in applications of quantum field theory, particularly to problems in quantum chromodynamics, dark energy, black holes, entropy bounds, and particle physics beyond the standard model. He has also made contributions to genomics and bioinformatics, the theory of modern finance, and in encryption and information security. Founder of two Silicon Valley companies—SafeWeb, a pioneer in SSL VPN (Secure Sockets Layer Virtual Private Networks) appliances, which was acquired by Symantec in 2003, and Robot Genius Inc., which developed anti-malware technologies—Hsu has given invited research seminars and colloquia at leading research universities and laboratories around the world.