Finally, we dub the lower left quadrant “Unprepared,” which reflects countries that are both lacking in technology and research and are also lacking from a funding perspective. Countries in the upper left quadrant we dub “Funding Positioned,” and are countries that have a strong funding stream but are behind in terms of technology and research. Countries in the lower right quadrant we dub “Technology Skilled.” These countries have a strong current technology and research platform but are lacking strong public and private investments. The countries that are in the upper right-hand corner we dub “Leaders ” these have both a robust technology and research platform (factor one) and substantial public/private investments (factor two). We interpret and name the quadrants as follows. The second factor is solely focused on investments, and so we name this field Investments.įigure 1 shows where a select group of countries sit along these sub-dimensions.
As a result, we name this factor Technology and Research. It is clear that all of the fields in the first factor are either directly related to technology or its use in research. One field, AI startups, was not closely associated with either factor and was dropped from further analysis. The second factor contained private and public investments in AI. The first factor contained country ranks by theoretical peak computer performance, number of processing cores, number of supercomputers, and maximal LINPACK performance achieved country ranks for the number of conference papers and journal papers and the country rank for the number of patents. In this factor analysis, two clear factors emerged. Closely related items can be mathematically combined into a composite factor, which aids in interpretation. Denford Thursday, May 13, 2021Īs with our previous analyses, we conducted a factor analysis to determine if any of the data elements were closely related. This resulted in ten distinct data elements. In order to analyze each country’s technology preparedness, we assembled a country-level dataset containing: the number and size of supercomputers in each country, the amount of public and private spending on AI initiatives in each country, the number of AI startups in each country, and the number of AI patents and conference papers each country’s scholars produced. In our most recent post, “ The people dilemma: How human capital is driving or constraining the achievement of national AI strategies,” we discussed the people dimension and so, in this piece, we will examine how each country is prepared to meet their AI objectives in the second pillar-the technology dimension. In a follow-up piece, “ Winners and losers in the fulfillment of national artificial intelligence aspirations,” we discussed how different countries were fulfilling their aspirations along technology-oriented and people-oriented dimensions.
Our prior reports for Brookings, “ How different countries view artificial intelligence” and “ Analyzing artificial intelligence plans in 34 countries,” detailed how countries are approaching national AI plans, and how to interpret those plans. Nonetheless, supercomputers can be found in most countries pursuing AI research.Īs such, much of the development of AI is predicated on two pillars: technologies and human capital availability. Mindful of the threats to security that are posed by supercomputers, a consortium of countries, including the United States, Germany, and South Korea, developed the Wassenaar Arrangement, which restricts the sale of, among other things, supercomputers that can be used for military purposes.
Current state-of-the-art supercomputers have over 60,000 massively parallel processors to approach petaflop performance levels. Early supercomputers used only a few extremely powerful processors but, in the late 1990s, computer experts realized that stringing together thousands of off-the-shelf processors would yield the greatest processing power. The term appeared in the late 1920s and the CDC 6600 (released in 1964) is generally considered to be the first true supercomputer. Professor, Management Department - Royal Military College of Canada