Authors: Earl Joseph, Steve Conway, Alex Norton
Publication Date: January 2021
Length: 10 pages
Since the dawn of the Supercomputer Era in the 1960s, a succession of base processors (CPUs) has attempted to satisfy HPC users’ nearly insatiable demands for fast solution times on a wide spectrum of challenging problems, combined with affordability and energy efficiency. Chief among these entrants were vector processors, which ruled the HPC market through the 1990s, then RISC processors, and then x86-based processors, which began their steep ascendancy at that time and continue to dominate the market today, often in tandem with GPUs or other accelerators.
By most objective measures, the United States is the leader in AI capability, both in its AI technology and its application. Whether looking at R&D spending, research capability, ecosystem support, or commercial deployment, the US is at the top or near the top of its global competition. That strength is derived largely from successes in the US private sector. In particular, computer companies in Silicon Valley and elsewhere have been at the forefront in developing new AI hardware and software technologies. A receptive user environment in areas such as web services, financial services, healthcare, and scientific research, among others, has created a virtuous dynamic between supply and demand for AI technologies and products. As a result, the depth and breadth of AI capability in the US is such that the country is well positioned to maintain its lead position in the near-term.
May 2020 | Special Report
China has emerged as the strongest regional contender to overtake the US in AI capability. The government has devised a strategy to attain global AI leadership by 2030, leveraging the country’s growing technological prowess, its enormous domestic market, and its position as the world’s second largest economy.
March 2020 | Special Report