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On July 10, 2025, NSF issued an Important Notice providing updates to the agency’s research security policies, including a research security training requirement, Malign Foreign Talent Recruitment Program annual certification requirement, prohibition on Confucius institutes and an updated FFDR reporting and submission timeline.
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This Track seeks to increase the capacity of only IHEs with low to medium RTRL. IHEs that are a good fit for this Track are those that have a low to moderate level of research activity and are in a position to identify high-promise discoveries/innovations, solicit disclosures of such discoveries/innovations, evaluate those discoveries/innovations and their product or service markets for protectability and product-market-fit potential, and protect IP thereby incentivizing and initiating a pipeline for subsequent translation activity to de-risk technologies, conduct proof-of-concept work, and advance technologies through partnership or new venture creation. Developing the building blocks for identification, pipeline development, evaluation, and IP protection activity is the primary aim of the ACT Track. Specifically, the primary goals of this Track are to build capacity and infrastructure for technology transfer units to develop a culture of innovation and entrepreneurship, grow innovation management capacity and process-supported
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In Seattle, a meteorologist analyzes dynamic atmospheric models to predict the next major storm system. In Stuttgart, an automotive engineer examines crash-test simulations for vehicle safety certification. And in Singapore, a financial analyst simulates portfolio stress tests to hedge against global economic shocks.
Each of these professionals—and the consumers, commuters, and investors who depend on their insights— relies on a time-tested pillar of high-performance computing: the humble CPU.
With GPU-powered AI breakthroughs getting the lion’s share of press (and investment) in 2025, it is tempting to assume that CPUs are yesterday’s news. Recent predictions anticipate that GPU and accelerator installations will increase by 17% year over year through 2030. But, in reality, CPUs are still responsible for the vast majority of today’s most cutting-edge scientific, engineering, and research workloads. Evan Burness, who leads Microsoft Azure’s HPC and AI product teams, estimates that CPUs
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For all the excitement around GPUs—the workhorses of today’s AI revolution—the central processing unit (CPU) remains the backbone of high-performance computing (HPC). CPUs still handle 80% to 90% of HPC workloads globally, powering everything from climate modeling to semiconductor design. Far from being eclipsed, they’re evolving in ways that make them more competitive, flexible, and indispensable than ever.
The competitive landscape around CPUs has intensified. Once dominated almost exclusively by Intel’s x86 chips, the market now includes powerful alternatives based on ARM and even emerging architectures like RISC-V. Flagship examples like Japan’s Fugaku supercomputer demonstrate how CPU innovation is pushing performance to new frontiers. Meanwhile, cloud providers like Microsoft and AWS are developing their own silicon, adding even more diversity to the ecosystem.
What makes CPUs so enduring? Flexibility, compatibility, and cost efficiency are key. As Evan Burness of Microsoft Azure points out,
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