Laser Focus World is an industry bedrock—first published in 1965 and still going strong. We publish original articles about cutting-edge advances in lasers, optics, photonics, sensors, and quantum technologies, as well as test and measurement, and the shift currently underway to usher in the photonic integrated circuits, optical interconnects, and copackaged electronics and photonics to deliver the speed and efficiency essential for data centers of the future.

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Editorial Advisory Board

  • Professor Andrea M. Armani, University of Southern California
  • Ruti Ben-Shlomi, Ph.D., LightSolver
  • James Butler, Ph.D., Hamamatsu
  • Natalie Fardian-Melamed, Ph.D., Columbia University
  • Justin Sigley, Ph.D., AmeriCOM
  • Professor Birgit Stiller, Max Planck Institute for the Science of Light, and Leibniz University of Hannover
  • Professor Stephen Sweeney, University of Glasgow
  • Mohan Wang, Ph.D., University of Oxford
  • Professor Xuchen Wang, Harbin Engineering University
  • Professor Stefan Witte, Delft University of Technology

Protect U.S. Advantage in Generative AI for Economic Success

By: NewsUSA

(NewsUSA) - The United States currently leads the world in its adoption of generative artificial intelligence (GenAI) and the potential for increased productivity and economic success is high. However, more work is needed to stay a step ahead of global rivals, according to experts at the Special Competitive Studies Project (SCSP), a bipartisan nonprofit organization.

Unlike industrial technologies such as the steam engine, GenAI can perform a range of functions with few barriers to widespread adoption and diffusion, and deliver more than four trillion dollars into the global economy, according to a new report from SCSP.

Some examples of potential economic functions of GenAI at the government level include a chatbot assistant to enhance end-to-end IRS electronic tax filing; improved data analysis, risk modeling, and policy simulation by the Federal Reserve; and streamlining permitting and licensing by agencies such as the Departments of Commerce and Energy.

In the report, the authors explain how the U.S. could boost the economic benefits of GenAI by boosting competitiveness across three building blocks of AI leadership: Compute, Data, and People.

Computing Control. Computing chip technology is the engine that drives GenAI, and access to computing power and resources is essential to sustain GenAI leadership. Although the largest chip design companies are located in the U.S., the majority are manufactured in Taiwan, which creates vulnerability in supplies for the U.S. and its competitors. Cloud computing allows for increased computing power, and the U.S. is a global leader in this area, which also can help prevent bad actors from deploying dangerous AI models. SCSP advises the U.S. government to follow China’s example and ensure that academic researchers can access large amounts of computing resources via the cloud in order to maintain our competitive edge.

Data Driving. Detailed data are the raw material for training AI models. Data should be treated as strategic assets that must be harnessed, but used in a way that protects Americans’ rights and complies with relevant legal regimes. SCSP calls for a national strategy for strengthening the digital infrastructure, including advanced networks for nationwide data storage, processing, and transport. Legislation is needed for data privacy and also for digital trade.

People Power. People are America’s most important asset to stay competitive in GenAI and maximize the economic potential. The administrative burdens of the current immigration system may discourage highly skilled AI experts from bringing their talents the U.S., and reform is needed to smooth the path for these individuals. In addition, improvements in high-quality STEM education and pathways for reskilling and training in the U.S. are vital to optimize the productivity benefits of GenAI. Skilled AI researchers and end-users will advance innovation, create workforce opportunities, and sustain national competitiveness.  

For more information, visit scsp.ai.

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