Rossin College professors Jonas Baltrusaitis (chemical and biomolecular engineering), Xuanhong Cheng (bioengineering and materials science and engineering), Siddha Pimputkar (materials science and engineering), and Yahong Rosa Zheng (electrical and computer engineering) are among the six Lehigh University faculty members named Senior Members of the National Academy of Inventors (NAI).

High-performance computing (HPC) systems – advanced computing ensembles that harness deliver massive processing power – are used for a range of applications, and the demand for them has increased with the rise of generative artificial intelligence (AI). However, for both traditional uses and to advance the power of AI, technical advances in HPC are greatly needed, say Ewa Deelman and colleagues in a Policy Forum. “With international competition for leadership in computing intensifying, without a renewed commitment, we fear that the US will soon lose scientific computing leadership and technological independence,” say the authors. They outline how HPC systems are in a state of transition, shaped by both technology constraints and market forces. Among the major challenges for HPC systems are the wide use of chips with lower-precision arithmetic – insufficient for applications important for science, engineering, and defense – as well as the power consumption of current machines. Deelman and colleagues highlight how over time, the global HPC landscape has evolved, placing HPC in a geopolitical arena where nations compete for technological sovereignty. They provide examples of HPC-related initiatives in different nations, which “reveal deep-seated policy and technical tensions around national security, international collaboration, and market independence.” The authors write, “With this Policy Forum, we aim to bring attention to the totality of challenges and opportunities in HPC and advocate for a multiagency, ‘whole-nation,’ and internationally collaborative effort to reenergize HPC R&D.”

The UK government’s proposed ‘rights reservation’ model for AI data mining tells British artists, musicians, and writers that “tech industry profitability is more valuable than their creations” say leading academics.