TPC Alliance established: Targeting AI models with more than one trillion parameters to promote scientific discovery

According to news on November 16, leading scientific research institutions in the industry, the US National Supercomputing Center and many leading companies in the AI ​​field, recently jointly formed the Trillion Parameter Consortium (TPC).

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According to reports, this site learned that the TPC Alliance consists of laboratories, scientific research institutions, and academia around the world and scientists from industry to jointly advance artificial intelligence models for scientific discovery, with a special focus on giant models with a trillion parameters or more

The TPC consortium is currently working to develop scalable Model architecture and training strategies, while organizing and collating scientific data for model training to optimize the application of AI libraries on current and future exascale computing platforms

TPC aims to create an open A community of researchers developing large-scale generative AI models for scientific and engineering problems, in particular, will launch joint projects to avoid duplication of work and share methods, approaches, tools, knowledge and workflows. In this way, the consortium hopes to maximize the impact of these projects on the broader artificial intelligence and scientific communities.

TPC’s goal is to build a global network of resources, data and expertise. Since its inception, the consortium has established multiple working groups aimed at addressing the complexities of building large-scale artificial intelligence models. The exascale computing resources required for training will be provided by the U.S. Department of Energy (DOE). Available from several national laboratories in , as well as several TPC founding partners in Japan, Europe, and other countries. Even with these resources, training can take months.

Rick Stevens, associate director for computational, environmental and life sciences at the U.S. Department of Energy's Argonne National Laboratory and professor of computer science at the University of Chicago, said: "In our laboratory and with partner institutions around the world In the process of collaboration, our team is beginning to develop a series of cutting-edge artificial intelligence models for scientific research and is preparing to use large amounts of previously untapped scientific data for training."

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