U.S. and EU to Share AI Expertise to Solve Global Challenges

In mid-June of 2022, Cerebras Systems announced a new feature that allows users to train some of the largest AI models in the world within a single CS-2 machine using a simplified software support scheme. The announcement highlights multiple capabilities that Cerebras sees as their competitive advantages over other companies. Notable examples cited include the ability to accommodate an entire training model within the memory, through Cerebras' Weight Streaming software on the Wafer Scale Engine (WSE), instead of splitting it across processors, as well as the ability for users to manipulate a few inputs within the software scheme and GUI to choose the scale of model desired for training (i.e., GPT-3 13B, GPT-3XL 1.3B). Cerebras claims that this advancement can cut down the setup of large model training runs from months to minutes, with the Cerebras software managing much of the initial setup.

Expertise is now a major concern for both HPC and AI centers, outranked only by budget concerns. When asked about barriers to furthering AI capabilities, AI-specific expertise was a significant concern. Popular responses included access to AI expertise (49%), skills in AI model development (47%), and skills in AI programming (36%). This development comes at a time when a third of HPC sites (33%) report a lack of knowledge or skilled staff and identified this issue among their top three barriers to expanding on-premises HPC. This data is from the eighth annual study of Hyperion Research's high-performance computing (HPC) end-user-based tracking of the HPC marketplace. It included 181 HPC end-user sites with 3,830 HPC systems.