Demand for AI could exceed computing capacity

AI, and generative AI in particular, is expected to greatly enhance productivity within work processes. Some studies estimate that generative AI could contribute between $2.6 trillion and $4.4 trillion annually to the economy. However, AI infrastructure is costly because the underlying algorithmic problems are extremely computationally intensive and this means there's a potential gap between demand and the capacity needed to meet it. A new report from OpenNebula Systems identifies key challenges, including data availability, scalability of centralized systems, power constraints, and the intricacies of accelerator manufacturing. The report estimates that this year a single AI training run will demand… [Continue Reading]