Learn languages naturally with fresh, real content!

tap to translate recording

Explore By Region

flag Nearly half of enterprises waste millions on underused GPUs despite cost concerns, prompting tools like ClearML to boost efficiency via fractional GPU sharing.

flag A new ClearML report reveals that nearly half of enterprises are wasting millions due to underutilized GPU capacity despite prioritizing cost control and efficiency in 2025–2026. flag While 35% aim to improve GPU utilization, 44% still rely on manual workload assignment or lack formal strategies, creating delays in AI development. flag Cost management is the top challenge for 53%, and governance of data, models, and compute is a key priority for many. flag To address inefficiencies, ClearML has expanded support for fractional GPU partitioning on AMD Instinct GPUs, enabling multiple workloads to run simultaneously on a single GPU with automated, centralized management. flag The silicon-agnostic platform improves resource efficiency, reduces idle capacity, and supports heterogeneous environments—helping enterprises maximize ROI without increasing infrastructure costs.

22 Articles

Further Reading