Most enterprises are using only 25% of their GPU infrastructure on average.
Bringing models to production is painfully slow as static compute allocation limits progress.
The inability to efficiently utilize resources slows experimentation and is one of the primary reasons most enterprises don't see ROI from AI.
Building AI Infrastructure Optimized for GPUs, with Red Hat Openshift and Run:ai
Erez Kirzon, Principal Solution Architect at Run:ai
Overcoming AI Lifecycle Challenges using Openshift’s Ecosystem
Shon Hay Paz, Sr. Data Solution Architect at Red Hat
ML Dev to ML Ops with a click of a button
Boaz Goodovitch, Solution Architect at Matrix
