Keep your Data Scientists and GPUs busy - Reduce your time-to-result?

This presentation addresses the following topic(s):

• When is cloud more efficient than on-premises computing, and vice versa? How should these hybrid environments be managed? (Alternately: Discuss the efficiencies and inefficiencies of operating all on-prem, all cloud, and hybrid.)
• Specialization vs. standardization: How do you maximize specific application performance without creating silos?

The challenges of building an efficient architecture for Machine Learning are not only related to buying and implementing great infrastructure, it is also important to make it useful for Data Scientists. If your Data Scientists can concentrate on their main tasks the time-to-result will improve and your investments will payout sooner than expected. To achieve that you must have the right data, in the right format, in the right place, at the right time, with the right performance.