When my team works on projects, sometimes we work across three or four systems and environments to experiment and complete a model. For each environment we have to configure systems to work with the notebook files and datasets we are working off of. 

Passing the projects assets from system to system is an inconvenience for version control, but my biggest pet peeve is configuring and restarting environments over and over again even though our core assets or system requirements have not. 

Just yesterday I had to work across two online notebook systems and one on-prem system each serving its own purpose, whether it was deployment, centralizing data, or accessing available GPU. It was frustrating when kernels crashed and systems had to be restarted. For my on-prem system, re-running code proved fastest to return to the prior state, whereas the online systems required environment instances to be reset, proving repetitive and time consuming. 

In my experience, the Z by HP AI Studio simplifies the redundancy of re-configuration and restarting with its ability to create workspaces and share them across account members so everyone is working the same way and up to date. 

For me, it’s proving to save time. I’d love to hear what other testers are finding.