trainML Models can now be copied between projects.

Save even more money with CPU-Only job instances.

trainML now provides unparalleled job flexibility by allowing jobs to specify multiple GPU types that can satisfy a job request. The trainML job scheduler will automatically select the most affordable GPU type available.

CloudBender™ now allows you directly connect to regional datastores without having to copy that data into or out of trainML persistent storage.

New job environments based on Python 3.9 are now available for all frameworks.

trainML Endpoints are now even more flexibile with the ability to bring-your-own-web-server.

Persistent Notebooks can now be compressed to free up space from deleted files stored in previous job runs.

CloudBender™ lets you connect your on-prem and cloud GPUs to the trainML platform and seamlessly run jobs on any CloudBender enabled system. When you start a notebook or submit a job, CloudBender will automatically select the lowest cost available resource that meets your hardware, cost, data, and security specifications.

trainML is making it even easier to run any GPU-enabled workload by allowing customers to use job images directly from NVIDIA's NGC Catalog.

Teams can now create collaborative projects to share access to jobs, datasets, and models.