Accelerate AI Modeling Velocity with AI Platform as-a-Service

Data Scientists are highly skilled individuals charged with, and trained in, the art and science of uncovering patterns from massive amounts of data. They want to, and should, spend their time thinking through and building models that offer deep and relevant insights into today’s healthcare, financial or even governmental challenges.

But as data sets continue to grow exponentially, with 463 exabytes of data projected to be created per day by 20251, Data Scientists often find themselves spending most of their time not on model building, but on ML infrastructure and operations challenges, so-called MLOps.

For Data scientist these include:

  • Seamlessly graduating from a single GPU notebooks proof-of-concepts, to multi-node distributed training frameworks and ETL pipelines
  • A choice and access to the best-in-class tooling for each step of the Model Development Lifecycle
  • Having turn-key access to sufficiently large AI compute infrastructure without having to learn new ML workflows

For IT teams these include:

  • Provisioning and managing the cost of compute infrastructure across on-prem, co-location and cloud, so-called hybrid- and multi-cloud environments.
  • Making large datasets available to data scientist in a low latency manor.
  • Managing internal team resource access, quotas and utilization.
  • Deploying and monitoring models from the lab to production systems on the edge

As businesses begin to see the need to scale their AI efforts, they’re realizing that the traditional IT/DevOps infrastructure approach is not suitable. That’s where our recently announced offering with Digital Realty and NVIDIA can help more Data Scientists models see the light of day – and help IT teams scale AI efforts across the enterprise.

Creating the Cloud for Data Scientists™

As businesses move towards scaling their AI infrastructure, Core Scientific Plexus™, an enterprise-grade NVIDIA DGX-Ready Solution, has become the best-in-class software preferred by Data Scientists to streamline workflows and AI operations, including features like:

  • Single Pane of Glass for Data Scientists and IT teams across On-Prem, CSPs, Co-location and Super Computing Centers
  • Walk up to to simplify large-Scale, multi-node training , tuning and monitoring.
  • Support to “burst” workloads to Public Cloud in a true multi-cloud fashion.
  • Workload Placement Recommendation Engine to maximize ROI

With Core Scientific Plexus™, Data Scientists get an unprecedented level of accessibility and ease-of-use of tooling, as well as making their data frameworks easier to use. Having a cloud-like user experience that both Data Scientists and IT teams are used to, Core Scientific Plexus™ helps to decrease the time spent on MLOps tasks and increase the model velocity of Data Science teams.

Deployed in the same facilities as the data, the Core Scientific Plexus™ software stack is “roof-local.” With direct access to their data, Data Scientists are able to avoid the costly and time-consuming tasks of moving and prepping of data not to mention egress fees.

Partnering with Digital Realty and NVIDIA, this solution offering is built for AI from the ground up. NVIDIA’s A100 systems in Digital Realty’s Platform Digital, running Core Scientific Plexus™ software, Data Scientists and MLOps teams can have a single pane of glass across their environment. This helps to significantly reduce the time it takes to train and tune models.

Get Started

As businesses see the need to scale their AI operations, and are considering “build vs. buy” for their AI infrastructure, new models make it easy to get started. Take a test drive today on Core Scientific Plexus™ powered by Digital Realty’s PlatformDigital on NVIDIA DGX A100 Systems and see how you can accelerate ROI with AI Platform as-a-Service.

 

Sources:1 https://seedscientific.com/how-much-data-is-created-every-day