HPE launches ML Ops Solution, Accelerates AI Deployments

Hewlett Packard Enterprise (HPE) recently announced a container-based machine learning solution supporting machine learning lifecycle in any cloud environment.

The solution, HPE ML Ops, allows the enterprises to standardize the ML workflows and improve the pace of AI deployments from months to days, said the announcement.

HPE Machine Learning Ops will harness the capabilities provided by the BlueData EPIC (Elastic Private Internet Clusters), as a software platform that facilitates the ML, AI, and Big Data analytics.

In 2018, HPE (Hewlett Packard Enterprise) acquired BlueData for its capabilities to use Docker containers to deploy large-scale machine learning and big data analytics environments in a cost-effective way.

Executive Opinion

SVP and CTO, Hybrid IT at HPE, Kumar Sreekanti, said, "Only operational machine learning models deliver business value. And with HPE ML Ops, we provide the only enterprise-class solution to operationalize the end-to-end machine learning lifecycle for on-premises and hybrid cloud deployments. We’re bringing DevOps speed and agility to machine learning, delivering faster time-to-value for AI in the enterprise."

Program vice president, Artificial Intelligence (AI) Strategies at IDC, Ritu Jyoti, said, "From retail to banking to manufacturing to healthcare and beyond, virtually all industries are adopting or investigating AI/ML to develop innovative products and services and gain a competitive edge. While most businesses are ramping up on the build and train phase of their AI/ML projects, they are struggling to operationalize the entire ML lifecycle from PoC to pilot to production deployment and monitoring."

More about the HPE technology advancement

HPE’s technology solution transforms AI initiatives from the experimentation and pilot stage to the enterprise-grade operations, and production stages, the announcement notes.

HPE ML Ops helps AI initiatives by supporting the entire machine learning lifecycle including training, data management, and monitoring.

Data science teams involved in the deploying and building ML models will be able to benefit from the HPE’s lifecycle management solution, said the announcement. The solution will also be compatible with the open-source deep learning platforms such as the TensorFlow, PyTorch, MXNet as well as commercially available applications of machine learning like Dataiku and H20.ai.
HPE has also been deploying the cloud and AI capabilities to facilitate the adoption of digital solutions across the foundations and enterprises.

The offering will come bundled as a subscription service along with the HPE Pointnext services and customer support.