Industrializing your AI and data science models with IBM Cloud Private for Data

Director for Watson and AI applications, IBM

Companies are entering “chapter two” of their digital transformation. The next chapter is all about moving from experimentation to true transformation. It’s about gaining speed and scale. We are helping businesses activate data as a strategic asset, with desire to maximize the impact of AI as core to the business strategy.

To do so, businesses must explore AI and become comfortable with data science embedded into business processes. Early open source data science and AI proofs-of-concept are beginning to mature. Businesses leaders are starting to seek help on how they can scale and industrialize these AI initiatives to meet their business needs.IBM Cloud Private for Data

At IBM, we acknowledge what our customers need to scale and industrialize open source AI. This obviously starts with the tools they have in place. And this can include many different technologies ranging from TensorFlow, Apache Spark, Keras or XGboost and also custom code built in open source languages like R, Python, or Scale. I like to call it as the “landscape of now.”

This isn’t a bad thing, but it’s a management challenge. How do we standardize on a platform? How do we make sure that we are betting on the right technology stack? What about security and privacy? Do we have the right skills in place? How do we enhance productivity of data scientists?

I want our clients’ data science teams to know: if you already have a preferred data science tools, increasingly more of which are also using Apache Spark or TensorFlow, we will help you bring it to IBM Cloud Private for Data.

Patterns to scale open source AI

IBM has observed patterns in the steps in takes to scale open source AI. This involves people, tools and the platform. The first step is to let the AI team to work with their favorite tools and framework in which they are comfortable. Second is to help govern the machine learning models and scripts using an enterprise wide tool. Step three: automate the model management and deployment process so data scientists can focus on the business logic and model outputs.

These steps will expand AI and bring it to all of your business units, so you can redefine every business process. That’s the true transformational moment in our customers’ business. The next frontier is to bring AI to every employee, so every function in the organization is amplified with AI.

Businesses are already working with IBM Cloud Private for Data to tap into lucrative opportunities to manage and scale their open source data science models, applications and processes. We’re helping them run on the same frameworks and languages their data science teams have been using. How? By managing and governing models spanning across on-premises or behind the firewall, and ensuring they can be easily ported to cloud using an underlying Kubernetes and containers foundation.

Freedom of choice and trust

The IBM Cloud Private for Data platform provides customers with the freedom to choose how and where they want to deploy their open source stack - on-premises, in the cloud, or both, and the freedom to change! Remember open source is not about “free,” It’s about “freedom.” IBM Cloud Private for Data delivers the trust, innovation and control so customers have the freedom to realize the value of their open source investments.

So how can your business get started?

  1. Discover how your data scientists, data engineers or AI team use open source today. Ask them which open source technologies they use, where they use it and what they use it for.
  1. Land simple open source data science workloads on IBM Cloud Private for Data. Identify which machine learning or data science models you will like to infuse in your business at scale. This could be risk analytics, customer churn, customer analytics or financial analytics.
  1. Scale your open source data science models on IBM Cloud Private for Data. Once on the platform, we can extend these models with world-class Watson services as well.

When provisioned on Red Hat OpenShift, IBM Cloud Private for Data creates a highly flexible, open source-savvy platform for modernizing and building a new generation of intelligent, cloud-native applications that more easily can tap into your data, wherever it resides.

We have been working with our customers to help them build, scale and deploy open source quickly so they don’t get left behind. These clients can bring new disruptive ideas to the market with speed so they can capture share-of-wallet swiftly in their respective industries.