• June 25, 2022

Rocket.Build 2019: Creating next-generation AI experiences

We’ve all heard the expression “to think outside the box” a few times in our lives. (“Thinking outside the square,” in other parts of the world.) It’s a simple metaphor that means to think differently, unconventionally, or from a new perspective—necessary ingredients in software development, and problem solving.

At Rocket.Build this week, we’ve invited participants to do nothing but think differently to solve the biggest customer challenges. When we considered today’s greatest difficulties for customers, one such challenge became obvious. Customers and legacy-businesses are having problems understanding all of the dark, unmapped mysteries of their IBM Z, Power Systems, and embedded database platforms. When we were choosing the four themes meant to inspire this year’s Rocket.Builders, this problem was clearly an important one.

The technologies and platforms we create software for are like a “black box” to many of their modern end-users. They don’t know what’s inside the box, they’re afraid to touch it, and they just don’t know all of its quirks and intricacies. And as the generations of mainframers/legacy-developers have turned over, the original platform expertise which has allowed these systems to run has dwindled day-by-day. Few people know to use these systems, and it’s very hard for anyone new to understand what’s happening in the background of these business critical platforms.

So, how can we think outside the box to help customers crack open the box? That’s exactly the question that our theme, “Creating next-generation AI experiences,” is meant to answer.

For us, the theme of AI-driven next-generation experiences is multidimensional. We have so much power with AI and machine learning today that we can use intelligent programs to learn about systems, natively, and provide that information to users. No more mysterious black box. Can we go further? Can we discover everything, and can we correlate what we learn and send it to our models to definitively answer the question: what’s here? Can we answer definitively what normal behavior is, what does it look like when things go wrong, and what does peak-workload actually look like?

We can further use AIs to analyze system performance, and user behaviors to find patterns and predict outcomes. In essence, use AIs to see in the dark, unmapped reaches of the “black box.”

What it means to be “next generation” has a few interpretations for this year’s Rocket.Builders; two flavors, if you will. Most commonly when we talk about “next generation,” we are referring to elevating the technology of today, trying to design and solve for tomorrow’s problems. But our second interpretation is more literal, because we also want to keep in mind the next generation of engineers, end-users, systems administrators, and people who may have never worked on these systems before. People who are graduating from college, and even children who aren’t even been born yet! How do we make these platforms approachable to these next generations, and therefore new workloads, while still managing today’s current workloads? AI is definitely one way!

We want to enable customers to see in the dark using artificial intelligence. This week, Rocket.Builders are working to make life easier for customer’s developers, users, and end-users, enable them to hire new talent, to train them, and to become productive sooner. I can’t wait to see what the teams come up with!

Anjali Arora 0 Posts

Rocketeer emeritus


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