Watson Studio, Watson Machine Learning and Urbancode
Your team is moving faster than ever before, including writing more software and making more frequent updates. The ability to inject production-worthy models into your application development has never been more critical.
Making your apps more powerful with prediction and optimization from AI and machine learning has gotten easier, yet meeting security, scalability and governance requirements for at-scale ML algorithms and apps is still a real challenge. In order for you to succeed and unleash the power of your team, you need the right set of DevOps, data science practices, modern architecture, and platform to build and run AI and cloud native applications.
Join IBM speakers as we share the problems that arise when teams push AI into apps. We will also address how you can tackle those problems to accelerate time to go live and drive monetization.
- Discuss why it is crucial to scale ahead in organizational design, processes and technologies
- Explore scenarios on choosing when to augment existing processes or re-platform and modernize your environments
- Tackle the most common issues and opportunities we face
- Demonstrate examples of AI-powered modern apps