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Cloud-native environment considerations for decision makers—a webinar series
In this 3-webinar series, we’ll explore several considerations around cloud-native application development, design, and operations. The webinars in this series include:
- Choose your cloud-native path—an executive checklist
- Cloud-native, event-driven design for high-value use cases
- How explainable, predictive decision making can help us trust our AI models
Webinar 1: Choose your cloud-native path—an executive checklist
Speaker: Brian Gracely & Stu Miniman
With a cloud-native strategy, organizations can begin the culture, process, and technology evolutions needed to meet new demands and deliver business innovations faster.
In this webinar, we’ll discuss how to make decisions that benefit your business, developers, and IT operations teams, including how to:
- Boost developer productivity
- Maximize future choice and maintain control of your environment
- Capitalize on existing investments
- Make security a top priority
Webinar 2: Cloud-native, event-driven design for high-value use cases
Speaker: David Codelli
Event-driven architecture (EDA) is as old as computing itself, and some would say even older. The basic principle is quite clear: software should react immediately to changes sensed in the relevant environment. However, application of EDA and the design of EDA systems is different in the world of microservices. Additionally, the dramatic decrease in the cost of computing resources has whole new classes of problems that were previously intractable. These problems are addressable using a combination of technology, practices, and above all, a careful attention to design.
In this webinar, we’ll review some of these technologies and practices, and show how carefully designed systems are solving some of the most complex challenges the world faces.
Webinar 3: How explainable, predictive decision making can help us trust our AI models
Speakers: Matteo Mortari & Daniele Zonca
The demand has never been greater for transparent, explainable decision making that is accurate, consistent, and effective. Legislations like GDPR are a result of increasing concerns about privacy, safety, and transparency in general. While AI/ML solutions are great at making sense of high volumes of data, the reasoning process is usually quite opaque, sometimes leaving us baffled as to why it made a particular recommendation.
In this webinar, you’ll hear about the latest research in eXplainable AI (XAI), an approach that combines AI/ML and traditional business rules to better understand the factors that contribute to an automated decision. We’ll introduce you to the latest standards for representing decision logic, and we’ll demonstrate an XAI solution built from open source components that will show how we can finally answer questions about why an automated decision was made.