Engineering suite of "Intelligent Applications" for the enterprises
In the last few years, we have witnessed the proliferation of AI getting adopted in the enterprises to solve some of the critical problems. This is true and applicable across all the major industries - including - Finance, Insurance, Telecom, Healthcare, Entergy, Internet Services and the like. The most apparent outcome of this wave of change is that the traditional applications are now being disrupted and are getting replaced with "Intelligent Applications".
In this talk, we would explore what makes "intelligent Applications" different from the traditional application and what are the technical challenges in designing, architecting, deploying and maintaining such systems at the enterprise scale. The talk would cover some of the important details in designing the enterprise-wide suite of intelligent applications, some of the architectural considerations and design patterns, and the best practices.
Outline/Structure of the Talk
Define intelligent applications
How are they different from traditional non-intelligent applications
Technical Challenges - What it takes to bring intelligence to applications
Architectural Considerations and Design Patterns.
Best Practices on designing, deploying and maintaining intelligent applications.
Tools, Technologies, and Frameworks that are emerged in the last few years to tackle these challenges
Understanding of what Intelligent Applications are, how best to design, build, deploy and manage them.
AI Engineers, Architects, and Data Scientists.
Prerequisites for Attendees
Prior knowledge in building products and exposure to machine learning is desired.
Prior knowledge of operationalizing machine learning systems would be good to have.