Platform to Share, Discuss and Advise Enterprises on best use of AI.

Looking to understand the huge gap between AI/ML advances and enterprise usage? Looking to share experiences of successful usage and failed AI Projects?


AI Ops (for ex. IT Ops, HR Ops, Billing Ops) will impact most staff across enterprises; advances in chatbots, audio/video recognition technologies will bring huge process improvements to enterprises. We look closer at multiple case studies and ideas.

AiEthics is a fascinating area, something that will surely become a front-and-center concern for enterprises as they seek to build in AI into every application. We will carry essays from a wide range of contributors on this critical emerging area.

The DevSecOps /Agile SDLC process is the standard for all new digital projects.  In AiSEP, we will discuss enhancements needed to the processes, to ensure AI/ML applications are developed, taught, tested, secured and supported at production grade.

The mathematics and statistics behind Data Sciences are still very much relevant today. ML models that are being created by enterprises need massive amounts of quality data, which isn’t always available. We will hear from mathematicians, statisticians, data scientists, business leaders, and more. 

In the Case Studies section, we will discuss success and failure stories related to the deployment of AI, with a focus on what we can learn from these experiences.

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