Presentation: Building an AI in the Cloud



1:40pm - 2:30pm

Day of week:




Building a successful cloud-based A.I. dev platform on top of an open-source machine learning project is more complicated than one would imagine. Simply offering a hosted version of the project is hardly the answer. The secret to success is to differentiate the needs between the open-source users and the potential SaaS users. Oftentimes, they are of different species.

With years of experience building , Simon will walk through how the team at PredictionIO (acquired by Salesforce) navigated this roadmap and he will share the on-going challenges ML SaaS platforms face when developers try to build customized large-scale predictive applications on production environments.

Specifically, Simon will walk through these topics:

  • The ML platform product design dilemma 
  • The difference between building A.I. in a lab and for real applications on production 
  • The uniqueness of several predictive applications
  • The steps to build an end-to-end Machine Learning solution, from data sourcing to live monitoring
  • The future of A.I. dev platforms

Speaker: Simon Chan

Co-Founder @PredictionIO & Senior Director of Product Management @Salesforce

Simon Chan is a serial entrepreneur and product innovator, with 12 years of tech management experience in various cities including London, Hong Kong, Guangzhou, Beijing and the San Francisco Bay Area. Recently, Simon joins Salesforce as a Senior Director, Product Management to lead data science product development through the acquisition of PredictionIO. He was the founding CEO of PredictionIO - an open source Machine Learning Server that empowers programmers and data engineers to build smart applications. Following a successful launch in 2012, PredictionIO has become the most popular Spark-based machine learning project on Github. Simon holds a B.S.E. in Computer Science from University of Michigan, Ann Arbor and a PhD in Machine Learning from University College London.

Find Simon Chan at

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