I will share the vision and the production journey of how we build enterprise shared AI As A Service platforms with distributed deep learning technologies. Including those topics:
1) The vision of Enterprise Shared AI As A Service and typical AI services use cases at FinTech industry
2) The high level architecture design principles for AI As A Service
3) The technical evaluation journey to choose an enterprise deep learning framework with comparisons, such as why we choose Deep learning framework based on Spark ecosystem
4) Share some production AI use cases, such as how we implemented new Users-Items Propensity Models with deep learning algorithms with Spark,improve the quality , performance and accuracy of offer and campaigns design, targeting offer matching and linking etc.
5) Share some experiences and tips of using deep learning technologies on top of Spark , such as how we conduct Intel BigDL into a real production.
Session hashtag: #AI1SAIS
Suqiang Song is director and chapter leader at Mastercard, where directly oversees a team embedded within the data engineering and AI tribe. Suqiang blends deep business and technical expertise with a passion for coaching people, helping them grow and develop in their area of expertise and ensuring alignment on the “how” of the work they perform in squads.