Presented By
O’Reilly + Cloudera
Make Data Work
March 25-28, 2019
San Francisco, CA

Yay, we are going to deploy an AI/ML-powered app. But wait! Where do I deploy?

Swatee Singh (American Express)
11:50am12:30pm Wednesday, March 27, 2019
Strata Business Summit
Location: 2018
Average rating: ****.
(4.00, 3 ratings)

What you'll learn

  • Learn why organizations should consider a fully or partially hybrid cloud environment for AI/ML deployments
  • Understand which public cloud offers the most features and capabilities

Description

Organizations are developing artificial intelligence and machine learning (AI/ML)-powered applications in increasingly large numbers. As the trend to use AI/ML to address needs from a variety of areas grows, companies will face two existential questions: Should they consider a fully or partially hybrid cloud environment for AI/ML deployments, and which public cloud will give them the most features and capabilities?

Swatee Singh discusses available options for companies facing these challenges. Most experts in this area agree that large global organizations will choose multicloud-capable hybrid platforms for their AI/ML needs. Such an approach brings remarkable benefits but also heralds a multitude of integration and deployment challenges unique to AI/ML workloads. Swatee explains what these challenges are and details possible solutions to address them.

Photo of Swatee Singh

Swatee Singh

American Express

Swatee Singh is the vice president of the big data platform and the first female distinguished architect of the machine learning platform at American Express, where she’s spearheading machine learning transformation. Swatee’s a proponent of democratizing machine learning by providing the right tools, capabilities, and talent structure to the broader engineering and data science community. The platform her team is building looks to leverage American Express’s closed loop data to enhance its customer experience by combining artificial intelligence, big data, and the cloud, incorporating guiding pillars such as ease of use, reusability, shareability, and discoverability. Swatee also led the American Express recommendation engine road map and delivery for card-linked merchant offers as well as for personalized merchant recommendations. Over the course of her career, she’s applied predictive modeling to a variety of problems ranging from financial services to retailers and even power companies. Previously, Swatee was a consultant at McKinsey & Company and PwC, where she supported leading businesses in retail, banking and financial services, insurance, and manufacturing, and cofounded a medical device startup that used a business card-sized thermoelectric cooling device implanted in the brain of someone with epilepsy as a mechanism to stop seizures. Swatee holds a PhD focused on machine learning techniques from Duke University.