Faster Data Science & Best Practices for Building AI-enabled applications

Digital transformation demands faster, more productive data science
-by Ian Swanson, VP of Product Management AI and ML, Oracle Cloud
Software Engineering Best Practices for Building AI-enabled applications
-by Rama Akkiraju, Director, IBM Watson Division

Agenda

6:00 Doors Open, Food & Networking
6:30 Presentation by Ian Swanson
7:30 Presentation by Rama Akkiraju
*** Please arrive by 6 PM due to Security ***

Abstract
The key to accelerating digital transformation is deploying quality machine learning solutions faster to operationalize decisions. With this mandate, organizations are racing to hire more data scientists. However, many do not fully realize the value of these teams and face roadblocks trying to scale their efforts. In this talk, we will go over the digital transformation mandate and learn steps you can take today to
meet growing demands for AI and machine learning use cases.

Speaker Bio
Ian Swanson is Vice President of Product Management AI and Machine Learning for Oracle Cloud. In this role, he oversees the product, market, and customer success strategy for Oracle’s Data Science Cloud. The Oracle Data Science Cloud empowers data scientists to deliver the business-changing insights executives expect in less time with self-service access to open source tools, data and computing resources,
while also improving the ability of IT teams to support that work.

Prior to Oracle, Swanson was CEO and Founder of DataScience.com which was acquired by Oracle, May 2018. DataScience.com provided an industry leading enterprise data science platform that combined the tools, libraries, and languages data scientists loved with the infrastructure and workflows their organizations needed. Earlier in his career, Swanson was an executive at American Express, Sprint, and CEO of Sometrics. Sometrics launched the industry’s first global virtual currency platform
in 2008 and was acquired by American Express in 2011. That platform — for which he earned a patent — managed more than 3.3 trillion units of virtual currency and served an online audience of 250 million in more than 180 countries.

Abstract
Advancements in computational power, and algorithms has brought Artificial Intelligence (AI) to the forefront in the past decade, taking AI out from ‘AI winter’. Many companies and developers are exploring AI as chatbots in customer support scenarios, as doctors’ assistants in hospitals, as legal research assistants, as marketing manager assistants, or as real-time face detection in security domain. Building high quality and scalable AI models or services takes specific kind of discipline, methodology and tools. While some of these processes, methods and tools overlap with traditional software engineering practices, several are new to AI domain. In this talk, I will share the best practices for building AI-enabled applications from personal experiences from running AI Operations team at IBM’s Watson division.

Speaker Bio
Rama Akkiraju is a Director, Distinguished Engineer, Master Inventor and IBM Academy Member, at IBM’s Watson Division where she leads the AI operations teams and also heads the AI mission of enabling natural, personalized and compassionate conversations between computers and humans. In her career, Rama has worked on agent-based decision support systems, electronic market places, and semantic Web services, for which she led a World-Wide-Web (W3C) standard.

Rama has co-authored 4 book chapters, over 50 technical papers. Rama has over dozen issued patents and 20+ pending. She is the recipient of 3 best paper awards in AI and Operations Research, also multiple awards at IBM. Rama has been named by Forbes as one of the ‘Top 20 Women in AI Research’ in May 2017. Her team’s work has been featured in various media. Rama currently serves as the President for ISSIP, a Service Science professional society for 2018.