Abstract: 

Artificial Intelligence (AI) has taken the spotlight in Data Sciences and Operations Research. As AI investment grows and becomes integrated into our financial systems, machinery, retail operations, supply chain and health, safety, security, environment (HSSE) systems, the complexity and risk increases. Terms like software factory, AI factory, data warehouses, and agile practices fill the literature to accelerate adoption of the complex efforts and risks of AI.

That said, a large percentage of AI deployments fail. This occurs from either moving too fast, too slow, or simply not moving forward at all. Many AI technologies are being deployed with uncertainty and no governing method or minimum standard guidelines needed to ensure success. Institutions and individuals are reacting to the allure of AI technology without creating a robust method of governance where the gap between business goals and technological innovation converge. A key to deployment discussions, often overlooked, is how to make sense of the enormous amount of unstructured data in image, video, audio, and text that has the highest value.

Session Outline:
This presentation explores:
- Why AI?
- Best practices from process to unstructured data
- Modeling technology across industry, academia, and government

Bio: 

Kirk DeBaets is a Senior Solution Engineer at Clarifai. He has an MBA and a passion for turning technologies into positive business outcomes. A former VP of Database Engineering in both the Investment Bank and Global Technology lines of business at JP Morgan Chase, he has spent the last several years working with customers to derive business value from their AI/ML investment.