Featured Guest Speaker: Anil Kumar, Executive Director and Head of AI Industrialization at Verizon! As companies are looking to leverage cognitive technology, and deploying machine learning models, organizations need to make sure they have the correct people, processes, and technology in place to succeed. In this presentation, Anil will share what AI industrialization is and how Verizon is moving from pockets of AI/ML to AI/ML being implemente...

The world is facing a digital boom with massive amounts of data generated each and every day. There’s 40-times more bytes of data than the number of stars in the observable universe. And soon, a vast majority of the global GDP will be digitized. So, now what? After an unprecedented year of increased remote work, more data is being produced than ever before. In the age of open data, where intelligent applications are running on hybrid pla...

Featured Speaker: Colin Russel, Director of Data Science at the New York Times! The November Data for AI Event is hosting Colin Russel, Director of Data Science at the New York Times as our featured speaker and his session 'How the NY Times uses Machine Learning to create, curate, and optimize social media campaigns with Colin Russel, Dir. Data Science’! For large organizations such as the New York Times, creating and running various soc...

Expanding and Evolving within the Digital Revolution At the heart of the Digital Revolution is quick-term, short-term, and long-term growth and profitability. The acceleration of automation development from inception throughout the supply chain will drive customer demands now and in the future. Simply put, companies embracing faster a positive seamless digital customer experience will be the relevant companies for the future. Employing effecti...

Featured Guest Speakers: Gregory Brown, Vice President of Strategy and R&D, Advanced Technology Group at UPS and Laura Patel, Advanced Analytics Manager at UPS! About Data for AI: The Data for AI Community is geared toward innovative companies pushing the boundaries of what’s possible with Artificial Intelligence and cognitive technologies. This community is focused on the data side of AI including: Data Engineering, Data Preparation...

Federal agencies must shift fully to electronic records management by December 2022, when the National Archives and Records Administration will stop accepting new paper records. Successfully making that transition entails far more than simply digitizing existing documents. Meeting the goals set by M-19-21 demands changes to current business processes, dramatically different approaches to content classification, new systems that are digital thr...