Lindsey Coombs is a Senior Editor for data and AI at SAS. She researches and writes on topics covering advanced analytics and evolving tech like generative AI. Lindsey is a seasoned communicator with more than 18 years of experience writing content for a broad range of industries and audiences. She is passionate about the safe and ethical use of technology that benefits humanity.
Fast-paced technology like AI can have barriers to entry. Whether infrastructure, data limitations, talent gaps or complying with rapidly changing regulations. Organizations from health care to manufacturing and the public sector are often stymied by these obstacles that can slow AI adoption and use. Ready-made AI models can bypass the
In 2012, Harvard Business Review declared the data scientist the sexiest job of the 21st century. Here’s what we knew at the time: big data was (and still is to this day) an enormous opportunity to make new discoveries. We were in the boom of user-generated content from social platforms,
Data scarcity, privacy and bias are just a few reasons why synthetic data is becoming increasingly important. In this Q&A, Brett Wujek, Senior Manager of Product Strategy at SAS, explains why synthetic data will redefine data management and speed up the production of AI and machine learning models while cutting
