AI Podcast Interviews Articles and Reports

Companies that use AI copilots experience numerous benefits, including streamlined processes, improved customer experience, and cost savings. Large language models (LLMs) form the basis of many AI copilot applications. While LLMs have a remarkable capacity to generate humanlike text, that same capability is the reason businesses need to exercise caution in order to prevent misapplications of this otherwise transformative technology. 

This interview analysis is sponsored by Riskified and was written, edited and published in alignment with our Emerj sponsored content guidelines. Learn more about our thought leadership and content creation services on our Emerj Media Services page.

Duke University Health Systems is composed of a world-renowned hospital and healthcare network. Duke University Hospital, one of their three hospitals in North Carolina, is nationally ranked in 14 adult specialties.

This interview analysis is sponsored by Aquant and was written, edited and published in alignment with our Emerj sponsored content guidelines. Learn more about our thought leadership and content creation services on our Emerj Media Services page.

Problems in different industries can look quite similar when looked at from the perspective of data. Though diverse business problems originate from distinct domains and needs, they often share a common thread and solution. 

Originally founded as Fair, Isaac and Company, FICO is a data analytics company founded in 1956. Based in Bozeman, Montana, the company is focused on credit scoring services, most notably its FICO score, which measures a person's creditworthiness. 

This interview analysis is sponsored by Uniphore and was written, edited and published in alignment with our Emerj sponsored content guidelines. Learn more about our thought leadership and content creation services on our Emerj Media Services page.

AI and machine learning have promising potential in the field of healthcare. However, there is one significant hurdle healthcare companies often encounter when trying to implement AI and machine learning. The data architecture of current legacy systems in healthcare settings prevents implementing many use cases and limits a company’s ability to benefit from these technologies fully.