Artificial Intelligence (AI), Machine Learning, and Deep Learning are all topics of considerable interest in news articles and industry discussions these days. However, to the average person or to senior business executives and CEO’s, it becomes increasingly difficult to parse out the technical differences which distinguish these capabilities. …
I met last week with Ben Lorica, Chief Data Scientist at O’Reilly Media, and a co-host of the annual O’Reilly Strata Data and AI Conferences. O’Reilly recently published their latest study, The State of Machine Learning Adoption in the Enterprise. Noting that “machine learning has become more widely adopted by business”, O’Reilly sought to understand the state of industry deployments on machine learning capabilities, finding that 49% of organizations reported they were exploring or “just looking” into deploying machine learning, while a slight majority of 51% claimed to be early adopters (36%) or sophisticated users (15%). Lorica went on to note that firms identified a range of issues that make deployment of machine learning capabilities an ongoing challenge. These issues included a lack of skilled people, and ongoing challenges with lack of access to data in a timely manner.
Read more at Forbes
