To assess the state of adoption of machine learning (ML) and AI, we recently conducted a survey that garnered more than 11,000 respondents. As I pointed out in previous posts, we learned many companies are still in the early stages of deploying machine learning:
Companies cite “lack of data” and “lack of skilled people” as the main factors holding back adoption. In many instances, “lack of data” is literally the state of affairs: companies have yet to collect and store the data needed to train the ML models they desire. The “skills gap” is real and persistent.
Read more at O’Reilly
