Most enterprise technology vendors just don’t have enough data to do proper AI, according to InsideSales CEO Dave Elkington.

The 2016 Expert Survey on Progress in AI is a survey of machine learning researchers that AI Impacts ran in collaboration with others in 2016. (more…)

Driven by a fear of losing out, many companies have announced AI-focused initiatives. Unfortunately, most of these efforts will fail. This isn’t the first time companies have made this mistake. Back in the late 90s, the big buzz was around the internet. M... (more…)

Important for enterprise machine learning: concurrent heterogeneous models, hybrid cloud, and deep monitoring. Learn one way to build an end-to-end system. (more…)

For engineers looking to draw insights from AI, it's best to remember the idiom, 'Garbage in, garbage out.' Experienced AI jockeys can spend as much as 80% of their time optimizing their data before building a machine learning model with it. (more…)