Machine learning (ML) is empowering average business users with superior, automated tools to apply their domain knowledge to predictive analytics or customer profiling. The article What is Automated Machine Learning (AutoML)? These are not just empty promises to worldwide business leaders; in 2017, the age of automated, ML-powered analytics and BI dawned, and has since transformed one industry sector at a time. The automation revolution has not paused and is likely to storm global businesses in years to come. The era of AutoML is beginning to enable business users to tune existing data models and apply custom models to their everyday business situations as well.

ServiceNow survey results shed light on the state of machine learning in business. Earlier this month ServiceNow released the results of a survey it ran to better understand the state of machine learning in businesses today. The survey questioned 500 CIOs across 11 countries and 25 industries, providing a broad brush on the opinions of machine learning (ML). Let's take a look at some of the more interesting findings from the survey. For the report, ServiceNow cut the data into an isolated a group it called "first movers," which are the 10% that were ahead of their industry peers in spending on machine learning.

PAU: In the ML space, it's very important to focus on niche apps and solutions. If somebody aims at a very broad application and a very broad set of solutions, it's probably going to fail. If entrepreneurs focus on solving a particular problem with a particular algorithm, they are more likely to succeed. A narrowed variability of results. There are 12-15 algorithms availalbe to use. Very difficult to chose - for solving what?

The event took place on Thursday, September 22nd, 2016. We asked startup vendors and representatives from the organization team about these trends. Kevin Kelly was right when he predicted that the business plans of the next 10,000 startups were easy to forecast: »take X and add AI«. Computers that see and listen, think and predict are already making a difference across industries. Artificial intelligence can automate processes, reduce costs and improve customer experience. Corporations need to leverage those machine learning technologies or risk being replaced by'smarter disruptors.' [Tomasz Rudolf, CEO D-RAFT] For sure, we now have the technology (measured in computer power and algorithms) that is able to achieve great progress every year. But the most important difference is that AI started to finance itself. A great recent example is about using DeepMind's work on reinforcement learning to reduce Google's Data Center cooling bill by 40%. The biggest difference is unsupervised learning and the availability of "cheap" GPU power. That's why we see so many startups rising in the field of AI. I believe this is the main reason that we are entering the machine learning era.