Data is eating the world and there are many indicators of its ubiquitous presence in our lives: AI, digital transformation, data monetization, and the effect of Covid-19 on the accelerated growth of data.

Distributed applications are not new. The first distributed applications were developed over 50 years ago with the arrival of computer networks, such as ARPANET. Since then, developers have leveraged distributed systems to scale out applications and services, including large-scale simulations, web serving, and big data processing. In my own career, which started more than 20 years ago, I have worked on distributed systems in the context of the internet, peer-to-peer networks, big data, and now, machine learning. However, until recently, distributed applications have been the exception, rather than the norm.

Artificial Intelligence Specialist - Artificial Intelligence and Machine Learning have both become synonymous with innovation, and LinkedIn data shows that's more than just buzz. Hiring growth for this role has grown 74% annually in the past 4 years and encompasses a few different titles within the space that all have a very specific set of skills despite being spread across industries, including artificial intelligence and machine learning engineer. According to Indeed, Machine Learning Engineer job openings grew 344% between 2015 to 2018 and have an average base salary of $146,085 according their Best Jobs In The U.S. Study. Robotics Engineer – LinkedIn is seeing a 40% annual increase in demand for technical professionals with robotics expertise today. Robotics is an industry on fire according to LinkedIn's study.