EMA Blog: Business Intelligence and IT Management

OpenManage Enterprise is a big deal, but underrated: OpenManage Enterprise is the new infrastructure automation platform that could unlock the private and hybrid cloud for Dell. Deploying Dell infrastructure through a simple YAML file is within reach.

Companies who manage to put AI capabilities into the hands of each and every business employee will be vastly successful in the marketplace. Enabling business employees to back up their decisions with data will dramatically increase staff productivity. At the same time, employees will feel empowered by their new ability to make much more informed decisions and automating certain tasks, based on intelligence derived from operations and market data that is now available to them.

Everyone wants to talk about how analytics is the future of network engineering and operations. The phrase “network analytics” is used by vendors of various stripes to imply that a particular technology is smarter and better than the average solution.

Why Machine Learning Diagnoses Cancer but Can’t Run our Hybrid Cloud

Neural Networks Are Key in 2018

Neural networks are back, but please don’t think they are able to emulate the context awareness of the human brain. Don’t get me wrong, I believe that the neural network approach is a viable one, but we do need to be clear about its limitations. All of these limitations are rooted in the limited 'worldview' the neural network is able to take in. This worldview is limited as it relies on a human being with limited time and knowledge creating the neural network topology by providing the following components and enough sample data for the machine to determine how input should be processed.

My constant search for the next ‘cool’ tech toy or app is inspired by my obsession for automation. Trying to teach my 4 and 6 year old kids to think of creative solutions for their repetitive problems (no, there’s not yet a robot that cleans their rooms) surfaced the following 3 top toys and top apps in 2017.

In 2017, CEOs arrived at the conclusion that machine learning and artificial intelligence (ML / AI) will be critical to unlock competitive advantages in the future. However, most enterprises had very little understanding of exactly what is possible today and how much value the investment in various ML / AI technologies can bring. Here are my six key recommendations for 2018:

Now that I’ve predicted that in 2018 machine learning will be available to ‘average Joe developer,’ let me share my experience from this weekend. Note that I’m not trying to be a ‘cool geek’ by doing some hands on work (I’m way too old to still be cool), but based on all the machine learning and artificial intelligence buzz in 2017, I thought my use case should be quick, simple, and most importantly solving a problem that could otherwise not be solved.

For readers who would like to see what happened to our 2017 predictions, please take a look. Jens Soeldner and the EMA Team sat down again this month to look into the crystal ball for 2018.

“We want everyday developers (...) to be able to use machine learning much more extensively.” This is Andy Jassy’s mantra targeted at making AWS the company that turns machine learning into a commodity, similar to what the company achieved for IaaS before. Within this context, the following two new offerings stood out of the glut of machine learning and IoT news at Re:Invent 2017.