In Part 1 of our blog post series on the possibilities for targeted use of companies’ data, we looked at data science on scale – the huge demand for concepts and the development of valuable data applications and analytics applications, in order to see a positive return on investments in data infrastructure. Now let’s continue...
Machine learning / Deep Learning (as a Service)
Of all the big things this year, artificial intelligence (AI) seems to be the biggest: The machine itself analyzes complex volumes of data based on automated models and learns from the results. This process still continues to amaze and to many it seems like real magic. But with open systems such as Google TensorFlow, Azure ML and others, AI is becoming increasingly mainstream and attracting more and more attention. Even Deep Learning is now pretty much part of wider, everyday language.
2016 will be the year of action! Especially when it comes to Industry 4.0! Learning machines make forecasts or decisions based on data, and enable companies to maximize their potential in any conceivable area. Machine learning experts are able to map all of these possibilities, tools and options on a case-by-case basis to suit specific business proposals and data projects – especially because the whole field is very much a work in progress and is achieving new milestones virtually every week.
One of the promising outlooks in 2016 is custom Machine Learning as a Service: AI logic is optimized for each individual project and can be made available in highly secure cloud environments via defined programming interfaces. This greatly helps companies in separating their first projects and learning outcomes from longer-term activities, such as the building of teams, skills and structures. In order to implement applications and infrastructures, companies certainly don’t need to be experts in Scala, Hadoop, Python, AI, etc. from the very beginning – they can simply go straight in and get started.
To find out how in the very near future we’ll be able to overcome the task of optimally supporting people in interpreting and assessing data and analyses, watch out for Part 3 of Trends in 2016: Human Data Interfaces (HDI).
Here’s something else that may interest you:
Trends in 2016: The next big things in the data world (Part 1)
Listen up! *um is in a podcast about artificial intelligence
Clever machines, simply to use: *um lecture on Machine Learning and APIs