Serving more than a billion people a day, Facebook has its work cut out for it when providing customized news feeds. That is where the social network giant takes advantage of deep learning to serve up the most relevant news to its vast user base.

Making a career change is never easy, but few things are more motivating than the prospect of a good salary and a dearth of competition. That's a fair summary of the data science world today, as at least one well-publicized study has made clear, so why not investigate a little further?

Data scientists use statistical analysis tools to find non-obvious patterns in deep data. But they know the universe is full of spurious correlations. Big data simply intensifies the problem.

When Alan Turing and his colleagues cracked the Nazi Enigma codes during World War II, the impact on Britain's war-planning was minimal. The reason little changed is because Britain's armed forces simply didn't know how to take advantage of the abundance of data they now had.

Next the company plans to take on WebP with its neural network approach

Small is beautiful, as the old saying goes, and nowhere is that more true than in media files. Compressed images are considerably easier to transmit and store than uncompressed ones are, and now Google is using neural networks to beat JPEG at the compression game.

In years past, Business intelligence (BI) was something only big blue chip companies could enjoy. Mainly because employing analytics software was expensive, and it required building data centres and hiring IT specialists, who are also expensive. BI systems have, over time, become less expensive and have become a useful way of gathering corporate data and correlating that data in a way that will produce useful observations to the business.

As the 2016 Rio Olympics remains fresh in my mind, I’m reminded of the Olympic motto “Citius, Altius, Fortius” (faster, higher, stronger). Since their inception in 1896, the goal of the modern Olympics has been to provide an international forum where the world’s elite athletes could come together and compete.

“A data scientist does model-driven analyses of our data; analyses to improve our planning, increase our productivity, and develop our deeper levels of subject matter expertise. A data scientist works at the tactical, operational, and strategic levels, sharing insights with the business.”