Wondering what we these numbers are? These stats depict the active users, of the above mentioned social media platforms, globally. This basically means that almost everyone is active on some or the other social media platform at a given point of time. Social Media is giving voice to the general mass. People discuss issues, debate, opine and review.

You already know that machine learning is essentially a form of data analytics, but where did it come from and how has it evolved to become what it is today? In the past couple of decades, we have seen a rapid expansion and evolution of information technology. In 1995, data storage cost around 1000/GB; by 2014 that cost had plummeted to 0.03/GB . With access to larger and larger data sets, data scientists have made major advances in neural networks, which have led to better accuracy in modeling and analytics. As we mentioned earlier, the combination of data and analytics opens up unique opportunities for businesses.

During the christmas vacation of 2015, I got a motivational boost again and decided try out Kaggle. So I spent quite some time experimenting with various algorithms for their Homesite Quote Conversion, Otto Group Product Classification and Bike Sharing Demand contests. The main takeaway from this was the experience of iteratively improving the results by experimenting with the algorithms and the data. I learned to trust my logic when doing machine learning. If tweaking a parameter or engineering a new feature seems like a good idea logically, it's quite likely that it actually will help.

Some 40 years ago, a long-running series of iconic TV commercials featured the E.F. Typically in a crowded setting like a party or on an airplane, someone would mention that his broker was E.F. Suddenly there was dead silence; no one moved a muscle. Hutton talks, people listen," the announcer intoned. When it comes to computer science, we tend to pay particularly close attention to those we regard as experts and visionaries in the field.

A company can spend all the funds it wants on the latest cybersecurity technology, like firewalls, threat detection, artificial intelligence and machine learning tools, but there is one security risk that can't blocked from entering the company networks: the employee. Whether they're being coerced into doing do it or not an employee could actively be working with hackers and cybercriminals to let them inside in your network. But in many cases it's a lax or ill-informed attitude to cybersecurity by staff which is potentially putting organisations at risk, with employees falling victim to phishing one of the major reasons that data breaches occur. "The human operating system is a challenge in itself, we know human beings are the weakest link" says Philipp Amann, head of strategy at Europol's European Cybercrime Centre (EC3). And the problem is only going to become trickier to solve because people are becoming more connected than ever, offering hackers additional opportunities to find that one weakness that allows them access.

If'big data' was the phrase du-jour in 2015, I propose that in 2016 it will be'artificial intelligence' – or'AI' if you're really cool. AI combines all the efficiency and futuristic promise of robotics and takes them to the next level, where they are able to seem more like super human beings than toys leftover from the 1960's. Be careful, though, before you make assumptions about what AI really offers to an organization. It doesn't have to lead to something as extreme as having a CEO-script running the company. In fact, AI might actually present an opportunity to bring more people into an organization rather than less.

Artificial intelligence is making a lot of promises for even the near future. We already have access to digital assistants like Microsoft's Cortana and Apple's Siri. It has already made great improvements in the healthcare industry. AI can even compose music, dream, and beat us at complex games like Go. All of these advancements are incredible, but why did they start appearing recently, and how far will we be able to push AI? Modern AI has been a thought since the first digital computer was created around the 1940s.

But most people seem far more interested in what you can tell them about the future. The agricultural and industrial revolutions were about changing the world outside us. This century will be about changing the world inside us – making new entities with new kinds of brains. We are quickly acquiring powers that were always thought to be divine. I grew up in a small industrial suburb of Haifa, in Israel.

THE descent into a post-truth world continues at a depressing rate. The latest winner of the pants-on-fire award is former US presidential candidate Newt Gingrich. In an interview with CNN after a speech in which Donald Trump wrongly claimed that violent crime was rising, Gingrich cherry-picked the facts – then abandoned them altogether. "The average American does not think crime is down," he said. "As a political candidate, I'll go with what people feel."

Apache PredictionIO (incubating) is an open source Machine Learning Server built on top of state-of-the-art open source stack for developers and data scientists create predictive engines for any machine learning task. Apache PredictionIO (incubating) can be installed as a full machine learning stack, bundled with Apache Spark, MLlib, HBase, Spray and Elasticsearch, which simplifies and accelerates scalable machine learning infrastructure management. A summary of the changes in each release before migrating to Apache Software Foundation are on GitHub here. Apache PredictionIO (incubating) is licensed under the Apache License, Version 2.0. See LICENSE for the full license text.