The extent to which AI systems have made life easy in possibly every field needs no special mention. Healthcare, defence, transportation, or any sector for that matter – you name it and you know how positive the impact has been. Be it assisting the doctors while surgery is performed, controlling the traffic, assisting you at restaurants, teaching online or even getting done with your daily chores, AI has got you covered. However, a point here to note is that no matter how much AI promises to automate, human involvement cannot be eliminated totally. Simply put, AI has no meaning unless humans are involved.

As impressively capable as AI systems are these days, teaching machines to perform various tasks, whether its translating speech in real time or accurately differentiating between chihuahuas and blueberry muffins. But that process still involves some amount of hand holding and data curation by the humans training them. However the emergence of self supervised learning (SSL) methods, which have already revolutionized natural language processing, could hold the key to imbuing AI with some much needed common sense. Facebook's AI research division (FAIR) has now, for the first time, applied SSL to computer vision training. "We've developed SEER (SElf-supERvised), a new billion-parameter self-supervised computer vision model that can learn from any random group of images on the internet, without the need for careful curation and labeling that goes into most computer vision training today," Facebook AI researchers wrote in a blog post Thursday.

In the last few months, two "predictive" documents found their way into our hands. The first one is the 2016 NMC[1]/CoSN[2] Horizon report for elementary and secondary education and the second is the SURF Trend report 2016: How technological trends enable customised education. Both are very interesting and well-written reports. However they're also a bit tricky in that they're not really underpinned by concrete evidence from the educational sciences and therefore, their predictions are in our opinion a bit like reading tea leaves: They're very visible, but what do they mean? As a preamble to discussing the SURF Trend report 2016 an aside to frame some background. Last year, Paul Kirschner presented a keynote at the 6th International Conference on Learning Analytics and Knowledge (LAK16).