Automatic object recognition in images is currently tricky. Even if a computer has the help of smart algorithms and human assistants, it may not catch everything in a given scene. Google might change that soon, though; it just detailed a new detection systemthat can easily spot lots of objects in a scene, even if they're partly obscured. The key is aneural network that can rapidly refine the criteria it's looking for without requiring a lot of extra computing power. The result is a far deeper scanning system that can both identify more objects and make better guesses -- it can spot tons of items in a living room, including (according to Google's odd example) a flying cat. The technology is still young, but the internet giant sees its recognition breakthrough helping everything fromimage searches through to self-driving cars. Don't be surprised if it gets much easier to look for things online using only vaguest of terms.
Impatience characterizes the technology sector’s approach to education. Disruption is taking place in all other sectors of society — so, why not education? I know too well, whether at Pearson or in the classroom, the challenges and frustration of developing and using digital tools that improve outcomes for students. But I’m optimistic. We are on the verge of a tide of smarter innovation that, if allowed to spread, will turbocharge the learning experience for students. Here are four areas worth watching: 1. Using technology to learn from learners Every great digital product constantly evolves by learning from its users, adding capabilities, and improving its performance. If it’s true for your Facebook feed, then why not education? The potential is there, as the OECD’s recent report on Students, Computers and Learning (OECD) incidentally showed how clickstream and tracking navigation in digital readers can be used to see how students process online text and...
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