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"Technology is evolving us, says Amber Case, as we become a screen-staring, button-clicking new version of homo sapiens. We now rely on "external brains" (cell phones and computers) to communicate, remember, even live out secondary lives. But will these machines ultimately connect or conquer us? Case offers surprising insight into our cyborg selves."

Everyone is a futurist. We all think about the future, imagining and evaluating possibilities, making plans, and implementing strategies for realizing our goals. Educators deliberate the future of education, both where it is heading and where we think it should be heading. I will outline here my vision for a preferable future for education, realistically anchored to certain fundamental features of contemporary affairs and human psychology.

"This symbiotic relationship between human teacher and computer seems to be the next frontier for education. No, cyborgs are not going to take over our classrooms. But in the very near future, teachers and AI computers may team up to provide stronger, better educational experiences for students at every level from primary school up to university."

"You have probably heard a lot about wearables, living services, the Internet of Things, and smart materials by now. Designers are beginning to think about even weirder and wilder things, envisioning a future where evolved technology is embedded inside our digestive tracts, sense organs, blood vessels, and even our cells."

"If we can tap into the same network effects that drive the internet economy and bring it into the firm, we have the potential to build businesses that don't just benefit the bottom line but create a culture of participation and learning. And that's when we'll find that machines are far less adept at delivering the imagination, creativity, genuine insight, and emotional and moral intelligence that is uniquely human."

"In two different tests, the NTM was asked to 1) learn to copy blocks of binary data and 2) learn to remember and sort lists of data. The results were compared with a more basic neural network, and it was found that the computer learned faster and produced longer blocks of data with fewer errors. Additionally, the computer's methods were found to be very similar to the code a human programmer would've written to make the computer complete such a task."