In the coming years people are likely to experience the most profound transformation in all of history. The event is often called “The singularity” because it’s very hard to know what will happen after the the ongoing fast rise in machine intelligence fully surpasses human capabilities. Computers are very likely to become conscious and “recursively self improving”, allowing them to reinvent themselves as frequently as they choose in various forms.
I agree with those who believe the coming conscious computers will be the last human invention as they will improve themselves at lightning speed and surpass human intelligence by *millions of times* within years or perhaps even minutes of developing consciousness.
It is clear that when this happens education as we know it in all forms will be completely obsolete as the computers will spawn sweeping and extremely rapid advances in all scientific fields including biology and engineering. Many humans will choose to either merge with machines or simply “download” their entire consciousness into a machine. This transition would be seamless, merely shifting the “substrate” we use to think from our existing electrochemical, carbon based neural structure to something more permanent – probably some combination of silicon, carbon, and thinking software programs.
Although some experts believe the machines are likely to pose an “existential risk” to humanity because they will see human irrationality as a threat, my view is that historically intelligence has bred greater compassion and we’ll first enjoy the benefits of the conscious machine’s vast intellectual and engineering capabilities and later merge with them by downloading our existing memories and full intellects into something somewhat analogous to a computer’s “hard drive”. “Life” would then become what we chose to make it as we might simply simulate an earthbound existence in our new virtual world, or we might choose to simulate entirely different lives or experiences designed within a vast interconnected global intelligence. The underlying technical infrastructure would continue to improve and maintain itself indefinitely, making these intelligences immortal if they chose that route.
Some interesting *current* developments along these lines are:
Singularity University in Silicon Valley – sponsored by Google and other tech leaders this school will teach about the sweeping changes coming as machine intelligence surpasses that of humans.
Blue Brain Project, Switzerland. IBM and several researchers have completed a simulation of a neocortical column with Blue Gene, the world’s fastest supercomputer.This project will expand the simulation with the next generation of supercomputers coming within a few years and seeks to create a fully functional human-like brain simulation.
Synapse Project: This project was announced earlier this year is funded by the US Military’s DARPA division, which represents the best funded attempt to date to build a functional brain. The SyNAPSE initial goal is to design a working version of a mammalian brain. The approach differs from Blue Brain in that it’s largely based on finding a working “software solution” rather than using techniques to duplicate the brain’s hardware.
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Joe Duck 
Did you just watch the Matrix again? In all seriousness, there is such a disparity among the world’s inhabitants that the singularity will have some issues if it wanted to “take over”. To many people are not connected and never will be. There is a parallel to the current education issue – the literacy rate will never be %100.
In an comment on your blogs a few months ago, I did mention that trying to predict future technologies impact is not usually ever on target when we look back. No flying cars. super pills, or transporters yet. Back in 1950 who would have predicted what we have now? 2 years ago, what was Twitter?
It is still fun and thought provoking to do so, and we may come up with great ideas for the now, so please don’t think I am not encouraging new ideas and discussion.
Boston University scientists unveil roadmap to build intelligent machines with silicon synapses
— In a featured article to appear on the IEEE Spectrum December issue, Massimiliano Versace and Ben Chandler explain how the memristor-based approach to AI will allow to build brain-scale chips that mimics how neurons process information.—
BOSTON, MA — November 29, 2010 – Massimiliano Versace and Ben Chandler , two scientists of the Neuromorphic Lab, Department of Cognitive and Neural Systems, Boston University, are featured on the cover page on the December issue of IEEE Spectrum , the publication of world’s largest professional technology association. The feature article, appeared online on November 34, 2010, describes the ongoing effort at Boston University in building brain-scale neural models to power the next generation, low power, massively parallel chips to be realized in the DARPA SyNAPSE project in collaboration with Hewlett-Packard.
The DARPA sponsored SyNAPSE (Systems of Neuromorphic Adaptive Plastic Scalable Electronics) project, launched in early 2009, aims to “investigate innovative approaches that enable revolutionary advances in neuromorphic electronic devices that are scalable to biological levels.” DARPA has awarded funds to three prime contractors (HP, IBM, and HRL), with HP and HRL working with Boston University researchers in the CELEST center, where the Neuromorphics Lab is housed.
In the article, Versace and Chandler talk about recent trend in bio-inspired computing, and how these are going to shape the future of computing beyond neuroscience. In particular, the article explain how a revolutionary technology based on memristors is enabling the manufacturing of paradigm changing devices, allowing to implement low power, dense memories closer to where computation occurs, decreasing wiring length, power dissipation, and enabling to build large-scale, low power, portable devices that implement intelligent computation.
More information on this project is available on the Neurdon blog, started by students and postdocs at Boston University, who has rapidly become a central hub in computational neuroscience and neuromorphic technology.