What if computers could learn from their mistakes? Not long ago, this question would seem like nothing but far off Sci-Fi. Even currently, almost everyone would just scratch their heads and say it has to be a few years away, at the most. After all, there is something about learning that seems to necessitate, deep down, a kind of realistic and organic intelligence – almost something soul-like.
Recently, the New York Times published an article detailing how brain-like computers will be available for commercial use starting this year. 2014. These new computer processors, instead of being based on the binary algorithms that have underscored computing for its entire history, will now have processor systems modeled on the neural connections found in the human brain.
Although designers say that this new type of processor makes a thinking and self-aware computer still years away, it does open the door to future computer chips that become consistently more efficient as their computational mode changes based upon the types of calculations it does most often – just as how neural pathways in the brain change and adapt to the activities the brain does most often. This change in processing allows computers to work both smarter and faster, while being more energy efficient. It also opens the door to computers and robots that can learn to survive in the real world.
Programmers can, hypothetically, now rely on the computer’s self learning to successfully navigate the real world and acquire speech recognition better than they would normally through just pre-programming. As of now, these new chips will work in tandem with older binary chips. Eventually, though, future robots and computers could rely solely on self-learning chips, leading to ever smarter and more efficient machines.
Although A.I. systems are still years and years away, would machines that could learn alter our relationship with technology? At what point would we almost consider robots or machines to be ‘alive’ if they could actively learn in the future? Just think of how much emotional attachment people already have for their smart phones.
Image courtesy of Hammacher.