Artificial Intelligence. To most of us that brings up images and short clips from movies where AI dominates Earth and enslaves us poor humans. Put away those connotations for a moment. AI in its purest sense, where programs evolve and self-improve has been very interesting. Google recently showcased an interesting program; they plugged it into a game on the PS4, and in a matter of hours, the program had taught itself to play the game, and a few hours later could play it better than any human. Although this is slightly frightening, it shows how powerful technology is getting.
A newly founded artificial intelligence lab, called Vicarious, wants to build the world’s first, unified artificial intelligence that can match human intelligence. This is not the first time we’ve heard companies or universities trumpet such ambitious goals, but considering who’s backing the project I can only entertain the possibility Vicarious might just do it. Entrepreneurs with great vision and a track record of backing successful companies have all hopped aboard, like Elon Musk (SpaceX, Tesla), Mark Zuckerberg (Facebook), Peter Thiel (Paypal, founder of venture capital and hedge funds worth billions), Jerry Yang (Yahoo! founder), Jeff Bezos (Amazon founder) and more.
Despite decades worth of research, unbelievable computing power and sophisticated algorithms, one of today’s best artificial intelligence can’t score better than a four year old on a standard IQ test.
Researchers from the University of Washington and the Allen Institute for Artificial Intelligence (AI2) have developed a computer software that scored 49% on high-school geometry SAT tests – an average score for a human, but a great one for current AIs.
Facial recognition and motion tracking is already old news. The next level is describing what you do or what’s going on – for now only in still pictures. Meet NeuralTalk, a deep learning image processing algorithm developed by Stanford engineers which uses processes similar to those used by the human brain to decipher and interpret photos. The software can easily describe, for instance, a band of people dressed up as zombies. It’s remarkably effective and freaking creepy at the same time.
Tesla Motors’ Elon Musk has said that our civilization is dangerously close to encountering AI problems within a “five-year timeframe, 10 years at most.” He made the comment on the website Edge.org shortly before deleting it. His point was that, sometime soon, we may actually create a form of artificial intelligence that decides to rise up and wipe out the
This question was prompted to Ray Kurzweil – well known futurologist, pioneer of the Singularity Movement and Director of Engineering at Google – by a member of the audience during a Q&A session at an Executive Program hosted at Singularity University last October. You might not give it much thought now, but the truth is half of all American jobs could be replaced by robots in just a couple of decades. If you’re a teller, supermarket cashier, call center operator or even a famer, you’ll likely lose your job in the coming decades. So, what’s to do then? Should we all rally and ban robots? It’s no easy topic, but at the same time it’s important, I think, not to panic. We need to remember that this isn’t the first time something like this happened. It’s the old human vs automation problem. How many millions of jobs were lost to mass production in the late XIXth century? How many more once computers started permeating society? At the same time, new jobs were made. Just look at where the information industry is today. The major challenge is not if new jobs can be made. This isn’t really problem. The real challenge is to make these available at the right pace and make sure people have the necessary resources to repurpose their skill set. I’ll leave you to Ray.
In his book “Do Androids Dream of Electric Sheep”, one of my favorite writers Philip K. Dick explores what sets apart humans from androids. The theme is more valid today than it ever was, considering the great leaps in artificial intelligence we’re seeing coming off major tech labs around the world, like Google’s. Take for instance how the company employs advanced artificial neural networks to zap through a gazillion images, interpret them and return the right one you’re looking for when you make a query using the search engine. Though nothing like a human brain, the networks uses 10-30 stacked layers of artificial neurons with each layer doing its job in incremental order to come to an “answer” by the final output layer is finished. While not dead-on, the network seems to return results better than anything we’ve seen before and as a by-product, it can also “dream.” These artificial dreams output some fascinating images to say the least, going from virtually nothing (white noise) to something’s that out of a surrealist painting. Who says computers can’t be creative?
Don’t you just hate it when you’re looking for support for a service or app you bought, only to be greeted by some monosyllabic robot ? Ok, that can happen just as well when dealing with outsourced tech support, but at least you know you’re talking to a real person. Well, that might change sooner than you might think. The singularity is getting closer by the moment. Just take a look at Google’s new chatbot which according to the developers has moderate “natural language understanding”. In other words, it can roll with the punches and continue the conversation by itself without following predefined question – answer. Of course, after a while you can still tell it’s not human (fails Turing test), but that doesn’t mean it isn’t entertaining. Have a look at how it answers to “what’s the purpose of life?”.
Using a novel deep learning algorithm, a team at UC Berkeley demonstrated a robot that learns on the fly and performs various tasks that weren’t pre-programmed. It starts off shy and clumsy, but eventually gets the ahead of it. For instance, after it stomped a bit around its environment, when given a new task, but with no further instructions, the robot learned by itself to assemble LEGO bricks or twist caps onto pill bottles.
Even the best chess players are no match for computers these days, but computers are still struggling when it comes to games that have a random or unknown component. In games like Bridge or Poker, humans still hold the crown. Scientists from the Carnegie Mellon University tried to change that, by designing Claudico – a computer program built to defeat humans. But Claudico lost, badly.
About two dozen University of Texas students gathered on Saturday at the entrance to the SXSW tech and entertainment festival to voice their concerns about the risks artificial intelligence might pose to humanity. Though largely ignored by hipster pedestrians nearby, the protest does raise some legitimate concerns even though technology is still far off from any Skynet scenario. Thankfully, we might never cross this SciFi threshold.
We’ve come to understand that human players will never stand a chance against a computer with enough fire power at finite and open games like checkers or chess. Poker is sensibly different because the computer doesn’t know his human opponent’s hands. No matter, a group of computer scientists from the University of Alberta in Canada have programmed an AI to
Needless to say, the human brain is the most complex neural structure encountered so far. While a computer can outwork a human in many cognitive tasks, our brain can perform a variety of tasks that no computing machine can even scratch the surface. Just think a bit about imagination – how could a computer ever come as close as generating
As years pass, computers start beating us in more and more fields: math is out of the question, chess, and even jeopardy; but in crossword puzzles, man still beats computer – and easily. In a contest held in New York this weekend, a program designed to work crossword puzzles, came in 141st among 600 human puzzle solvers. Matthew Ginsberg, who
Researchers from the CalTech University have managed to create the first artificial neural network from DNA, a circuit built out of interactinig molecules that can recall memories based on an incomplete pattern, in pretty much the same way a brain works. “Although brainlike behaviors within artificial biochemical systems have been hypothesized for decades,” says Lulu Qian, a Caltech senior postdoctoral
The Japanese seem to have not lost one inch of the determination to push science forward after the major earthquake, the tsunamis it generated, and the colateral damage that comes with such a tragic event (power shortages, infrastructure damage, and most of all, radiation danger from nuclear plants). They are now trying to trim the costs of space rockets by