Researchers are working very hard on the ability of computers to mimic the human senses—in their own way, to see, smell, touch, taste and hear. In this article we highlight two examples of algorithms that seem to be beating us at our own game.
Your eyes can be deceiving. Sometimes -even for humans- it is hard to distinguish a muffin from a Chiwawa. Most of us can recognize an object after seeing it once or twice. But the algorithms that power computer vision and voice recognition need thousands of examples to become familiar with each new image or word.
Researchers at Google DeepMind now have a way around this. They made a few clever tweaks to a deep-learning algorithm that allows it to recognize objects in images and other things from a single example—something known as “one-shot learning.” Read More
> Read full A new pair of eyes post
Knowledge grows the more people contribute. Information wants to be free. And Artificial Intelligence needs to be open. Just three one-liners that would make great t-shirts. Fortunately, many people feel the same way. In this article two interesting initiatives that try to democratize A.I.
1. Let’s work out at the Google Gym
Alphabet Inc.’s artificial intelligence division Google DeepMind is making the maze-like game platform it uses for many of its experiments available to other researchers and the general public.
DeepMind is putting the entire source code for its training environment — which it previously called Labyrinth and has now renamed as DeepMind Lab — on the open-source depository GitHub, the company said Monday. Read More
> Read full The future is open post
Three interesting articles on how A.I. shouldn’t be a black box when it comes to scientific value or ethical and moral values.
1. Technology Review writes about how Algorithmic systems have a way of making mistakes or leading to undesired consequences. They offer five principles to help technologists deal with that. Because despite the potential for efficiency gains, algorithms fed by big data can also amplify structural discrimination, produce errors that deny services to individuals, or even seduce an electorate into a false sense of security. Indeed, there is growing awareness that the public should be wary of the societal risks posed by over-reliance on these systems and work to hold them accountable. Read More
> Read full AI with a conscience? post
Computers that create their own secret language. The end of black and white photographs. And an algorithm that knows what will come next in your photo. In this article three new examples of skills that computers have and humans not so much.
1. Esperanto was once invented to help people from different cultures to talk to each other using an easy to learn, politically neutral, language. Recently researchers at Google witnessed the convergence of a similar concept when machines were -together- trying to talk in a new language. Read More
> Read full Amazing discoveries post