Lifeboat Foundation

Creative Machines; however, are they truly without a built in bias due to their own creator/s?

Despite nature’s bewildering complexity, the driving force behind it is incredibly simple. ‘Survival of the fittest’ is an uncomplicated but brutally effective optimization strategy that has allowed life to solve complex problems, like vision and flight, and colonize the harshest of environments.

Continue reading “Evolution’s Brutally Simple Rules Can Make Machines More Creative” »

Quantum computing might be closer than we thought, thanks to a series of newly developed scientific methods. Furthermore, a new implementation of Shor’s algorithm increases the urgency of getting Bitcoin ready for the advent of quantum computing.

Also read: NIST Starts Developing Quantum-Resistant Cryptography Standards.

Read this introductory list of contemporary machine learning algorithms of importance that every engineer should understand.

By James Le, New Story Charity.

Continue reading “The 10 Algorithms Machine Learning Engineers Need to Know” »

It is not often that a scientist walks the red carpet at a Silicon Valley party and has Morgan Freeman award them millions of dollars while Alicia Keys performs on stage and other A-listers rub shoulders with NASA astronauts.

But the guest list for the Breakthrough prize ceremony is intended to make it an occasion. At the fifth such event in California last night, a handful of the world’s top researchers left their labs behind for the limelight. Honoured for their work on black holes and string theory, DNA repair and rare diseases, and unfathomable modifications to Schrödinger’s equation, they went home to newly recharged bank accounts.

Founded by Yuri Milner, the billionaire tech investor, with Facebook’s Mark Zuckerberg and Google’s Sergey Brin, the Breakthrough prizes aim to right a perceived wrong: that scientists and engineers are not appreciated by society. With lucrative prizes and a lavish party dubbed “the Oscars of science”, Milner and his companions want to elevate scientists to rock star status.

Continue reading “Breakthrough prize awards $25m to researchers at ‘Oscars of science’” »

The goal of roboticists has long been to make A.I. as efficient as the human brain, and researchers at the Massachusetts Institute of Technology just brought them one step closer.

In a recent paper, published in the journal Biology, scientists were able to successfully train a neural network to recognize faces at different angles by feeding it a set of different orientations for several face templates. Although this only initially gave the neural network the ability to roughly reach invariance — the ability to process data regardless of form — over time, the network taught itself to achieve full “mirror symmetry. Through mathematical algorithms, the neural network was able to mimic the human brain’s ability to understand objects are the same despite orientation or rotation.

Continue reading “A.I. Can Teach Itself to Recognize Faces Now” »

What if a simple algorithm were all it took to program tomorrow’s artificial intelligence to think like humans?

According to a paper published in the journal Frontiers in Systems Neuroscience, it may be that easy — or difficult. Are you a glass-half-full or half-empty kind of person?

Researchers behind the theory presented experimental evidence for the Theory of Connectivity — the theory that all of the brains processes are interconnected (massive oversimplification alert) — “that a simple mathematical logic underlies brain computation.” Simply put, an algorithm could map how the brain processes information. The painfully-long research paper describes groups of similar neurons forming multiple attachments meant to handle basic ideas or information. These groupings form what researchers call “functional connectivity motifs” (FCM), which are responsible for every possible combination of ideas.

Continue reading “Researchers may have uncovered an algorithm that explains intelligence” »

When you see a photo of a dog bounding across the lawn, it’s pretty easy for us humans to imagine how the following moments played out. Well, scientists at MIT have just trained machines to do the same thing, with artificial intelligence software that can take a single image and use it to to create a short video of the seconds that followed. The technology is still bare-bones, but could one day make for smarter self-driving cars that are better prepared for the unexpected, among other applications.

The software uses a deep-learning algorithm that was trained on two million unlabeled videos amounting to a year’s worth of screen time. It actually consists of two separate neural networks that compete with one another. The first has been taught to separate the foreground and the background and to identify the object in the image, which allows the model to then determine what is moving and what isn’t.

Continue reading “MIT’s deep-learning software produces videos of the future” »

The Australian anthropologist explains why being scared about AI and big data has more to do with our fear of each other than killer robots.

We took the technology out of the studio and into a car – making Holoportation truly mobile. To accomplish this, we reduced the bandwidth requirements by 97%, while still maintaining quality. This new mobile Holoportation system greatly increases the potential applications of real-time 3D capture and transmission.