Will AI Ever Be Smarter Than A Four-Year-Old?

Posted by Peter Rudin on 8. March 2019 in News No Comments

The most sophisticated AIs are still far from being able to solve problems that human four-year-olds accomplish with ease. Despite the impressive name, artificial intelligence largely consists of techniques to detect statistical patterns in large data sets. There is much more to human learning. Children are active learners; they don’t just passively soak up data like AIs do.

Four-year-olds can immediately recognize cats and understand words, but they can also make creative and surprising new inferences that go far beyond their experience. Looking at what children do, building curiosity into machines and allowing them to actively interact with the world might be a route to more realistic and wide-range learning to advance AI.

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Are Cyborg Warriors a Good Idea?

Posted by Peter Rudin on 22. February 2019 in News No Comments

Pentagon’s think tank, the Defense Advanced Research Projects Agency, is funding efforts to create technologies that result in “merging minds and machines.” The most dramatic are brain chips, arrays of electrodes that, when implanted in the brain, can receive electrical signals from and send them to neural tissue, aimed at creating neurally “enhanced” soldiers.

In principle, brain chips could boost soldiers’ cognitive and physical functions. Soldiers could control complex weapons systems with their thoughts, communicate telepathically with other soldiers and upload large databases instantly. In principle, minds containing brain chips can also be read and controlled by others.

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Engineers translate brain signals directly into speech

Posted by Peter Rudin on 8. February 2019 in News No Comments

Decades of research has shown that when people speak — or even imagine speaking — telltale patterns of activity appear in their brain. Experts, trying to record and decode these patterns, see a future in which thoughts need not remain hidden inside the brain — but instead could be translated into verbal speech at will.

In a scientific first, neuro-engineers at Columbia University, N.Y. have created a system that translates thought into intelligible, recognizable speech. This breakthrough, which harnesses the power of speech synthesizers and artificial intelligence, could lead to new ways for computers to communicate directly with the brain.

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The Rise of a New Generation of AI Avatars

Posted by Peter Rudin on 25. January 2019 in News No Comments

The intelligence of digital humans comes from the innovative process that uses neural networks to combine biologically inspired models of the human brain and key sensory networks. Together they create a virtual central nervous system called the Human Computing Engine™. The result is an emotionally responsive, artificial human with personality and character that allows machines to talk to humans face-to-face.

Digital DNA™, a new product of Soul Machines, allows to create a completely new digital human in minutes versus the months it previously took.

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Six real AI dangers to watch out for in 2019

Posted by Peter Rudin on 11. January 2019 in News No Comments

Once it was fashionable to fret about the prospect of super-intelligent machines taking over the world. The past year showed that AI may cause all sorts of hazards long before that happens.

The latest AI methods excel at perceptual tasks such as classifying images and transcribing speech, but the hype and excitement over these skills have disguised how far we really are from building machines as clever as we are.

Six controversies from 2018 stand out as warnings that even the smartest AI algorithms can misbehave, or that carelessly applying them can have dire consequences.

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Understanding and Creating Artificial Intelligence

Posted by Peter Rudin on 28. December 2018 in News No Comments

The first glimmers of human-like intelligence appeared a few million years ago on the African continent, and continued to evolve, eventually culminating in the brain of our species Homo sapiens about 100,000 years ago.

In the last few hundred years, our species has made immense intellectual progress in developing a precise understanding of physical reality, by discovering fundamental mathematical laws governing the behavior of space, time, matter and energy.

Despite the remarkable commercial success of current AI systems on supervised pattern recognition tasks, we still have a long way to go in mimicking truly human like intelligence. A major divergence between biological and artificial neural models lies in the very way we model synapses connecting neurons.

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Alibaba’s voice assistant is way better than Google’s

Posted by Peter Rudin on 14. December 2018 in News No Comments

In May this year, Google made quite the splash when it unveiled Duplex, its eerily humanlike voice assistant capable of making restaurant reservations and salon appointments.

In December at the 2018 Neural Information Processing Systems conference, Alibaba demoed the AI customer service agent for its logistics company. It appears that Alibaba’s assistant is more sophisticated than Google Duplex, judging from similar sample calls demoed by Google.

Alibaba’s biggest advantage in this field is the overwhelming wealth of data it has to train its AI. In addition to handling a high volume of customer support calls, Alibaba delivers one billion packages per day.

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The World’s Fastest Brain-Mimicking Computer

Posted by Peter Rudin on 30. November 2018 in News No Comments

Scientists just activated the world’s biggest “brain”: a supercomputer with a million processing cores and 1,200 interconnected circuit boards that together operate like a human brain.

Dubbed Spiking Neural Network Architecture, or SpiNNaker, this neuromorphic system creates models of the neurons in human brains, and it simulates more neurons in real time than any other conventional computer can.

In the human brain, 100 billion neurons fire and transmit signals to thousands of destinations. SpiNNaker’s architecture supports an exceptional level of communication among its processors, behaving much like a brain’s neural network does.

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Can AI Create True Art?

Posted by Peter Rudin on 16. November 2018 in News No Comments

This portrait of Edmond Belamy sold for $432,500 nearly 45 times its high estimate — as Christie’s becomes the first auction house to offer a work of art created by an algorithm.

‘The algorithm is composed of two parts,’ says Caselles-Dupré of Obvious, the company that created the algorithm. ‘On one side is the Generator, on the other the Discriminator. We fed the system with a data set of 15,000 portraits painted between the 14th century to the 20th. The Generator makes a new image based on the set, then the Discriminator tries to spot the difference between a human-made image and one created by the Generator. The aim is to fool the Discriminator into thinking that the new image is a real-life portrait.’

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Top Lawyers Beaten by AI

Posted by Peter Rudin on 2. November 2018 in News No Comments

In a landmark study, 20 top US corporate lawyers with decades of experience in corporate law and contract review were pitted against an AI system. Their task was to spot issues in five Non-Disclosure Agreements (NDAs), which are a contractual basis for most business deals.

In this study AI achieved an average 94% accuracy rate, higher than the lawyers who achieved an average rate of 85%.

However, surprisingly, for these defeated lawyers, there was almost no talk of the “rise of the machines” nor fear of AI taking their jobs. Most of the lawyers agreed that high-volume and low-risk contracts took up too much of their time, and felt it was incumbent to automate work.

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