All posts filed under: Artificial Intelligence, Science, Technology

Articles relating to cognitive science, neurobiology, Artificial Intelligence and related fields

The Dark Secret at the Heart of AI

No one really knows how the most advanced algorithms do what they do. That could be a problem. by Will Knight April 11, 2017 Last year, a strange self-driving car was released onto the quiet roads of Monmouth County, New Jersey. The experimental vehicle, developed by researchers at the chip maker Nvidia, didn’t look different from other autonomous cars, but it was unlike anything demonstrated by Google, Tesla, or General Motors, and it showed the rising power of artificial intelligence. The car didn’t follow a single instruction provided by an engineer or programmer. Instead, it relied entirely on an algorithm that had taught itself to drive by watching a human do it. Getting a car to drive this way was an impressive feat. But it’s also a bit unsettling, since it isn’t completely clear how the car makes its decisions. Information from the vehicle’s sensors goes straight into a huge network of artificial neurons that process the data and then deliver the commands required to operate the steering wheel, the brakes, and other systems. The result …

Why our brains may be 100 times more powerful than believed

The dendrites in our brain have been underestimated for 60 years says a new study (Credit:vitstudio/Depositphotos) A new study out of the University of California Los Angeles (UCLA) has found that one part of the neurons in our brains is more active than previously revealed. The finding implies that our brains are both analog and digital computers and could lead to better ways to treat neurological disorders. The focus of the study was the dendrites, long branch-like structures that attach to a roundish body called the soma to form neurons. It was previously believed that dendrites were nothing more than conduits that sent spikes of electrical activity generated in the soma to other neurons. But the study has shown that the dendrites themselves are highly active, sending spikes of their own at a rate 10 times that previously believed. The finding runs counter to the long-held belief that somatic spikes were the main way we learn and form memories and perceptions. “Dendrites make up more than 90 percent of neural tissue,” said UCLA neurophysicist Mayank …

Electronic synapses that can learn: First step towards an artificial brain?

Artist’s impression of the electronic synapse: the particles represent electrons circulating through oxide, by analogy with neurotransmitters in biological synapses. The flow of electrons depends on the oxide’s ferroelectric domain structure, which is controlled by electric voltage pulses. Credit: © Sören Boyn / CNRS/Thales physics joint research unit. Researchers from the CNRS, Thales, and the Universities of Bordeaux, Paris-Sud, and Evry have created an artificial synapse capable of learning autonomously. They were also able to model the device, which is essential for developing more complex circuits. The research was published in Nature Communications on 3 April 2017. One of the goals of biomimetics is to take inspiration from the functioning of the brain in order to design increasingly intelligent machines. This principle is already at work in information technology, in the form of the algorithms used for completing certain tasks, such as image recognition; this, for instance, is what Facebook uses to identify photos. However, the procedure consumes a lot of energy. Vincent Garcia (Unité mixte de physique CNRS/Thales) and his colleagues have just taken a …

The future of AI is neuromorphic. Meet the scientists building digital ‘brains’ for your phone

Neuromorphic chips are being designed to specifically mimic the human brain – and they could soon replace CPUs AI services like Apple’s Siri and others operate by sending your queries to faraway data centers, which send back responses. The reason they rely on cloud-based computing is that today’s electronics don’t come with enough computing power to run the processing-heavy algorithms needed for machine learning. The typical CPUs most smartphones use could never handle a system like Siri on the device. But Dr. Chris Eliasmith, a theoretical neuroscientist and co-CEO of Canadian AI startup Applied Brain Research, is confident that a new type of chip is about to change that. “Many have suggested Moore’s law is ending and that means we won’t get ‘more compute’ cheaper using the same methods,” Eliasmith says. He’s betting on the proliferation of ‘neuromorphics’ — a type of computer chip that is not yet widely known but already being developed by several major chip makers. Traditional CPUs process instructions based on “clocked time” – information is transmitted at regular intervals, as …

Artificial Synapse Developed for Neural Networks

For all the improvements in computer technology over the years, we still struggle to recreate the low-energy, elegant processing of the human brain. Now, researchers at Stanford University and Sandia National Laboratories have made an advance that could help computers mimic one piece of the brain’s efficient design — an artificial version of the space over which neurons communicate, called a synapse. “It works like a real synapse but it’s an organic electronic device that can be engineered,” said Alberto Salleo, associate professor of materials science and engineering at Stanford and senior author of the paper. “It’s an entirely new family of devices because this type of architecture has not been shown before. For many key metrics, it also performs better than anything that’s been done before with inorganics.” The new artificial synapse, reported in the Feb. 20 issue of Nature Materials, mimics the way synapses in the brain learn through the signals that cross them. This is a significant energy savings over traditional computing, which involves separately processing information and then storing it into …

Researchers uncover algorithm which may solve human intelligence

By Charlie Osborne for Between the Lines | November 29, 2016 If we have the algorithm, we also have the key to true artificial intelligence. The key element which separates today’s artificial intelligence (AI) systems and what we consider to be human thought and learning processes could be boiled down to no more than an algorithm. That’s according to a recent paper published in the journal Frontiers in Systems Neuroscience, which suggests that despite the complexity of the human brain, an algorithm may be all it takes for our technological creations to mimic our way of thinking. As reported by Business Insider, the idea that human thought can be whittled down to an algorithm lies in the “Theory of Connectivity,” which proposes that human intelligence is rooted in “a power-of-two-based permutation logic (N = 2i-1)” algorithm, capable of producing perceptions, memories, generalized knowledge and flexible actions, according to the paper. First proposed in 2015, the theory suggests that how we acquire and process knowledge can be explained by how different neurons interact and align in …

Can Quantum Physics Explain Consciousness?

Written by JENNIFER OUELLETTE  NOV 7, 2016  The Atlantic A new approach to a once-farfetched theory is making it plausible that the brain functions like a quantum computer. The mere mention of “quantum consciousness” makes most physicists cringe, as the phrase seems to evoke the vague, insipid musings of a New Age guru. But if a new hypothesis proves to be correct, quantum effects might indeed play some role in human cognition. Matthew Fisher, a physicist at the University of California, Santa Barbara, raised eyebrows late last year when he published a paper in Annals of Physics proposing that the nuclear spins of phosphorus atoms could serve as rudimentary “qubits” in the brain—which would essentially enable the brain to function like a quantum computer. As recently as 10 years ago, Fisher’s hypothesis would have been dismissed by many as nonsense. Physicists have been burned by this sort of thing before, most notably in 1989, when Roger Penrose proposed that mysterious protein structures called “microtubules” played a role in human consciousness by exploiting quantum effects. Few researchers believe …

The Map of the Human Brain Is Finally Getting More Useful

                  The new human brain map has 180 regions on both the left and right halves. By Ryan Cross July 20, 2016 Human Connectome Project neuroscientists have created a program to make individualized brain maps.  The human brain is a little bit less of a mystery today, thanks to new maps from neuroscientists at Washington University Medical School. Not only did they identify more brain regions than previous maps, they also made a machine-learning program to re-create a new map for any brain, which will help scientists and doctors study individual differences in brain structure and disease, and will hopefully lead to new ways to diagnose brain disorders. The new map of the brain’s outermost crinkled layer, called the cerebral cortex, was published in Nature today. David Van Essen, the lead mapmaker, calls it a landmark study for the Human Connectome Project, which he heads. Researcher Matthew Glasser says that unlike many previous studies, this map considers several features of the brain simultaneously to mark its boundaries. Some neuroscientists …

The mind isn’t locked in the brain but extends far beyond it

The author of this piece is Keith Frankish , an English philosopher and writer. He is a visiting research fellow with the Open University in the UK and an adjunct professor with the Brain and Mind Programme at the University of Crete. He lives in Greece. Where is your mind? Where does your thinking occur? Where are your beliefs? René Descartes thought that the mind was an immaterial soul, housed in the pineal gland near the centre of the brain. Nowadays, by contrast, we tend to identify the mind with the brain. We know that mental processes depend on brain processes, and that different brain regions are responsible for different functions. However, we still agree with Descartes on one thing: we still think of the mind as (in a phrase coined by the philosopher of mind Andy Clark)brainbound, locked away in the head, communicating with the body and wider world but separate from them. And this might be quite wrong. I’m not suggesting that the mind is non-physical or doubting that the brain is central to it; but it …

Mind transfer is the future of the post-mortal human

Mortality has long been a thorn in the eye of human, tormenting the mind for centuries. Cold, gripping realization that death is inevitable and the speculation of afterlife has always been an object of obsession for many. Through its many forms, death is a literal end of the road, end of a journey long started. What if that road could continue, if that journey was ongoing? If there was a way to achieve proverbial life after death, transcending universe and material existence? [NOTE: This is precisely the issue that forms the basis for my 5-star science fiction novel, Mindclone. See at this link: https://www.amazon.com/Mindclone-youre-brain-without-called-ebook/dp/B00BJWOHDE ] Brain uploading With the rapid technological advancement, the desire to upload the contents of human brains into a machine grows with each passing day. There is a strong belief that this would allow anyone to live forever. Inside a machine entity, they’d form super AI. Every once in awhile, some neuroscientist reveals his or her project on brain mapping and other various similar themes. The trend is catching on and it slowly …

Smart Dust Is Coming: New Camera Is the Size of a Grain of Salt

BY JASON DORRIER ON JUN 28, 2016 The array of doublet lenses pictured here were printed directly onto a CMOS image sensor. Image credit: Timo Gissibl/University of Stuttgart Miniaturization is one of the most world-shaking trends of the last several decades. Computer chips now have features measured in billionths of a meter. Sensors that once weighed kilograms fit inside your smartphone. But it doesn’t end there. Researchers are aiming to take sensors smaller—much smaller. In a new University of Stuttgart paper published in Nature Photonics, scientists describe tiny 3D printed lenses and show how they can take super sharp images. Each lens is 120 millionths of a meter in diameter—roughly the size of a grain of table salt—and because they’re 3D printed in one piece, complexity is no barrier. Any lens configuration that can be designed on a computer can be printed and used. This allows for a variety of designs to be tested to achieve the finest quality images. According to the paper, the new method not only demonstrates high-quality micro-lenses can be 3D printed, but it also solves roadblocks to current …

Artificial synapse said to rival biological synapses in energy consumption and function

This article is lifted from the KurzweilAI site. Link: http://www.kurzweilai.net/artificial-synapse-said-to-rival-biological-synapses-in-energy-consumption-and-function Schematic of biological neuronal network and an organic nanowire (ONW) synaptic transistor (ST) that emulates a biological synapse. The yellow conductive lines and probe (A′) mimic an axon (A) that delivers presynaptic spikes from a pre-neuron to the presynaptic membrane. The mobile ions in the ion gel move in the electrical field, analogous to the biological neuron transmitters in the synaptic cleft; the field later induces an excitatory postsynaptic current (EPSC, light blue line) in the biological dendrite (B). An ONW (B′) combined with a drain electrode (yellow surface) mimics a biological dendrite (B). EPSC (light green line) is generated in the ONW in response to presynaptic spikes and is delivered to a post-neuron through connections to the drain electrode. (credit: Wentao Xu et al./Science Advances) A human synapse consumes an extremely small amount of energy (~10 fJ or femtojoules** per synaptic event). The researchers have fabricated an organic nanofiber (ONF), or organic nanowire (ONW), electronic device that emulates the important working principles and energy consumption …

Brain Scanning Just Got Very Good

Written By Megan Scudellari, Posted 21 Jun 2016 Seven years ago, the U.S. National Institutes of Health (NIH) decided to map all the connections in the brain. In 2010, the Human Connectome Project(HCP) was born. It has provided funding to the tune of $40 million to two collaborating consortia whose aim was to acquire and share high-resolution data of structural and functional connections in the human brain. The researchers have sought to understand, on a scale never before attempted, the neural pathways that make us human, and how changes in those pathways make us sick. At a symposium yesterday at the NIH campus in Bethesda, Maryland, top researchers from the HCP came together to provide an update on the project’s achievements and future directions. To date, the consortia have released brain-scanning data from hundreds of individuals and that data has been used in more than 140 scientific publications. Perhaps even more importantly, the effort has produced impressive new tech, including unprecedented magnetic resonance (MR) hardware. Among the gadgets are high-powered scanners and customized head coils. In addition, there are legions of software for …

This 5-Fingered Robot Hand Learns to Get a Grip on its Own

This five-fingered robot hand developed by University of Washington computer science and engineering researchers can learn how to perform dexterous manipulation — like spinning a tube full of coffee beans — on its own, rather than having humans program its actions.  Credit: University of Washington Robots today can perform space missions, solve a Rubik’s cube, sort hospital medication and even make pancakes. But most can’t manage the simple act of grasping a pencil and spinning it around to get a solid grip. Intricate tasks that require dexterous in-hand manipulation — rolling, pivoting, bending, sensing friction and other things humans do effortlessly with our hands — have proved notoriously difficult for robots. Now, a University of Washington team of computer science and engineering researchers has built a robot hand that can not only perform dexterous manipulation but also learn from its own experience without needing humans to direct it. Their latest results are detailed in a paper to be presented May 17 at the IEEE International Conference on Robotics and Automation. “Hand manipulation is one of …