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AI will upload and access our memories, predicts Siri co-inventor

Tuesday, 9 May 2017 by System Administrator

Canstockphoto4570804

AI will upload and access our memories, predicts Siri co-inventor

"Instead of asking how smart we can make our machines, let's ask how smart our machines can make us."

April 26, 2017

 “Hey Siri, what’s the name of that person I met yesterday?” (credit: Apple Inc.)

Instead of replacing humans with robots, artificial intelligence should be used more for augmenting human memory and other human weaknesses, Apple Inc. executive Tom Gruber suggested at the TED 2017 conference yesterday (April 25, 2017).

Thanks to the internet and our smartphones, much of our  personal data is already being captured, notes Gruber, who was one the inventors of voice-controlled intelligent-assistant Siri. Future AI memory enhancement could be especially life-changing for those with Alzheimer’s or dementia, he suggested.

Limitless

“Superintelligence should give us super-human abilities,” he said. “As machines get smarter, so do we. Artificial intelligence can enable partnerships where each human on the team is doing what they do best. Instead of asking how smart we can make our machines, let’s ask how smart our machines can make us.

“I can’t say when or what form factors are involved, but I think it is inevitable,” he said. “What if you could have a memory that was as good as computer memory and is about your life? What if you could remember every person you ever met? How to pronounce their name? Their family details? Their favorite sports? The last conversation you had with them?”

Gruber’s ideas mesh with a prediction by Ray Kurzweil: “Once we have achieved complete models of human intelligence, machines will be capable of combining the flexible, subtle human levels of pattern recognition with the natural advantages of machine intelligence, in speed, memory capacity, and, most importantly, the ability to quickly share knowledge and skills.”

Two projects announced last week aim in that direction: Facebook’s plan to develop a non-invasive brain-computer interface that will let you type at 100 words per minute and Elon Musks’ proposal that we become superhuman cyborgs to deal with superintelligent AI.

But trusting machines also raises security concerns, Gruber warned. “We get to choose what is and is not recalled,” he said. “It’s absolutely essential that this be kept very secure.”

 

 

Ultra-low-power artificial synapse for neural-network computing

Saturday, 25 March 2017 by System Administrator

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An ultra-low-power artificial synapse for neural-network computing

Brain-like device with 500 states instead of binary could one day communicate with live neurons, merging computers with the brain

February 24, 2017

(Left) Illustration of a synapse in the brain connecting two neurons. (Right) Schematic of artificial synapse (ENODe), which functions as a transistor. It consists of two thin, flexible polymer films (black) with source, drain, and gate terminals, connected by an electrolyte of salty water that permits ions to cross. A voltage pulse applied to the “presynaptic” layer (top) alters the level of oxidation in the “postsynaptic layer” (bottom), triggering current flow between source and drain. (credit: Thomas Splettstoesser/CC and Yoeri van de Burgt et al./Nature Materials)

Stanford University and Sandia National Laboratories researchers have developed an organic artificial synapse based on a new memristor (resistive memory device) design that mimics the way synapses in the brain learn. The new artificial synapse could lead to computers that better recreate the way the human brain processes information. It could also one day directly interface with the human brain.

The new artificial synapse is an electrochemical neuromorphic organic device (dubbed “ENODe”) — a mixed ionic/electronic design that is fundamentally different from existing and other proposed resistive memory devices, which are limited by noise, required high write voltage, and other factors*, the researchers note in a paper published online Feb. 20 in Nature Materials.

Like a neural path in a brain being reinforced through learning, the artificial synapse is programmed by discharging and recharging it repeatedly. Through this training, the researchers have been able to predict within 1 percent of uncertainly what voltage will be required to get the synapse to a specific electrical state and, once there, remain at that state.

“The working mechanism of ENODes is reminiscent of that of natural synapses, where neurotransmitters diffuse through the cleft, inducing depolarization due to ion penetration in the postsynaptic neuron,” the researchers explain in the paper. “In contrast, other memristive devices switch by melting materials at relatively high temperatures (PCMs) or by voltage-induced breakdown/filament formation and ion diffusion in dense oxide layers (FFMOs).”

The ENODe achieves significant energy savings** in two ways:

  • Unlike a conventional computer, where you save your work to the hard drive before you turn it off, the artificial synapse can recall its programming without any additional actions or parts. Traditional computing requires separately processing information and then storing it into memory. Here, the processing creates the memory.
  • When we learn, electrical signals are sent between neurons in our brain. The most energy is needed the first time a synapse is traversed. Every time afterward, the connection requires less energy. This is how synapses efficiently facilitate both learning something new and remembering what we’ve learned. The artificial synapse, unlike most other versions of brain-like computing, also fulfills these two tasks simultaneously, and does so with substantial energy savings.

“More and more, the kinds of tasks that we expect our computing devices to do require computing that mimics the brain because using traditional computing to perform these tasks is becoming really power hungry,” said A. Alec Talin, distinguished member of technical staff at Sandia National Laboratories in Livermore, California, and co-senior author of the paper. “We’ve demonstrated a device that’s ideal for running these type of algorithms and that consumes a lot less power.”

A future brain-like computer with 500 states

Only one artificial synapse has been produced so far, but researchers at Sandia used 15,000 measurements to simulate how an array of them would work in a neural network. They tested the simulated network’s ability to recognize handwriting of digits 0 through 9. Tested on three datasets, the simulated array was able to identify the handwritten digits with an accuracy between 93 to 97 percent.

This artificial synapse may one day be part of a brain-like computer, which could be especially useful for processing visual and auditory signals, as in voice-controlled interfaces and driverless cars, but without energy-consuming computer hardware.

This device is also well suited for the kind of signal identification and classification that traditional computers struggle to perform. Whereas digital transistors can be in only two states, such as 0 and 1, the researchers successfully programmed 500 states in the artificial synapse, which is useful for neuron-type computation models. In switching from one state to another they used about one-tenth as much energy as a state-of-the-art computing system needs to move data from the processing unit to the memory.

However, this is still about 10,000 times as much energy as the minimum a biological synapse needs in order to fire**. The researchers hope to attain neuron-level energy efficiency once they test the artificial synapse in smaller devices.

Linking to live organic neurons

This new artificial synapse may one day be part of a brain-like computer, which could be especially beneficial for computing that works with visual and auditory signals. Examples of this are seen in voice-controlled interfaces and driverless cars. Past efforts in this field have produced high-performance neural networks supported by artificially intelligent algorithms but these depend on energy-consuming traditional computer hardware.

Every part of the device is made of inexpensive organic materials. These aren’t found in nature but they are largely composed of hydrogen and carbon and are compatible with the brain’s chemistry. Cells have been grown on these materials and they have even been used to make artificial pumps for neural transmitters. The switching voltages applied to train the artificial synapse (about 0.5 mV) are also the same as those that move through human neurons — about 1,000 times lower than the “write” voltage for a typical memristor.

That means it’s possible that the artificial synapse could communicate with live neurons, leading to improved brain-machine interfaces. The softness and flexibility of the device also lends itself to being used in biological environments.

This research was funded by the National Science Foundation, the Keck Faculty Scholar Funds, the Neurofab at Stanford, the Stanford Graduate Fellowship, Sandia’s Laboratory-Directed Research and Development Program, the U.S. Department of Energy, the Holland Scholarship, the University of Groningen Scholarship for Excellent Students, the Hendrik Muller National Fund, the Schuurman Schimmel-van Outeren Foundation, the Foundation of Renswoude (The Hague and Delft), the Marco Polo Fund, the Instituto Nacional de Ciência e Tecnologia/Instituto Nacional de Eletrônica Orgânica in Brazil, the Fundação de Amparo à Pesquisa do Estado de São Paulo and the Brazilian National Council.

* “A resistive memory device has not yet been demonstrated with adequate electrical characteristics to fully realize the efficiency and performance gains of a neural architecture. State-of-the-art memristors suffer from excessive write noise, write non-linearities, and high write voltages and currents.  Reducing the noise and lowering the switching voltage significantly below 0.3 V (~10 kT) in a two-terminal device without compromising long-term data retention has proven difficult.” … Organic memristive devices have been recently proposed, but are limited by “the slow kinetics of ion diffusion through a polymer to retain their states or on charge storage in metal nanoparticles, which inherently limits performance and stability.” — Yoeri van de Burgt et al., Nature Materials

** ENODe switches at low voltage and energy (< 10 pJ for 1000-square-micrometer devices), compared to an estimated 1–100 fJ per synaptic event for the human brain.

 


Abstract of A non-volatile organic electrochemical device as a low-voltage artificial synapse for neuromorphic computing

The brain is capable of massively parallel information processing while consuming only ~1–100 fJ per synaptic event. Inspired by the efficiency of the brain, CMOS-based neural architectures and memristors are being developed for pattern recognition and machine learning. However, the volatility, design complexity and high supply voltages for CMOS architectures, and the stochastic and energy-costly switching of memristors complicate the path to achieve the interconnectivity, information density, and energy efficiency of the brain using either approach. Here we describe an electrochemical neuromorphic organic device (ENODe) operating with a fundamentally different mechanism from existing memristors. ENODe switches at low voltage and energy (<10 pJ for 103 μm2 devices), displays >500 distinct, non-volatile conductance states within a ~1 V range, and achieves high classification accuracy when implemented in neural network simulations. Plastic ENODes are also fabricated on flexible substrates enabling the integration of neuromorphic functionality in stretchable electronic systems. Mechanical flexibility makes ENODes compatible with three-dimensional architectures, opening a path towards extreme interconnectivity comparable to the human brain.

References:

Related:

Topics: Cognitive Science/Neuroscience | Computers/Infotech/UI

 

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Groundbreaking technology rewarms large-scale animal tissues preserved at low temperatures

A major step toward long-term preservation of organs and tissues for transplantation; could lead to saving millions of human lives

March 2, 2017

Inductive radio-frequency heating of magnetic nanoparticles embedded in tissue (red material in container) preserved at very low temperatures restored the tissue without damage (credit: Navid Manuchehrabadi et al./Science Translational Medicine)

A research team led by the University of Minnesota has discovered a way to rewarm large-scale animal heart valves and blood vessels preserved at very low (cryogenic) temperatures without damaging the tissue. The discovery could one day lead to saving millions of human lives by creating cryogenic tissue and organ banks of organs and tissues for transplantation.

The research was published March 1 in an open-access paper in Science Translational Medicine.

Long-term preservation methods like vitrification cool biological samples to an ice-free glassy state, using very low temperatures between -160 and -196 degrees Celsius, but tissues larger than 1 milliliter (0.03 fluid ounce) often suffer major damage during the rewarming process, making them unusable for tissues.

In the new research, the researchers were able to restore 50 milliliters (1.7 fluid ounces) of tissue with warming at more than 130°C/minute without damage.

Radiofrequency inductive heating of iron nanoparticles

To achieve that, they developed a revolutionary new method using silica-coated iron-oxide nanoparticles dispersed throughout a cryoprotectant solution around the tissue. The nanoparticles act as tiny heaters around the tissue when they are activated using noninvasive radiofrequency inductive energy, rapidly and uniformly warming the tissue.

 

This transmission electron microscopy (TEM) image shows the iron oxide nanoparticles (coated in mesoporous silica) that are used in the tissue warming process. (credit: Haynes research group/University of Minnesota)

The results showed that none of the tissues displayed signs of harm — unlike control samples using vitrification and rewarmed slowly over ice or using convection warming. The researchers were also able to successfully wash away the iron oxide nanoparticles from the sample following the warming.

“This is the first time that anyone has been able to scale up to a larger biological system and demonstrate successful, fast, and uniform warming of hundreds of degrees Celsius per minute of preserved tissue without damaging the tissue,” said University of Minnesota mechanical engineering and biomedical engineering professor John Bischof, the senior author of the study.

Organs next

Bischof said there is a strong possibility they could scale up to even larger systems, like organs. The researchers plan to start with rodent organs (such as rat and rabbit) and then scale up to pig organs and then, hopefully, human organs. The technology might also be applied beyond cryogenics, including delivering lethal pulses of heat to cancer cells.

The researchers’ goal is to eliminate transplant waiting lists. Currently, hearts and lungs donated for transplantation must be discarded because these tissues cannot be kept on ice for longer than a matter of hours, according to the researchers.*

It will be interesting to see if the technology can one day be extended to cryonics.

The research was funded by the National Science Foundation (NSF), National Institutes of Health (NIH), U.S. Army Medical Research and Materiel Command, Minnesota Futures Grant from the University of Minnesota, and the University of Minnesota Carl and Janet Kuhrmeyer Chair in Mechanical Engineering. Researchers at Carnegie Mellon University, Clemson University and Tissue Testing Technologies LLC were also involved in the study.

* “A major limitation of transplantation is the ischemic injury that tissue and organs sustain during the time between recovery from the donor and implantation in the recipient. The maximum tolerable organ preservation for transplantation by hypothermic storage is typically 4 hours for heart and lungs; 8 to 12 hours for liver, intestine, and pancreas; and up to 36 hours for kidney transplants. In many cases, such limits actually prevent viable tissue or organs from reaching recipients. For instance, more than 60% of donor hearts and lungs are not used or transplanted partly because their maximum hypothermic preservation times have been exceeded. Further, if only half of these discarded organs were transplanted, then it has been estimated that wait lists for these organs could be extinguished within 2 to 3 years.” — Navid Manuchehrabadi et al./Science Translational Medicine


Abstract of Improved tissue cryopreservation using inductive heating of magnetic nanoparticles

Vitrification, a kinetic process of liquid solidification into glass, poses many potential benefits for tissue cryopreservation including indefinite storage, banking, and facilitation of tissue matching for transplantation. To date, however, successful rewarming of tissues vitrified in VS55, a cryoprotectant solution, can only be achieved by convective warming of small volumes on the order of 1 ml. Successful rewarming requires both uniform and fast rates to reduce thermal mechanical stress and cracks, and to prevent rewarming phase crystallization. We present a scalable nanowarming technology for 1- to 80-ml samples using radiofrequency-excited mesoporous silica–coated iron oxide nanoparticles in VS55. Advanced imaging including sweep imaging with Fourier transform and microcomputed tomography was used to verify loading and unloading of VS55 and nanoparticles and successful vitrification of porcine arteries. Nanowarming was then used to demonstrate uniform and rapid rewarming at >130°C/min in both physical (1 to 80 ml) and biological systems including human dermal fibroblast cells, porcine arteries and porcine aortic heart valve leaflet tissues (1 to 50 ml). Nanowarming yielded viability that matched control and/or exceeded gold standard convective warming in 1- to 50-ml systems, and improved viability compared to slow-warmed (crystallized) samples. Last, biomechanical testing displayed no significant biomechanical property changes in blood vessel length or elastic modulus after nanowarming compared to untreated fresh control porcine arteries. In aggregate, these results demonstrate new physical and biological evidence that nanowarming can improve the outcome of vitrified cryogenic storage of tissues in larger sample volumes.

References:

Topics: Biomed/Longevity | Electronics | Nanotech/Materials Science

 

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