<h2>ARTIFICIAL SYNAPSES AND NEURONS</h2>
Our quest to build a computer that mimics our brain took another important step. Researchers have used a single memristor — a resistor capable of &#8220;remembering&#8221; the flow of electrical currents — to build efficient electronic devices that partly imitate our brain&#8217;s neurons and synapses, according to a <a href="http://www.nature.com/nmat/journal/vaop/ncurrent/full/nmat4756.html" target="_blank">new study in Nature Materials</a>.
The devices emulate how calcium ions diffuse through junctions between neurons known as synapses — a process that is far from fully understood. And the memristors can store information when electricity is no longer flowing, unlike circuits found in present day microcontrollers, microprocessors, and static RAM. They also &#8220;forget&#8221; information over time, much like a real neuron.
<figure id="attachment_54423" style="width: 454px" class="wp-caption aligncenter"><img class="wp-image-54423 size-full" src="https://wp-assets.futurism.com/2016/10/pic1.jpg" alt="Nature Materials" width="454" height="351" /><figcaption class="wp-caption-text">Nature Materials</figcaption></figure>
The model neurons could help develop better computing and shed light on the mysteries of the brain, said lead research Joshua Yang of the University of Massachusetts.
&#8220;These could allow us to make more bio-realistic artificial synapses with higher fidelity that could help neurobiologists better understand — and replicate — how real synapses work,” Yang told NanoTechWeb.org.
<h2>MORE THAN 1s AND 0s</h2>
Normally, computers only switch between two states: 1s and 0s. These 1s and 0s make up the code and processes that allow social networks or search engines like Google to exist.
Although our brain isn&#8217;t as efficient as computers at rapidly calculating complex math, the &#8220;circuitry&#8221; of our brain can easily zero in on a particular image out of a thousand. Our brain is also much more energy efficient than traditional computers.
That&#8217;s why computers that successfully imitate the human brain could handle massive data sets or even help unlock the secrets of artificial intelligence or consciousness itself. And the researchers plan to use the technology for large scale computing.
&#8220;We will then be able to engineer the devices, optimize them and integrate them into large scale arrays for different applications,” Yang said.
Yang&#8217;s team isn&#8217;t the first to imitate neurons. In early August, we reported on <a href="https://futurism.com/ibm-creates-crystalline-artificial-neurons-to-help-computers-mimic-our-brains/" target="_blank">IBM&#8217;s artificial neurons</a>.

Hard Science

Scientists have used resistors that "remember" electrical currents to create artificial synapses and neurons.
The technology could let computers handle larger data sets more efficiently and unlock the secrets of our brain.

Scientists Just Made Tech That Mimics the Brain’s Building Blocks

They used a resistor that "remembers" electrical currents.

<h2>Cognitive Computing</h2>
Even after all the developments in computers, the human brain remains by far, the most complex, sophisticated, and powerful computer in existence. And for decades, scientists have been looking for ways to translate its processing mechanisms into a system that machines can replicate.
IBM is one of the most avid proponents of cognitive computing, with their <a href="http://www.research.ibm.com/cognitive-computing/watson/index.shtml#fbid=fd6sG5-wPxo">artificial intelligence</a> program, Watson, being the first cognitive system ever created. In 2011, <a href="https://www.youtube.com/watch?v=WFR3lOm_xhE">Watson debuted</a> on the television show, Jeopardy!. Despite not being connected to the internet, Watson won the quiz show against two human opponents, taking home a $1-million prize.
“Cognitive computing refers to systems that learn at scale, reason with purpose and interact with humans naturally. Rather than being explicitly programmed, they learn and reason from their interactions with us and from their experiences with their environment,” IBM wrote in <a href="http://www.research.ibm.com/software/IBMResearch/multimedia/Computing_Cognition_WhitePaper.pdf">their whitepaper</a>.
<h2>Closer to Brain Power</h2>
Last year, IBM pulled off a <a href="http://www.techtimes.com/articles/77610/20150818/ibm-creates-neuromorphic-chip-powerful-rodents-brain.htm">48-million connection network</a>—around the same computing power as a rat’s brain, with their system TrueNorth. Earlier this year, they were able to fit 3 bits per cell in <a href="https://futurism.com/ibm-achieves-breakthrough-in-memory-storage-50-times-faster-than-flash/">phase change memory</a> (PCM). Now, they are taking another big step forward in the quest to recreate the human brain’s cognitive computing power.
“The breakthrough marks a significant step forward in the development of energy-efficient, ultra-dense integrated neuromorphic technologies for applications in cognitive computing,” the <a href="http://phys.org/news/2016-08-ibm-scientists-imitate-functionality-neurons.html">scientists said</a>.
IBM scientists in Zurich designed artificial neurons using phase-change materials, including germanium antimony telluride. These materials exhibit two states, amorphous and crystalline, and are the same materials that made optical disk storage possible.
<figure id="attachment_46892" style="width: 771px" class="wp-caption alignright"><a href="https://wp-assets.futurism.com/2016/08/Capture.jpg"><img class="size-full wp-image-46892" src="https://wp-assets.futurism.com/2016/08/Capture.jpg" alt="IBM" width="771" height="435" /></a><figcaption class="wp-caption-text">IBM</figcaption></figure>
These phase-change-based artificial neurons can perform complex computations and fast learning while using very little energy, much like the human brain. The artificial neurons effectively fired in response to electrical pulses that made it crystallize, a property known in neuroscience as <a href="http://www.stat.columbia.edu/~liam/teaching/neurostat-fall15/papers/Jolivet04-JNP.pdf">integrate-and-fire</a>. This is the property which allows animals to react accordingly to stimuli, such as when you touch a hot surface.
These artificial neurons survived being subjected to billions of switching cycles, which would translate to multiple years of operation at an update frequency of 100Hz. Each neuron update required less than five picojoules and the average power less than 120 microwatts.
“This will significantly reduce the area and power consumption as it will be using tiny nanoscale devices that act as neurons,” says IBM scientist and author <a href="http://www.wired.co.uk/article/cientists-mimicking-human-brain-computation">Abu Sebastian</a>. “Populations of stochastic phase-change neurons, combined with other nanoscale computational elements such as artificial synapses, could be a key enabler for the creation of a new generation of extremely dense neuromorphic computing systems,” adds research co-author Tomas Tuma.

Scientists at IBM achieve another breakthrough by recreation of artificial neurons that successfully respond to phase changes due to electric signals while using very little power, much like the human brain.

/Artificial Neurons

Hard Science

Scientists Just Made Tech That Mimics the Brain’s Building Blocks

Hard Science

IBM Just Made Artificial Neurons to Help Computers Mimic Our Brains

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