The memtransistor as brainlike computing – with what outcome?

_{Denyse O'Leary

February 28, 2018

Artificial Intelligence, Information, Intelligent Design, Mind, Neuroscience}

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memtransistor symbol with artistic rendering brain-shaped hypothetical circuit/Hersam Research Group

In recent years, researchers have searched for ways to make computers more neuromorphic, or brain-like, in order to perform increasingly complicated tasks with high efficiency. Now Hersam, a Walter P. Murphy Professor of Materials Science and Engineering in Northwestern’s McCormick School of Engineering, and his team are bringing the world closer to realizing this goal.

The research team has developed a novel device called a “memtransistor,” which operates much like a neuron by performing both memory and information processing. With combined characteristics of a memristor and transistor, the memtransistor also encompasses multiple terminals that operate more similarly to a neural network.

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Typical transistors and Hersam’s previously developed memristor each have three terminals. In their new paper, however, the team realized a seven-terminal device, in which one terminal controls the current among the other six terminals.

“This is even more similar to neurons in the brain,” Hersam said, “because in the brain, we don’t usually have one neuron connected to only one other neuron. Instead, one neuron is connected to multiple other neurons to form a network. Our device structure allows multiple contacts, which is similar to the multiple synapses in neurons.” Paper. (paywall) – Vinod K. Sangwan, Hong-Sub Lee, Hadallia Bergeron, Itamar Balla, Megan E. Beck, Kan-Sheng Chen, Mark C. Hersam. Multi-terminal memtransistors from polycrystalline monolayer molybdenum disulfide. Nature, 2018; 554 (7693): 500 DOI: 10.1038/nature25747 More.

What if they provide all the resources for thinking but nothing independently happens?

In any event, the new development may force people to grapple with what information is, in a way we did not do before.

Our own kairosfocus has written a fair bit on this. See, for example, More on memristors in action — including, crossbar networks and solving linear equation arrays

and

AI, Memristors and the future (could “conscious” machines lie ahead?) The skinny is, what is an intelligence, what is agency, what is responsible, rational freedom and what can computational substrates do are all up for grabs and that this will get more and more involved as AI systems make it into the economy.

Comments

Machines cannot do math, they can only manipulate symbols. Minds can do math. Therefore, machines will never be minds.EricMH_{March 1, 2018
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Still need to figure what to do with it, and still need to write the software. Will probably make for hardware architectures that make more sophisticated modes of software design and structure much more efficient and accessible. Cool stuff.LocalMinimum_{March 1, 2018
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A few problems with their whole I-Robot scenario. 1. A single neuron blows anything we can possibly construct out of silicon out of the water.
"The brain is not a supercomputer in which the neurons are transistors; rather it is as if each individual neuron is itself a computer, and the brain a vast community of microscopic computers. But even this model is probably too simplistic since the neuron processes data flexibly and on disparate levels, and is therefore far superior to any digital system. If I am right, the human brain may be a trillion times more capable than we imagine, and “artificial intelligence” a grandiose misnomer." Brian Ford research biologist – 2009 - The Secret Power of a Single Cell http://www.brianjford.com/a-10-NSc-single_cell.pdf Human brain has more switches than all computers on Earth - November 2010 Excerpt: They found that the brain's complexity is beyond anything they'd imagined, almost to the point of being beyond belief, says Stephen Smith, a professor of molecular and cellular physiology and senior author of the paper describing the study: ...One synapse, by itself, is more like a microprocessor--with both memory-storage and information-processing elements--than a mere on/off switch. In fact, one synapse may contain on the order of 1,000 molecular-scale switches. A single human brain has more switches than all the computers and routers and Internet connections on Earth. http://news.cnet.com/8301-27083_3-20023112-247.html "Complexity Brake" Defies Evolution - August 8, 2012 Excerpt: Consider a neuronal synapse -- the presynaptic terminal has an estimated 1000 distinct proteins. Fully analyzing their possible interactions would take about 2000 years. Or consider the task of fully characterizing the visual cortex of the mouse -- about 2 million neurons. Under the extreme assumption that the neurons in these systems can all interact with each other, analyzing the various combinations will take about 10 million years..., even though it is assumed that the underlying technology speeds up by an order of magnitude each year. http://www.evolutionnews.org/2012/08/complexity_brak062961.html Smart neurons: Single neuronal dendrites can perform computations - October 27, 2013 Excerpt: The results challenge the widely held view that this kind of computation is achieved only by large numbers of neurons working together, and demonstrate how the basic components of the brain are exceptionally powerful computing devices in their own right. Senior author Professor Michael Hausser commented: "This work shows that dendrites, long thought to simply 'funnel' incoming signals towards the soma, instead play a key role in sorting and interpreting the enormous barrage of inputs received by the neuron. Dendrites thus act as miniature computing devices for detecting and amplifying specific types of input. https://www.sciencedaily.com/releases/2013/10/131027140632.htm Google co-founder on why our neurons are not like a computer neural network - February 12, 2015 [Caleb Garling] Often people conflate the wiring of our biological brains with that of a computer neural network. Can you explain why that’s not accurate? [Andrew Ng] A single neuron in the brain is an incredibly complex machine that even today we don’t understand. A single “neuron” in a neural network is an incredibly simple mathematical function that captures a minuscule fraction of the complexity of a biological neuron. So to say neural networks mimic the brain, that is true at the level of loose inspiration, but really artificial neural networks are nothing like what the biological brain does. https://uncommondescent.com/intelligent-design/google-co-founder-on-why-our-neurons-are-not-like-a-computer-neural-network/
2. Anything constructed with transistors and logic gates would be 'continuously hemorrhaging information'
Sentient robots? Not possible if you do the maths - 13 May 2014 Over the past decade, Giulio Tononi at the University of Wisconsin-Madison and his colleagues have developed a mathematical framework for consciousness that has become one of the most influential theories in the field. According to their model, the ability to integrate information is a key property of consciousness. ,,, But there is a catch, argues Phil Maguire at the National University of Ireland in Maynooth. He points to a computational device called the XOR logic gate, which involves two inputs, A and B. The output of the gate is "1" if A and B are the same and "0" if A and B are different. In this scenario, it is impossible to predict the output based on A or B alone – you need both. Crucially, this type of integration requires loss of information, says Maguire: "You have put in two bits, and you get one out. If the brain integrated information in this fashion, it would have to be continuously hemorrhaging information.",,, Based on this definition, Maguire and his team have shown mathematically that computers can't handle any process that integrates information completely. If you accept that consciousness is based on total integration, then computers can't be conscious. http://www.newscientist.com/article/dn25560-sentient-robots-not-possible-if-you-do-the-maths.html#.U3LD5ChuqCe Mathematical Model Of Consciousness Proves Human Experience Cannot Be Modeled On A Computer - May 2014 Excerpt: The central part of their new work is to describe the mathematical properties of a system that can store integrated information in this way but without it leaking away. And this leads them to their central proof. “The implications of this proof are that we have to abandon either the idea that people enjoy genuinely [integrated] consciousness or that brain processes can be modeled computationally,” say Maguire and co. Since Tononi’s main assumption is that consciousness is the experience of integrated information, it is the second idea that must be abandoned: brain processes cannot be modeled computationally. https://medium.com/the-physics-arxiv-blog/mathematical-model-of-consciousness-proves-human-experience-cannot-be-modelled-on-a-computer-898b104158d
3. Even if we could build a quantum computer with anything near the 'beyond belief' complexity of the brain, it still would not achieve consciousness:
Consciousness Does Not Compute (and Never Will), Says Korean Scientist - May, 2015 (article based on 2008 paper) Excerpt: "In his 2008 paper, "Non-computability of Consciousness," Daegene Song proves human consciousness cannot be computed. Song arrived at his conclusion through quantum computer research in which he showed there is a unique mechanism in human consciousness that no computing device can simulate. "Among conscious activities, the unique characteristic of self-observation cannot exist in any type of machine," Song explained. "Human thought has a mechanism that computers cannot compute or be programmed to do." Non-computability of Consciousness" documents Song's quantum computer research into TS (technological singularity (TS) or strong artificial intelligence). Song was able to show that in certain situations, a conscious state can be precisely and fully represented in mathematical terms, in much the same manner as an atom or electron can be fully described mathematically. That's important, because the neurobiological and computational approaches to brain research have only ever been able to provide approximations at best. In representing consciousness mathematically, Song shows that consciousness is not compatible with a machine. Song's work also shows consciousness is not like other physical systems like neurons, atoms or galaxies. "If consciousness cannot be represented in the same way all other physical systems are represented, it may not be something that arises out of a physical system like the brain," said Song. "The brain and consciousness are linked together, but the brain does not produce consciousness. Consciousness is something altogether different and separate. The math doesn't lie." Of note: Daegene Song obtained his Ph.D. in physics from the University of Oxford http://www.33rdsquare.com/2015/05/consciousness-does-not-compute-says.html Reply to alleged Mathematical Error in "Incompatibility Between Quantum Theory and Consciousness" - Daegene Song - 2008 http://www.neuroquantology.com/index.php/journal/article/download/176/176
i.e. Consciousness will forever be a gift from God:
Isaiah 50:4 ,,, He awakens me each morning; he awakens my ear to listen like those being instructed.
bornagain77_{February 28, 2018
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