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Category: computing – Page 265

This is leading to even better brain engineering 👏 🙌 👌 😀 😄.

Computer-augmented brains, cures to blindness, and rebuilding the brain after injury all sound like science fiction. Today, these disruptive technologies aren’t just for Netflix, “Terminator,” and comic book fodder — in recent years, these advances are closer to reality than some might realize, and they have the ability to revolutionize neurological care.

Neurologic disease is now the world’s leading cause of disability, and upwards of 11 million people have some form of permanent neurological problem from traumatic brain injuries and stroke. For example, if a traumatic brain injury has damaged the motor cortex — the region of the brain involved in voluntary movements — patients could become paralyzed, without hope of regaining full function. Or some stroke patients can suffer from aphasia, the inability to speak or understand language, due to damage to the brain regions that control speech and language comprehension.

Thanks to recent advances, sometimes lasting neurologic disease can be prevented. For example, if a stroke patient is seen quickly enough, life-threatening or-altering damage can be avoided, but it’s not always possible. Current treatments to most neurologic disease are fairly limited, as most therapies, including medications, aim to improve symptoms but can’t completely recover lost brain function.

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We often believe computers are more efficient than humans. After all, computers can complete a complex math equation in a moment and can also recall the name of that one actor we keep forgetting. However, human brains can process complicated layers of information quickly, accurately, and with almost no energy input: recognizing a face after only seeing it once or instantly knowing the difference between a mountain and the ocean. These simple human tasks require enormous processing and energy input from computers, and even then, with varying degrees of accuracy.

Creating brain-like computers with minimal energy requirements would revolutionize nearly every aspect of modern life. Funded by the Department of Energy, Quantum Materials for Energy Efficient Neuromorphic Computing (Q-MEEN-C) — a nationwide consortium led by the University of California San Diego — has been at the forefront of this research.

UC San Diego Assistant Professor of Physics Alex Frañó is co-director of Q-MEEN-C and thinks of the center’s work in phases. In the first phase, he worked closely with President Emeritus of University of California and Professor of Physics Robert Dynes, as well as Rutgers Professor of Engineering Shriram Ramanathan. Together, their teams were successful in finding ways to create or mimic the properties of a single brain element (such as a neuron or synapse) in a quantum material.

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Most of today’s EVs use lithium-ion batteries, the same kind you’ll find in your smartphone or laptop. These batteries all have two electrodes (one positive and one negative), and the negative one is usually made of graphite.

While the battery is being charged, the lithium ions flow from the side of the battery with the positive electrode to the side with the negative electrode. If the charging happens too fast, the flow can be disrupted, causing the battery to short circuit.

StoreDot’s EV battery replaces the graphite electrode with one made from nanoparticles based on the chemical element germanium — this allows the ions to flow more smoothly and quickly, enabling a faster charge.

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Advance lays the groundwork for miniature devices for spectroscopy, communications, and quantum computing. Researchers have created chip-based photonic resonators that operate in the ultraviolet (UV) and visible regions of the spectrum and exhibit a record low UV light loss. The new resonators lay the groundwork for increasing the size, complexity, and fidelity of UV photonic integrated circuit (PIC) design, which could enable new miniature chip-based devices for applications such as spectroscopic sensing, underwater communication, and quantum information processing.

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Founded in 2021, Virginia-based Procyon Photonics is a startup aiming to change the future of computing hardware with its focus on optical computing. What makes the company unique is that their entire team consists of current high school students, and its co-founder, CEO, and CTO, Sathvik Redrouthu, holds the distinction of being the world’s youngest CEO in the photonic and optical computing sector.

Optical computing represents an innovative leap from traditional computing, which relies on electrons moving through wires and transistors. Instead, this relatively nascent field seeks to harness photons — particles of light — as the fundamental elements in computational processes. The promise of optical computing is compelling enough that industry giants like IBM and Microsoft, among others, are heavily investing in its research and development.

Procyon is attempting to differentiate itself in this competitive landscape not just by its youth, but with their technology. The team is pioneering a unique, industry-leading optical chip, and has published a conference paper detailing how a specialized form of matrix algebra could be executed on an optoelectronic chip.

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In a press release, Bujack, who creates scientific visualizations at Los Alamos National Laboratory, called the current mathematical models used for color perceptions incorrect and requiring a “paradigm shift.”

A surprise finding

Being able to accurately model human color perception has a tremendous impact on automating image processing, computer graphics, and visualization. Bujack’s team first set out to develop algorithms that would automatically enhance color maps used in data visualization to make it easier to read them.

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Femtotech: Computing at the femtometer scale using quarks and gluons.
How the properties of quarks and gluons can be used (in principle) to perform computation at the femtometer (10^−15 meter) scale.

I’ve been thinking on and off for two decades about the possibility of a femtotech. Now that nanotech is well established, and well funded, I feel that the time is right to start thinking about the possibility of a femtotech.

You may ask, “What about picotech?” — technology at the picometer (10-12m) scale. The simple answer to this question is that nature provides nothing at the picometer scale. An atom is about 10–10 m in size.

The next smallest thing in nature is the nucleus, which is about 100,000 times smaller, i.e., 10–15 m in size — a femtometer, or “fermi.” A nucleus is composed of protons and neutrons (i.e., “nucleons”), which we now know are composed of 3 quarks, which are bound (“glued”) together by massless (photon-like) particles called “gluons.”

Hence if one wanted to start thinking about a possible femtotech, one would probably need to start looking at how quarks and gluons behave, and see if these behaviors might be manipulated in such a way as to create a technology, i.e., computation and engineering (building stuff).

In this essay, I concentrate on the computation side, since my background is in computer science. Before I started ARCing (After Retirement Careering), I was a computer science professor who gave himself zero chance of getting a grant from conservative NSF or military funders in the U.S. to speculate on the possibilities of a femtotech. But now that I’m no longer a “wager,” I’m free to do what I like, and can join the billion strong “army” of ARCers, to pursue my own passions.

Continue reading “Hugo de Garis — Innovating Beyond the Nanoscale, Femtometer Scale Technology” | >

Quantum technology holds immense promise, yet it is riddled with complexity. Anticipated to usher in a slew of technological advancements in the upcoming decades, it is set to offer us more compact and accurate sensors, robustly secure communication networks, and high-capacity computers. These advancements will outpace the capabilities of present computing technologies, aiding in the swift development of new drugs and materials, controlling financial markets, and enhancing weather forecasting.

To realize these benefits, we require what are termed as quantum materials, which display significant quantum physical effects. One such material is graphene.

Graphene is an allotrope of carbon in the form of a single layer of atoms in a two-dimensional hexagonal lattice in which one atom forms each vertex. It is the basic structural element of other allotropes of carbon, including graphite, charcoal, carbon nanotubes, and fullerenes. In proportion to its thickness, it is about 100 times stronger than the strongest steel.

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Scientists at the National Institute of Standards and Technology (NIST) with colleagues elsewhere have employed neutron imaging and a reconstruction algorithm to reveal for the first time the 3D shapes and dynamics of very small tornado-like atomic magnetic arrangements in bulk materials.

These collective atomic arrangements, called skyrmions—if fully characterized and understood—could be used to process and store information in a densely packed form that uses several orders of magnitude less energy than is typical now.

The conventional, semiconductor-based method of processing information in binary form (on or off, 0 or 1) employs electrical charge states that must be constantly refreshed by current which encounters resistance as it passes through transistors and connectors. That’s the main reason that computers get hot.

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