Archive for the ‘computing’ category: Page 2

Aug 31, 2023

Analog and digital: The best of both worlds in one energy-efficient system

Posted by in categories: computing, neuroscience

We live in an analog world of continuous information flow that is both processed and stored by our brains at the same time, but our devices process information digitally in the form of discrete binary code, breaking the information into little bits (or bites).

Researchers at EPFL have revealed a pioneering technology that combines the potential of continuous analog processing with the precision of digital devices. By seamlessly integrating ultra-thin, two-dimensional semiconductors with ferroelectric materials, the research, published in Nature Electronics, unveils a novel way to improve and add new functionalities in computing. The new configuration merges traditional digital logic with brain-like analog operations.

The innovation from the Nanoelectronics Device Laboratory (Nanolab), in collaboration with Microsystems Laboratory, revolves around a unique combination of materials leading to brain-inspired functions and advanced electronic switches, including the standout negative capacitance Tunnel Field-Effect Transistor (TFET).

Aug 31, 2023

Agency, Attractors, & Observer-Dependent Computation in Biology & Beyond

Posted by in categories: alien life, computing, engineering, ethics, genetics, quantum physics

Michael Levin discusses his 2022 paper “Technological Approach to Mind Everywhere: An Experimentally-Grounded Framework for Understanding Diverse Bodies and Minds” and his 2023 paper with Joshua Bongard, “There’s Plenty of Room Right Here: Biological Systems as Evolved, Overloaded, Multi-scale Machines.” Links to papers flagged 🚩below.

Michael Levin is a scientist at Tufts University; his lab studies anatomical and behavioral decision-making at multiple scales of biological, artificial, and hybrid systems. He works at the intersection of developmental biology, artificial life, bioengineering, synthetic morphology, and cognitive science.

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Aug 31, 2023

Transistor can adhere to internal organs like tape

Posted by in categories: biotech/medical, computing

UChicago researchers’ design makes stable, suture-free medical monitoring in body possible.

Aug 30, 2023

Future computers could be built using proteins that make up cells

Posted by in categories: biological, computing

Future computers could be built smaller than ever before using the tiny biological skeletons that hold our cells together.

That’s according to one team of scientists, who have devised a way to make computer chips using cytoskeletons — protein scaffolds that give cells their shape.

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Aug 30, 2023

Nano-Biological Computing — Quantum Computer Alternative!

Posted by in categories: biological, computing, nanotechnology, quantum physics

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Here it is, the bio computer. A new type of parallel computing method that could rival the infamous quantum computer at a much lower price while being more practical to boot.

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Aug 30, 2023

A new protocol to reliably demonstrate quantum computational advantage

Posted by in categories: computing, quantum physics

Quantum computers, devices that perform computations by exploiting quantum mechanical phenomena, have the potential to outperform classical computers on some tasks and optimization problems. In recent years, research teams at both academic institutions and IT companies have been trying to realize this predicted better performance for specific problems, which is broadly known as “quantum advantage.”

To reliably demonstrate that a quantum computer performs better than a classical computer, one should, among other things, collect inside the computer and compare them to those collected in . Doing this, however, can sometimes be challenging, due to the distinct nature of these two types of devices.

Researchers at NIST/University of Maryland, UC Berkeley, Caltech and other institutes in the United States recently introduced and tested a new protocol that could help to reliably validate the advantage of quantum computers. This protocol, introduced in Nature Physics, relies on mid-circuit measurements and a cryptographic technique.

Aug 29, 2023

Quantum simulator helps to unlock a major science mystery

Posted by in categories: chemistry, computing, quantum physics, science

A new study exemplifies how the strides made in quantum computing are now being harnessed to unlock the secrets of fundamental science.

Scientists at Duke University have harnessed the power of quantum-based methods to unravel a puzzling phenomenon related to light-absorbing molecules, according to a new study published in Nature Chemistry.

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Aug 29, 2023

Intel makes new chip more than double the power of others

Posted by in category: computing

In a bid to reduce data center power consumption, Intel has unveiled its new “Sierra Forest” chip with over double the power efficiency of other chips.

Intel has reported that its new chip, “Sierra Forest,” will have over double the efficiency for the same power consumption of other microchips. Designed as a new data center chip, Intel’s new double-efficiency chip is scheduled for release sometime in 2024, Reuters.

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Aug 29, 2023

Quantum device used to slow chemical reaction 100 billion times

Posted by in categories: chemistry, computing, quantum physics

A team of researchers has successfully simulated and” observed” a slow-motion chemical reaction at a billion times slower than “normal.”

For the first time ever, scientists have succeeded in slowing down (in simulation) a chemical reaction by around 100 billion times. Using a quantum computer, the researchers simulated and then “observed” the reaction in super slow motion.

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Aug 29, 2023

Memristors make versatile artificial synapses for neuromorphic computing

Posted by in categories: computing, mobile phones, neuroscience

Most modern computers – from primitive room-filling behemoths like the ENIAC to the smartphone in your pocket – are built according to a set of principles laid out by the mathematician John von Neumann in 1945. This von Neumann architecture, as it is known, incorporates many familiar elements, including a central processing unit, a memory for storing data and instructions, and input and output devices. Despite its ubiquity, though, von Neumann’s model is not the only way of building a computer, and for some applications, it is not the most desirable, either.

One emerging alternative is known as neuromorphic computing. As the name implies, neuromorphic computers are inspired by the architecture of the human brain and use highly connected artificial neurons and artificial synapses to simulate the brain’s structure and functions. For researchers like Le Zhao of China’s Qilu University of Technology, this neuromorphic model offers a fantastic opportunity to develop a new paradigm for computing – as long as we can develop artificial neurons and synapses that have the right properties.

In a recent paper published in Materials Futures, Zhao and colleagues describe how to use a memristor – essentially a switch that “remembers” which electric state it was in, even after its power is turned off – to emulate the function of a synapse in the brain. Here, he explains the team’s goals and plans.

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