Lifeboat Foundation

A new field of science has been emerging at the intersection of neuroscience and high-performance computing — this is the takeaway from the 2022 BrainComp conference, which took place in Cetraro, Italy from the 19th to the 22nd of September. The meeting, which featured international experts in brain mapping, machine learning, simulation, research infrastructures, neuro-derived hardware, neuroethics and more, strengthened the current collaborations in this emerging field and forged new ones.

Now in its 5th edition, BrainComp first started in 2013 and is jointly organised by the Human Brain Project and the EBRAINS digital research infrastructure, University of Calabria in Italy, the Heinrich Heine University of Düsseldorf and the Forschungszentrum Jülich in Germany. It is attended by researchers from inside and outside the Human Brain Project. This year was dedicated to the computational challenges of brain connectivity. The brain is the most complex system in the observable universe due to the tight connections between areas down to the wiring of the individual neurons: decoding this complexity through neuroscientific and computing advances benefits both fields.

Hosted by the organising committee of Katrin Amunts, Scientific Research Director of the HBP, Thomas Lippert, Leader of EBRAINS Computing Services from the Juelich Supercomputing Centre and Lucio Grandinetti from the University of Calabria, the sessions included a variety of topics over four days.

In the future, many computers will most likely be based on electronic circuits made of superconductors. These are materials through which an electrical current can flow without energy losses, could be very promising for the development of high-performance supercomputers and quantum computers.

Researchers at University of California Santa Barbara, Raytheon BBN Technologies, University of Cagliari, Microsoft Research, and the Tokyo Institute of Technology have recently developed a magneto-optic modulator—a device that control the properties of a light beam through a magnetic field. This device, introduced in a paper published in Nature Electronics, could contribute to the implementation of large-scale electronics and computers based on superconductors.

“We are working on a new technology that can speed up high-performance supercomputers and quantum computers based on superconductor technology,” Paolo Pintus, the researcher who led the study, told TechXplore. “Superconductors work properly only at low temperatures, generally just above absolute zero (−273.15° Celsius). Because of this, circuits made of these materials must be kept inside a dedicated refrigerator.”

Insights into how minute, yet powerful, bubbles form and collapse on underwater surfaces could help make industrial structures such as ship propellers more hardwearing, research suggests.

Supercomputer calculations have revealed details of the growth of so-called nanobubbles, which are tens of thousands of times smaller than a pin head.

The findings could lend valuable insight into damage caused on industrial structures, such as pump components, when these bubbles burst to release tiny but powerful jets of liquid.

The founders all believed that the traditional method of building a quantum computer of a useful size would take too long. At the company’s inception, the PsiQuantum team established its goal to build a million qubit, fault-tolerant photonic quantum computer. They also believed the only way to create such a machine was to manufacture it in a semiconductor foundry.

Early alerts

PsiQuantum first popped up on my quantum radar about two years ago when it received $150 million in Series C funding which upped total investments in the company to $215 million.

China Launches World’s Fastest Quantum Computers | China’s Advancement In Quantum Computers #technology.

“Techno Jungles”

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The most powerful Exascale Supercomputer is going to release in 2021 and will feature a total of 64 Exaflops. More than 6 times as much, as the Leonardo Supercomputer that’s also set to release this year.
This is accomplished with the help of a new type of processor technology from Tachyum that’s called “Prodigy” and is described as the first Universal Processor.

This new processor is set to enable General Artificial Intelligence at the speed of the human brain in real-time. It’s many times faster than the fastest intel xeon, nvidia graphics card or apple silicon. This new super-computer will enable previously-thought impossible simulations of the brain, medicine and more.
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Article originally published on LINKtoLEADERS under the Portuguese title “Sem saber ler nem escrever!”

In the 80s, “with no knowledge, only intuition”, I discovered the world of computing. I believed computers could do everything, as if it were an electronic God. But when I asked the TIMEX Sinclair 1000 to draw the planet Saturn — I am fascinated by this planet, maybe because it has rings —, I only glimpse a strange message on the black and white TV:

0/0

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A team of Japanese and US physicists has pushed thousands of Ytterbium atoms to just within a billionth of a degree above absolute zero to understand how matter behaves at these extreme temperatures. The approach treats the atoms as fermions, the type of particles like electrons and protons, that cannot end up in the so-called fifth state of matter at those extreme temperatures: a Bose-Einstein Condensate.

When fermions are actually cooled down, they do exhibit quantum properties in a way that we can’t simulate even with the most powerful supercomputer. These extremely cold atoms are placed in a lattice and they simulate a “Hubbard model” which is used to study the magnetic and superconductive behavior of materials, in particular the collective motion of electrons through them.

The symmetry of these models is known as the special unitary group, or, SU, and depends on the possible spin state. In the case of Ytterbium, that number is 6. Calculating the behavior of just 12 particles in a SU Hubbard model can’t be done with computers. However, as reported in Nature Physics, the team used laser cooling to reduce the temperature of 300,000 atoms to a value almost three billion times colder than the temperature of outer space.

Creating images from text in seconds—and doing so with a conventional graphics card and without supercomputers? As fanciful as it may sound, this is made possible by the new Stable Diffusion AI model. The underlying algorithm was developed by the Machine Vision & Learning Group led by Prof. Björn Ommer (LMU Munich).

“Even for laypeople not blessed with artistic talent and without special computing know-how and computer hardware, the new model is an effective tool that enables computers to generate images on command. As such, the model removes a barrier to ordinary people expressing their creativity,” says Ommer. But there are benefits for seasoned artists as well, who can use Stable Diffusion to quickly convert new ideas into a variety of graphic drafts. The researchers are convinced that such AI-based tools will be able to expand the possibilities of creative image generation with paintbrush and Photoshop as fundamentally as computer-based word processing revolutionized writing with pens and typewriters.

In their project, the LMU scientists had the support of the start-up Stability. Ai, on whose servers the AI model was trained. “This additional computing power and the extra training examples turned our AI model into one of the most powerful image synthesis algorithms,” says the computer scientist.