Lifeboat Foundation: Safeguarding Humanity
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Category: supercomputing – Page 44

The U.S. Department of Energy’s (DOE) Office of Science announced allocations of supercomputer access to 56 high-impact computational science projects for 2023 through its Innovative and Novel Computational Impact on Theory and Experiment (INCITE) program. These awards, which will pursue transformational advances in science and engineering, account for 60% of the available time on the leadership-class supercomputers at DOEs Argonne and Oak Ridge national laboratories.

The projects will support a broad range of large-scale research campaigns to advance knowledge in areas ranging from astrophysics to sustainable energy technologies to materials design and discovery.

Jointly managed by the Argonne Leadership Computing Facility (ALCF) and the Oak Ridge Leadership Computing Facility (OLCF), the INCITE program is the primary means by which the facilities fulfill their mission to advance open science by providing the scientific community with access to their powerful supercomputing resources. The ALCF and OLCF are DOE Office of Science user facilities.

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The hundreds of gold-rich stars discovered in our Milky Way galaxy may have come from smaller galaxies that merged 10 billion years ago, according to new simulations by a supercomputer.

Using the ATERUI II supercomputer in the Center for Computational Astrophysics at the National Astronomical Observatory of Japan, scientists at Tohoku University and the University of Notre Dame developed new simulations of galaxy formation with the highest resolution yet.

The paper was published this week in the Monthly Notices of the Royal Astronomical Society.

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Could energy efficiency be quantum computers’ greatest strength yet?

Bartlomiej Wroblewski/iStock.

However, the question of its energy consumption could also now warrant research, with current supercomputers sometimes consuming as much electricity as a small town (which could in fact limit the increase in their computing power). Information technologies, at their end, accounted for 11% of global electricity consumption in 2020.

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With mathematical modeling, a research team has now succeeded in better understanding how the optimal working state of the human brain, called criticality, is achieved. Their results mean an important step toward biologically-inspired information processing and new, highly efficient computer technologies and have been published in Scientific Reports.

“In particular tasks, supercomputers are better than humans, for example in the field of artificial intelligence. But they can’t manage the variety of tasks in —driving a car first, then making music and telling a story at a get-together in the evening,” explains Hermann Kohlstedt, professor of nanoelectronics. Moreover, today’s computers and smartphones still consume an enormous amount of energy.

“These are no sustainable technologies—while our brain consumes just 25 watts in everyday life,” Kohlstedt continues. The aim of their interdisciplinary research network, “Neurotronics: Bio-inspired Information Pathways,” is therefore to develop new electronic components for more energy-efficient computer architectures. For this purpose, the alliance of engineering, life and investigates how the is working and how that has developed.

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This time I come to talk about a new concept in this Age of Artificial Intelligence and the already insipid world of Social Networks. Initially, quite a few years ago, I named it “Counterpart” (long before the TV series “Counterpart” and “Black Mirror”, or even the movie “Transcendence”).

It was the essence of the ETER9 Project that was taking shape in my head.

Over the years and also with the evolution of technologies — and of the human being himself —, the concept “Counterpart” has been getting better and, with each passing day, it makes more sense!

Imagine a purely digital receptacle with the basics inside, like that Intermediate Software (BIOS(1)) that computers have between the Hardware and the Operating System. That receptacle waits for you. One way or another, it waits patiently for you, as if waiting for a Soul to come alive in the ether of digital existence.

Continue reading “Digital Doubles and Second Selves” | >

Are we alone in the universe? What could a future for humans in space look like? And what would Creon’s advise to Elon Musk be if he wants to make a self-sufficient mass colony there? This Hope Drop features Creon Levit, chief technologist and director of R&D at Planet Labs.

Creon Levit is chief technologist at Planet Labs, where he works to move the world toward existential hope via novel satellite technologies. He also hosts Foresight Institute’s Space Group.

Creon speaks on:

- His experiences working with NASA & Planet Labs.
- Natural systems technologies.
- Regenerative Agriculture.
- His vision for the future.
- And much more!

Creon is chief technologist and director of R&D at Planet Labs, and a Foresight Institute senior fellow. He previously worked at NASA Ames Research Center in Silicon Valley, where he was one of the founders of the NAS (NASA Advanced Supercomputing) division, co-PI on the Virtual Wind Tunnel project, co-founder of the NASA Molecular Nanotechnology Group (the first federally funded research lab devoted to molecular nanotechnology), co-PI on the hyperwall project, investigator on the Columbia accident investigation board, member of the NASA engineering and safety center, investigator on the millimeter-wave thermal rocket project, the Stardust re-entry observation campaign, PI on the LightForce project, special assistant to the center director, and chief scientist for the programs and projects directorate.

Submit your contribution to the storytelling bounty from Creon’s prompt to “Imagine a shift in human nature where we could all have love, community, technology, and adventure, as well as lack of severe hardship or fear.” here: https://680d4kcs6ki.typeform.com/to/jHROTs6z.

Continue reading “Existential Hope: Creon Levit | On space and the long-term future” | >

Elon Musk Reveals Secret DOJO Computer at Tesla AI Day.
#teslanews #teslaai #elonmusk.

During AI Day, the Tesla CEO was the first person to confirm the existence of the ‘Dojo’ program: “We do have a major program at Tesla which we don’t have enough time to talk about today called ” Dojo”. That’s a super powerful training computer. The goal of Dojo will be to be able to take in vast amounts of data and train at a video level and do massive unsupervised training of vast amounts of video with the Dojo program – or Dojo computer.”
In June 2020, Elon Musk tweeted, “Dojo, our training supercomputer, will be able to process vast amounts of video training data & efficiently run hyperspace arrays with an enormous number of parameters, plenty of memory & ultra-high bandwidth between cores.

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Circa 2018 face_with_colon_three

Since the time of Hippocrates and Herophilus, scientists have placed the location of the mind, emotions and intelligence in the brain. For centuries, this theory was explored through anatomical dissection, as the early neuroscientists named and proposed functions for the various sections of this unusual organ. It wasn’t until the late 19th century that Camillo Golgi and Santiago Ramón y Cajal developed the methods to look deeper into the brain, using a silver stain to detect the long, stringy cells now known as neurons and their connections, called synapses.

Today, neuroanatomy involves the most powerful microscopes and computers on the planet. Viewing synapses, which are only nanometers in length, requires an electron microscope imaging a slice of brain thousands of times thinner than a sheet of paper. To map an entire human brain would require 300,000 of these images, and even reconstructing a small three-dimensional brain region from these snapshots requires roughly the same supercomputing power it takes to run an astronomy simulation of the universe.

Fortunately, both of these resources exist at Argonne, where, in 2015, Kasthuri was the first neuroscientist ever hired by the U.S. Department of Energy laboratory. Peter Littlewood, the former director of Argonne who brought him in, recognized that connectome research was going to be one of the great big data challenges of the coming decades, one that UChicago and Argonne were perfectly poised to tackle.

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