Lifeboat Foundation

Quantum computers have the potential to solve complex problems in human health, drug discovery, and artificial intelligence millions of times faster than some of the world’s fastest supercomputers. A network of quantum computers could advance these discoveries even faster. But before that can happen, the computer industry will need a reliable way to string together billions of qubits—or quantum bits—with atomic precision.

Memphis may get most powerful super computer yet.

Memphis, Tennessee, may host the world’s largest supercomputer, the “Gigafactory of Compute.”:

The Memphis Shelby County Economic Development Growth Engine (EDGE), Tennessee Valley Authority (TVA), and governing authorities hold the key to finalizing the project. If approved, it would be the largest investment in Memphis history.

Continue reading “Elon Musk plans ‘world’s most powerful’ supercomputer’ in Memphis” »

@NVIDIAOmniverse is a development platform for virtual world simulation, combining real-time physically based rendering, physics simulation, and generative AI technologies.

In Omniverse, robots can learn to be robots – minimizing the sim-to-real gap, and maximizing the transfer of learned behavior.

Continue reading “Introducing Generative Physical AI” »

Industry and academia in Japan and the United States are collaborating on research to pioneer quantum-centric supercomputing.

One way to manage the unsustainable energy requirements of the computing sector is to fundamentally change the way we compute. Superconductors could let us do just that.

Superconductors offer the possibility of drastically lowering energy consumption because they do not dissipate energy when passing current. True, superconductors work only at cryogenic temperatures, requiring some cooling overhead. But in exchange, they offer virtually zero-resistance interconnects, digital logic built on ultrashort pulses that require minimal energy, and the capacity for incredible computing density due to easy 3D chip stacking.

Are the advantages enough to overcome the cost of cryogenic cooling? Our work suggests they most certainly are. As the scale of computing resources gets larger, the marginal cost of the cooling overhead gets smaller. Our research shows that starting at around 10 ¹⁶ floating-point operations per second (tens of petaflops) the superconducting computer handily becomes more power efficient than its classical cousin. This is exactly the scale of typical high-performance computers today, so the time for a superconducting supercomputer is now.

A new study reveals the sun’s magnetic field originates closer to the surface, solving a 400-year-old mystery first probed by Galileo and enhancing solar storm forecasting.

An international team of researchers, including Northwestern University engineers, is getting closer to solving a 400-year-old solar mystery that stumped even famed astronomer Galileo Galilei.

Since first observing the sun’s magnetic activity, astronomers have struggled to pinpoint where the process originates. Now, after running a series of complex calculations on a NASA supercomputer, the researchers discovered the magnetic field is generated about 20,000 miles below the sun’s surface.

Researchers use NASA supercomputer:

The new discovery not only enhances our understanding of the Sun’s dynamics but can also help in more precise prediction of solar storms.

The Sun’s magnetic field is an incredibly powerful mechanism that produces equally powerful solar storms, some of which resulted in the recent aurora activity observed as far south as the State of Florida. However, in the 400 years since Galileo Galilei first discovered the Sun’s magnetic field, scientists have been stumped regarding where inside the Sun the magnetic field originates. This is what a study published today in Nature hopes to address as a team of international researchers have discovered how deep inside the Sun the magnetic field originates, which holds the potential to help scientists better understand and predict solar storms.

“Understanding the origin of the sun’s magnetic field has been an open question since Galileo and is important for predicting future solar activity, like flares that could hit the Earth,” said Dr. Daniel Lecoanet, who is an Assistant Professor of Engineering Sciences and Applied Mathematics at Northwestern University and a co-author on the study. “This work proposes a new hypothesis for how the sun’s magnetic field is generated that better matches solar observations, and, we hope, could be used to make better predictions of solar activity.”

For the study, the researchers used a NASA supercomputer to conduct several calculations to ascertain if the source of the Sun’s magnetic field was close to the surface or much deeper, as previous hypotheses have stated the magnetic field’s source is more than 130,000 miles beneath the surface of the Sun. In the end, the researchers of this latest study estimated the source of the Sun’s magnetic field is approximately 20,000 miles beneath the surface. For context, the diameter of the Sun is just over 865,000 miles across, so these new findings indicate the magnetic field originates approximately 2 percent beneath the Sun’s surface, as opposed to 15 percent based on the previous hypotheses.

These businesses are building tech that could exceed the abilities of today’s AI.

The field of artificial intelligence is still in its early years, yet several businesses are already working on technology that can become the foundation for AI’s future. These companies are developing quantum computing systems capable of processing mountains of data in seconds, which would take decades for a conventional computer.

Quantum machines can execute multiple computations simultaneously, accelerating processing time, while typical computers must process data in a linear fashion. This means quantum systems can evolve AI beyond the abilities of the most powerful supercomputers, enabling AI to drive cars and help find cures to diseases.