Lifeboat Foundation

How far should we integrate human physiology with technology? What do we do with self-aware androids—like Blade Runner’s replicants—and self-aware supercomputers? Or the merging of our brains with them? If Ray Kurzweil’s famous singularity—a future in which the exponential growth of technology turns into a runaway train—becomes a reality, does religion have something to offer in response?

Yes, not only is A.I. potentially taking all of our jobs, but it’s also changing religion.

Brandon Withrow

“Scientists and philosophers… had always assumed that the world worked by physical laws, and if you could measure initial conditions accurately enough, those laws would let you predict the future indefinitely. As James Gleick described it in his book Chaos: Making a New Science, this view was very wrong.”

“There was always one small compromise, so small that working scientists usually forgot it was there, lurking in a corner of their philosophies like an unpaid bill. Measurements could never be perfect,” he wrote. “Scientists marching under Newton’s banner actually waved another flag that said something like this: Given an approximate knowledge of a system’s initial conditions and an understanding of natural law, one can calculate the approximate behaviour of the system. This assumption lay at the philosophical heart of science.”

“Today we know how wrong this assumption was. The Three Body Problem is now recognized as a classic example of a chaotic system. Like the butterfly that causes a hurricane by flapping its wings, it is exquisitely sensitive to initial conditions. The tiniest tweak can have massive consequences down the line.”

Continue reading “How Chinese scientists used a supercomputer to solve the ancient puzzle called the Three Body Problem” »

SPONSOR CONTENT: The U.S. Department of Energy tasked six major computing companies with researching and developing an exascale supercomputer.

With the ability to run a quintillion calculations per second—that’s a one with eighteen zeros after it—the implications of an exascale computer would touch nearly every facet of our lives, and would provide the opportunity to potentially solve humanity’s most pressing problems. http://theatln.tc/2xc7QLn

Aleksandr Noy has big plans for a very small tool. A senior research scientist at Lawrence Livermore National Laboratory, Noy has devoted a significant part of his career to perfecting the liquid alchemy known as desalination—removing salt from seawater. His stock-in-trade is the carbon nanotube. In 2006, Noy had the audacity to embrace a radical theory: Maybe nanotubes—cylinders so tiny, they can be seen only with an electron microscope—could act as desalination filters. It depended on just how wide the tubes were. The opening needed to be big enough to let water molecules flow through but small enough to block the larger salt particles that make seawater undrinkable. Put enough carbon nanotubes together and you potentially have the world’s most efficient machine for making clean water.

When one of the first personal computers, the Altair 8800 came along in 1976, Microsoft was ready with a programming language, Altair BASIC. It wants to be equally prepared when quantum computers go mainstream, so it has unveiled a new programming language and other tools for the futuristic tech at its Ignite conference. You’ll still need to understand Qubits and other weird concepts, but by integrating traditional languages like C# and Python, Microsoft will make it easier to do mainstream computing on the complex machines.

Quantum computing is famously difficult to grasp — even IBM’s “Beginner’s Guide” is laughingly opaque. In discussing Microsoft’s new initiatives, Bill Gates called the physics “hieroglyphics,” and when asked if he could describe it in one sentence, Satya Nadella said “I don’t think so. I wish I could.”

Continue reading “Microsoft’s new coding language is made for quantum computers” »

We have some breaking news from the IHPC Forum in Guangzhou today. Researchers in China are busy upgrading the MilkyWay 2 (Tianhe-2) system to nearly 95 Petaflops (peak). This should nearly double the performance of the system, which is currently ranked at #2 on TOP500 with 33.86 Petaflops on the Linpack benchmark. The upgraded system, dubbed Tianhe −2A, should be completed in the coming months.

Details about the system upgrade were presented at the conference opening session. While the current system derives much of its performance from Intel Knights Corner co-processors, the new system swaps these PCI devices out for custom-made 4-way MATRIX-200o boards, with each chip providing 2.46 Teraflops of peak performance.

Continue reading “China Upgrading Milky Way 2 Supercomputer to 95 Petaflops” »

At the Barcelona Supercomputer Centre on Wednesday (Sept. 6), 16 partners gathered to launch the EuroEXA project, which invests €20 million over three-and-a-half years into exascale-focused research and development.

Led by the Horizon 2020 program, EuroEXA picks up the banner of a triad of partner projects — ExaNeSt, EcoScale and ExaNoDe — building on their work to develop a complete HPC system based on ARM Cortex processors and Xilinx Ultrascale FPGAs. The goal is to deploy an energy-efficient petaflops system by 2020 and lay a path to achieve exascale capability in the 2022–23 timeframe.

All told, the European Commission is planning a €50 million investment for the EuroEXA group of projects, spanning “research, innovation and action across applications, system software, hardware, networking, storage, liquid cooling and data centre technologies.”

Continue reading “EU Funds 20 Million Euro ARM+FPGA Exascale Project” »

From smartphones to supercomputers, the growing need for smaller and more energy efficient devices has made higher density data storage one of the most important technological quests.

Now scientists at the University of Manchester have proved that storing data with a class of molecules known as single-molecule magnets is more feasible than previously thought.

The research, led by Dr David Mills and Dr Nicholas Chilton, from the School of Chemistry, is being published in Nature. It shows that magnetic hysteresis, a memory effect that is a prerequisite of any data storage, is possible in individual molecules at −213 °C. This is tantalisingly close to the temperature of liquid nitrogen (−196 °C).

Continue reading “Major leap towards storing data at the molecular level” »