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.
“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.”
Like the endlessly repeating patterns of chaos theory, the new solutions discovered by the Chinese researchers make for elaborate and weirdly beautiful images when they are plotted in two dimensions. They are unlikely to have ever existed in reality, however. Because of how solar systems form, planets, moons and stars tend to settle into regular orbits on a single plane.
Posted in supercomputing
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.”
So, let’s just talk about what it can do, then. By taking advantage of the principles of superposition and entanglement, quantum computers can solve certain types of problems exponentially faster than the best supercomputers. “It would allow scientists to do computations in minutes or hours that would take the lifetime of the universe on even the most advanced classical computers,” Microsoft explains. “That, in turn, would mean that people could find answers to scientific questions previously thought unanswerable.”
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.
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.”
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).
Yesterday, AMD revealed the Project 47 supercomputer was powered by 20 AMD EPYC 7601 processors and 80 Radeon Instinct GPUs. It is a petaFLOP supercomputer in a rack. Other hardware included 10TB of Samsung memory and 20 Mellanox 100G cards (and 1 switch). Project 47 is capable of 1 PetaFLOP of single-precision compute performance or 2 PetaFLOPS of half-precision.
Project 47 is built around the Inventec P47. The P47 is a 2U parallel computing platform designed for graphics virtualization and machine intelligence applications. A single rack of Inventec P47 systems is all that was necessary to achieve 1 PetaFLOP, and it does so while producing 30 GigaFLOPS/Watt, which AMD claims is 25% more efficient than some other competing supercomputing platforms. A petaFLOP system uses 33,333 watts. A thousand of PetaFLOP racks would use 33.3 MW and have an exaFLOP.
Thanks to its 32-core / 64-thread EPYC processors and Radeon Vega GPUs, which feature 4,096 stream processors each, AMD also claims that Project 47 rack has more cores/threads, compute units, I/O lanes and memory channels in use simultaneously than in any other similarly configured system.
We have some breaking news from the