Lifeboat Foundation

Researchers at Hokkaido University and Amoeba Energy in Japan have, inspired by the efficient foraging behavior of a single-celled amoeba, developed an analog computer for finding a reliable and swift solution to the traveling salesman problem—a representative combinatorial optimization problem.

Many real-world application tasks such as planning and scheduling in logistics and automation are mathematically formulated as combinatorial optimization problems. Conventional digital computers, including supercomputers, are inadequate to solve these complex problems in practically permissible time as the number of candidate solutions they need to evaluate increases exponentially with the problem size—also known as combinatorial explosion. Thus new computers called Ising machines, including quantum annealers, have been actively developed in recent years. These machines, however, require complicated pre-processing to convert each task to the form they can handle and have a risk of presenting illegal solutions that do not meet some constraints and requests, resulting in major obstacles to the practical applications.

These obstacles can be avoided using the newly developed ‘electronic amoeba,’ an analog computer inspired by a single-celled amoeboid organism. The amoeba is known to maximize nutrient acquisition efficiently by deforming its body. It has shown to find an approximate solution to the traveling salesman problem (TSP), i.e., given a map of a certain number of cities, the problem is to find the shortest route for visiting each city exactly once and returning to the starting city. This finding inspired Professor Seiya Kasai at Hokkaido University to mimic the dynamics of the amoeba electronically using an analog circuit, as described in the journal Scientific Reports. “The amoeba core searches for a solution under the electronic environment where resistance values at intersections of crossbars represent constraints and requests of the TSP,” says Kasai. Using the crossbars, the city layout can be easily altered by updating the resistance values without complicated pre-processing.

In what could be one of the significant developments in the field of quantum computing, Chinese researchers suggest having achieved quantum supremacy with the capability of performing calculations 100 trillion times faster than the world’s most advanced supercomputer. Researchers from the University of Science and Technology of China, Hefei, believe that when put into practical use, it can carry calculations in minutes which would have otherwise taken two billion years to perform. The fastest supercomputers, before this, claimed to have achieved computational efficiency easing up to 10,000 years of calculations.

Jiuzhang, as the supercomputer is called, has outperformed Google’s supercomputer, which the company had claimed last year to have achieved quantum computing supremacy. The supercomputer by Google named Sycamore is a 54-qubit processor, consisting of high-fidelity quantum logic gates that could perform the target computation in 200 seconds.

Continue reading “Quantum Computing Marks New Breakthrough, Is 100 Trillion Times More Efficient” »

A specialised quantum computer has achieved quantum supremacy, accomplishing in under 4 minutes what would take the biggest supercomputer 600 million years.

Since Xi put out the call to build up the new area, China’s tech giants have piled in. Alibaba Group Holding, Tencent Holdings, Baidu, Zhongguancun Science Park and Tsinghua University have all established projects in Xiongan. The projects include the use of sensors, 5G networks and facilities for supercomputing and big data in the pursuit of building up the smart city. Alibaba is the parent company of the Post.

JD Digits, the e-commerce giant’s big data arm, is building a smart city operating system that uses artificial intelligence for urban management.

The biggest computer chip in the world is so fast and powerful it can predict future actions “faster than the laws of physics produce the same result.”

That’s according to a post by Cerebras Systems, a startup company that made the claim at the online SC20 supercomputing conference this week.

Working with the U.S. Department of Energy’s National Energy Technology Laboratory, Cerebras designed what it calls “the world’s most powerful AI compute system.” It created a massive chip 8.5 inch-square chip, the Cerebras CS-1, housed in a refrigerator-sized computer in an effort to improve on deep-learning training models.

Scientists from NASA ’s Goddard Space Flight Center in Greenbelt, Maryland, and international collaborators demonstrated a new method for mapping the location and size of trees growing outside of forests, discovering billions of trees in arid and semi-arid regions and laying the groundwork for more accurate global measurement of carbon storage on land.

Using powerful supercomputers and machine learning algorithms, the team mapped the crown diameter – the width of a tree when viewed from above – of more than 1.8 billion trees across an area of more than 500,000 square miles, or 1,300,000 square kilometers. The team mapped how tree crown diameter, coverage, and density varied depending on rainfall and land use.

Researchers pitted the biggest computer chip in the world against a supercomputer to simulate combustion—and the megachip won the race by a mile.

Special thanks to Lieuwe Vinkhuyzen for checking that this very simplified view on building neural nets did not stray too far from reality.

The inhabitants of the Tesla fanboy echo chamber have heard regularly about the Tesla Dojo supercomputer, with almost nobody knowing what it was. It was first mentioned, that I know of, at Tesla Autonomy Day on April 22, 2019. More recently a few comments from Georg Holtz, Tesmanian, and Elon Musk himself have shed some light on this project.

Aurora 21 will help the US keep pace among the other nations who own the fastest supercomputers. Scientists plan on using it to map the connectome of the human brain.