Lifeboat Foundation

A novel computer algorithm, or set of rules, that accurately predicts the orbits of planets in the solar system could be adapted to better predict and control the behavior of the plasma that fuels fusion facilities designed to harvest on Earth the fusion energy that powers the sun and stars.

The algorithm, devised by a scientist at the U.S. Department of Energy’s (DOE) Princeton Plasma Physics Laboratory (PPPL), applies machine learning, the form of artificial intelligence (AI) that learns from experience, to develop the predictions. “Usually in physics, you make observations, create a theory based on those observations, and then use that theory to predict new observations,” said PPPL physicist Hong Qin, author of a paper detailing the concept in Scientific Reports. “What I’m doing is replacing this process with a type of black box that can produce accurate predictions without using a traditional theory or law.”

Qin (pronounced Chin) created a computer program into which he fed data from past observations of the orbits of Mercury, Venus, Earth, Mars, Jupiter, and the dwarf planet Ceres. This program, along with an additional program known as a “serving algorithm,” then made accurate predictions of the orbits of other planets in the solar system without using Newton’s laws of motion and gravitation. “Essentially, I bypassed all the fundamental ingredients of physics. I go directly from data to data,” Qin said. “There is no law of physics in the middle.”

The toolset runs with Q-CTRL’s flagship BOULDER OPAL software for developers and R&D teams, automated closed-loop hardware optimization is also trained to obtain new experimental data/results from quantum computers while simultaneously running optimizations for algorithms. It can be used as a standalone tool or in tandem with a machine-learner online optimization package (M-LOOP) that manages quantum experiments autonomously.

Facebook says that political content currently constitutes only 6% of what people see on the platform. It will begin running experiments to reduce that amount for a small percentage of people in Canada, Brazil and Indonesia immediately, with tests in the U.S. in weeks to come.

The company said it isn’t removing political content but rather exploring ways to reduce the exposure for users who would prefer not to see it. In practice, that means Facebook will still allow users to post about politics and argue among friends, but its algorithms will de-prioritize those conversations and spread them less widely across the network.

Facebook says it is beginning to reduce how much political content users see on its main platform, potentially diminishing the role that the world’s largest social network plays in elections and civil discourse more broadly.

As far as ‘compiling’ this into a human — I definitely don’t see the path to that.

Summary: A new machine-learning algorithm which videos of echocardiograms is able to accurately predict patients who will die within a year.

Source: Geisinger Health System

Circa 2013 o.o

Quantum entanglement, one of the odder aspects of quantum theory, links the properties of particles even when they are separated by large distances. When a property of one of a pair of entangled particles is measured, the other “immediately” settles down into a state compatible with that measurement. So how fast is “immediately”? According to research by Prof. Juan Yin and colleagues at the University of Science and Technology of China in Shanghai, the lower limit to the speed associated with entanglement dynamics – or “spooky action at a distance” – is at least 10000 times faster than light.

Despite playing a vital role in the development of quantum theory, Einstein felt philosophically at odds with its description of how the universe works. His famous quote that “God does not play dice” hints at his level of discomfort with the role of probability in quantum theory. He believed there exists another level of reality in which all of physics would be deterministic, and that quantum mechanics would turn out to be a description that emerges from the workings of that level – rather like a traffic jam emerges from the independent motions of a large number of cars.

Continue reading “Quantum ‘spooky action at a distance’ travels at least 10,000 times faster than light” »

Each year, billions of tons of goods are transported globally using cargo containers. Currently, there are concerns that this immense volume of traffic could be exploited to transport illicit nuclear materials, with little chance of detection. One promising approach to combating this issue is to measure how goods interact with charged particles named muons—which form naturally as cosmic rays interact with Earth’s atmosphere. Studies worldwide have now explored how this technique, named “muon tomography,” can be achieved through a variety of detection technologies and reconstruction algorithms. In this article of EPJ Plus, a team headed by Francesco Riggi at the University of Catania, Italy, build on these results to develop a full-scale muon tomograph prototype.

Attacks on vulnerable computer networks and cyber-infrastructure—often called zero-day attacks—can quickly overwhelm traditional defenses, resulting in billions of dollars of damage and requiring weeks of manual patching work to shore up the systems after the intrusion.

Computer-aided calculations have played a crucial part in producing the proofs of several high-profile results. And more recently, some mathematicians have made progress towards AI that doesn’t just perform repetitive calculations, but develops its own proofs. Another growing area has been software that can go over a mathematical proof written by humans and check that it is correct.

Algorithm named after mathematician Srinivasa Ramanujan suggests interesting formulae, some of which are difficult to prove true.