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Rumour has it that Albert Einstein spent his last few hours on Earth scribbling something on a piece of paper in a last attempt to formulate a theory of everything. Some 60 years later, another legendary figure in theoretical physics, Stephen Hawking, may have passed away with similar thoughts. We know Hawking thought something called “M-theory” is our best bet for a complete theory of the universe. But what is it?

Since the formulation of Einstein’s theory of in 1915, every theoretical physicist has been dreaming of reconciling our understanding of the infinitely small world of atoms and particles with that of the infinitely large scale of the cosmos. While the latter is effectively described by Einstein’s equations, the former is predicted with extraordinary accuracy by the so-called Standard Model of fundamental interactions.

Our current understanding is that the interaction between physical objects is described by four fundamental forces. Two of them – gravity and electromagnetism – are relevant for us on a macroscopic level, we deal with them in our everyday life. The other two, dubbed strong and weak interactions, act on a very small scale and become relevant only when dealing with subatomic processes.

20th century physics has seen two major paradigm shifts in the way we understand Mother Nature. One is quantum mechanics, and the other is relativity. The marriage between the two, called quantum field theory, conceived an enfant terrible, namely anti-matter. As a result, the number of elementary particles doubled. We believe that 21st century physics is aimed at yet another level of marriage, this time between quantum mechanics and general relativity, Einstein’s theory of gravity. The couple has not been getting along very well, resulting in mathematical inconsistencies, meaningless infinities, and negative probabilities. The key to success may be in supersymmetry, which doubles the number of particles once more.

Why was anti-matter needed? One reason was to solve a crisis in the 19th century physics of classical electromagnetism. An electron is, to the best of our knowledge, a point particle. Namely, it has no size, yet an electric charge. A charged particle inevitably produces an electric potential around it, and it also feels the potential created by itself. This leads to an infinite “self-energy” of the electron. In other words, it takes substantial energy to “pack” all the charge of an electron into small size.

On the other hand, Einstein’s famous equation says that mass of a particle determines the energy of the particle at rest. For an electron, its rest energy is known to be 0.511 MeV. For this given amount of energy, it cannot afford to “pack” itself into a size smaller than the size of a nucleus. Classical theory of electromagnetism is not a consistent theory below this distance. However, it is known that the electron is at least ten thousand times smaller than that.

This week a collaborative effort among computer scientists and academics to safeguard data is winning attention and it has quantum computing written all over it.

The Netherlands’ Centrum Wiskunde & Informatica (CWI), national research institute for mathematics and computer science, had the story: IBM Research developed “quantum-safe algorithms” for securing data. They have done so by working with international partners including CWI and Radboud University in the Netherlands.

IBM and partners share concerns that data protected by current encryption methods may become insecure within the next 10 to 30 years.

A team of Australian researchers has designed a reliable strategy for testing physical abilities of humanoid robots—robots that resemble the human body shape in their build and design. Using a blend of machine learning methods and algorithms, the research team succeeded in enabling test robots to effectively react to unknown changes in the simulated environment, improving their odds of functioning in the real world.

The findings, which were published in a joint publication of the IEEE and the Chinese Association of Automation Journal of Automatica Sinica in July, have promising implications in the broad use of in fields such as healthcare, education, disaster response and entertainment.

“Humanoid robots have the ability to move around in many ways and thereby imitate human motions to complete complex tasks. In order to be able to do that, their stability is essential, especially under dynamic and unpredictable conditions,” said corresponding author Dacheng Tao, Professor and ARC Laureate Fellow in the School of Computer Science and the Faculty of Engineering at the University of Sydney.

Aren Jay shared this cogent article to my Timeline… It is not new even Hippocrates was able to determine that the gut causes and or assists in all diseases. But the 19th and 20th centuries researchers began saying that microbes are good for mankind which sent science reeling through generations until this day… Respect r.p.berry & AEWR wherein we have developed a formula and Algorithm that deals with this very serious problem completely. A very expensive cure but one that will take Woman-Man past the Escape Velocity so many have written about… https://gerevivify.blogspot.com/


Recent research has found that bacteria in the gut can affect people’s mental state, leading to mood, cognition and behavioural problems. But in TCM, the link between the gut and all of the body’s organs has long been recognised.

David Lindell, a graduate student in electrical engineering at Stanford University, along with his team, developed a camera that can watch moving objects around corners. When they tested the new technology, Lindell wore a high visibility tracksuit as he moved around an empty room. They had a camera that was aimed at a blank wall away from Lindell, and the team was able to watch all of his movements with the use of a high powered laser. The laser reconstructed the images through the use of single particles of light that were reflected onto the walls around Lindell. The newly developed camera used advanced sensors and a processing algorithm.

Gordon Wetzstein, assistant professor of electrical engineering at Stanford, spoke about the newly developed technology.

“People talk about building a camera that can see as well as humans for applications such as autonomous cats and robots, but we want to build systems that go well beyond that,” he said. “We want to see things in 3D, around corners and beyond the visible light spectrum.”

Two researchers at Harvard University, Aavishkar A. Patel and Subir Sachdev, have recently presented a new theory of a Planckian metal that could shed light on previously unknown aspects of quantum physics. Their paper, published in Physical Review Letters, introduces a lattice model of fermions that describes a Planckian metal at low temperatures (Tà 0).

Metals contain numerous , which carry . When physicists consider the electrical resistance of metals, they generally perceive it as arising when the flow of current-carrying electrons is interrupted or degraded due to electrons scattering off impurities or off the crystal lattice in the metal.

“This picture, put forth by Drude in 1900, gives an equation for the electrical resistance in terms of how much time electrons spend moving freely between successive collisions,” Patel told Phys.org. “The length of this time interval between collisions, called the ‘,’ or ‘electron liftetime,’ is typically long enough in most common metals for the electrons to be defined as distinct, mobile objects to a microscopic observer, and the Drude picture works remarkably well.”

Under his plan, “Justice and Safety for All,” Bernie Sanders wants to ban facial recognition software for policing. As a supporter of Sanders, I’m going to have to respectfully disagree. Here’s why…


Last Sunday, presidential-hopeful Bernie Sanders released on his website what is arguably one of the most extensive plans for law enforcement oversight and criminal justice overhaul that the United States has ever seen. As a progressive, myself, and supporter of Sanders during his primary run, I fully endorse everything that’s been laid out in this plan— that is, except for one minor policy.

The plan, titled “Justice and Safety for All,” calls to “Ban the use of facial recognition software for policing.” It also calls for a “moratorium on the use of the algorithmic risk assessment tools in the criminal justice system until an audit is completed,” whereby the audit would “ensure these tools do not have any implicit biases that lead to unjust or excessive sentences.”

I’m perfectly fine with the policy on algorithmic risk assessment tools being used by our criminal justice system. It’s not a total ban; it simply serves as a temporary safety measure until it’s been proven that these algorithms won’t carry with them any unjust biases. But when it comes to Sanders’ policy on banning facial recognition software for policing, I simply cannot get behind it.