The theories of QED suggest that the universe is full of “virtual particles,” which are not really particles at all. They are fluctuations in quantum fields that have most of the same properties as particles, except they appear and vanish all the time. Scientists predicted the existence of virtual particles some 80 years ago, but we have never had experimental evidence of this process until now.
“Many people have long speculated that there has to be a basic design principle from which intelligence originates and the brain evolves, like how the double helix of DNA and genetic codes are universal for every organism,” Dr. Tsien said.
“We present evidence that the brain may operate on an amazingly simple mathematical logic.”
The authors believe that future designs of their technology could be used to automatically trigger drug release in humans when required.
The algorithm can be trained to track brain states that underlie ADHD or schizophrenia or otherwise be modified to suit your needs, explains study author Sachar Arnon to New Scientist. For example, if EEG detects signs of a burgeoning depressive episode, it could trigger DNA robots to expose anti-depressants briefly to counteract symptoms before they become full-blown. This way, the brain isn’t perpetually bathed in mind-altering drugs even when they’re not needed.
It’s a futuristic idea, and lots of things still need to be ironed out.
Artificial neural networks are famously based on biological ones. So not only do Lin and Tegmark’s ideas explain why deep learning machines work so well, they also explain why human brains can make sense of the universe. Evolution has somehow settled on a brain structure that is ideally suited to teasing apart the complexity of the universe.
This work opens the way for significant progress in artificial intelligence. Now that we finally understand why deep neural networks work so well, mathematicians can get to work exploring the specific mathematical properties that allow them to perform so well. “Strengthening the analytic understanding of deep learning may suggest ways of improving it,” say Lin and Tegmark.
Deep learning has taken giant strides in recent years. With this improved understanding, the rate of advancement is bound to accelerate.
The long-standing puzzle to be solved is why we and everything we see is matter-made. More to the point, why does anything — matter or antimatter — exist at all? The reigning laws of particle physics, known as the Standard Model, treat matter and antimatter nearly equivalently, respecting (with one known exception) so-called charge-parity, or “CP,” symmetry: For every particle decay that produces, say, a negatively charged electron, the mirror-image decay yielding a positively charged antielectron occurs at
In a unique twist, this binary star system is exhibiting some brutal behaviour. Highly magnetic and spinning rapidly, AR Sco’s white dwarf accelerates electrons up to almost the speed of light. As these high energy particles whip through space, they release radiation in a lighthouse-like beam which lashes across the face of the cool red dwarf star, causing the entire system to brighten and fade dramatically every 1.97 minutes. These powerful pulses include radiation at radio frequencies, which has never been detected before from a white dwarf system.
“During such interplanetary travel, astronauts will be exposed to multiple sources of ionizing radiation, including galactic cosmic rays, solar particle events, and trapped radiation in the Van Allen belts,” claims the paper. For this reason, humans are going to need serious protection to not only survive the long journey to Mars but to also become a fully space-faring civilization that continues to extend our reach into the solar system.
Excellent article on a question I’ve had for a long time.
“In the broadest sense, ‘particles’ are physical things that we can count,” says Greg Gbur, a science writer and physicist at the University of North Carolina in Charlotte. You can’t have half a quark or one-third of an electron. And all particles of a given type are precisely identical to each other: they don’t come in various colors or have little license plates that distinguish them. Any two electrons will produce the same result in a detector, and that’s what makes them fundamental: They don’t come in a variety pack.
Source: What is a “particle”?
Watson is more capable and human-like than ever before, especially when injected into a robot body. We got to see this first-hand at NVIDIA’s GPU Technology Conference (GTC) when Rob High, an IBM fellow, vice president, and chief technology officer for Watson, introduced attendees to a robot powered by Watson. During the demonstration, we saw Watson in robot form respond to queries just like a human would, using not only speech but movement as well. When Watson’s dancing skills were called into question, the robot responded by showing off its Gangnam Style moves.
This is the next level of cognitive computing that’s beginning to take shape now, both in terms of what Watson can do when given the proper form, and what it can sense. Just like a real person, the underlying AI can get a read on people through movement and cognitive analysis of their speech. It can determine mood, tone, inflection, and so forth.
For the first time, researchers have developed a microscope capable of observing — and manipulating — neural activity in the brains of live animals at the scale of a single cell with millisecond precision. The device, which uses lasers to create holographic images within the brain, is envisioned as a “Rosetta Stone” to crack the code on how brains work.