Archive for the ‘information science’ category: Page 182

Jan 20, 2020

How (Relatively) Simple Symmetries Underlie Our Expanding Universe

Posted by in categories: cosmology, information science, mathematics, physics

Isaac Newton and other premodern physicists saw space and time as separate, absolute entities — the rigid backdrops against which we move. On the surface, this made the mathematics behind Newton’s 1687 laws of motion look simple. He defined the relationship between force, mass and acceleration, for example, as $latex \vec{F} = m \vec{a}$.

In contrast, when Albert Einstein revealed that space and time are not absolute but relative, the math seemed to get harder. Force, in relativistic terms, is defined by the equation $latex \vec {F} =\gamma (\vec {v})^{3}m_{0}\,\vec {a} _{\parallel }+\gamma (\vec {v})m_{0}\,\vec {a} _{\perp }$.

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Jan 18, 2020

Not sure how old this video is

Posted by in categories: cybercrime/malcode, information science, robotics/AI, virtual reality

Not sure how old this video is. But, Very impressive if it is able to grab random objects at these speeds; although i suspect it needed a lot of training before.

This handy #roboticarm can be trained to catch practically anything. 🤖 💪

Looking for a job in AI & Machine Learning. Follow us for more updates or visit:

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Jan 16, 2020

AlphaZero learns to rule the quantum world

Posted by in categories: computing, information science, quantum physics

The chess world was amazed when the computer algorithm AlphaZero learned, after just four hours on its own, to beat the best chess programs built on human expertise. Now a research group at Aarhus University in Denmark has used the very same algorithm to control a quantum computer.

All across the world, numerous research groups are attempting to build a quantum . Such a computer would be able to solve certain problems that cannot be solved with current classical computers, even if we combined all these computers in the world into one.

At Aarhus University, researchers share the ambition of building a quantum computer. For this reason, a research group under the direction of Professor Jacob Sherson has just used the computer algorithm AlphaZero to learn to control a quantum system.

Jan 13, 2020

Hall-effect magnetic tracking device for Magnetic Resonance Imaging

Posted by in categories: biotech/medical, computing, information science

Circa 2013

The unique relationship between the coordinates in the bore of a Magnetic Resonance Imaging (MRI) scanner and the magnetic field gradients used for MRI allows building a localization system based on the measurement of these gradients. We have previously presented a miniature 3D Hall probe integrated in a low cost, low voltage 0.35μm CMOS chip from which we were able to measure the magnetic gradient 3D maps of 1.5T and 3T MRI scanners. In this paper, this 3D Hall probe has been integrated in a magnetic tracking device prototype and an algorithm was built to determine the position of the probe. First experimental results show that the probe gives its position with accuracy close to a few millimeters, and that sub-millimeter localization in a one-shot-3ms-measurement should be readily possible. Such a prototype opens the way for the development of MRI compatible real time magnetic tracking systems which could be integrable in surgical tools for MR-guided minimally-invasive surgery.

Jan 5, 2020

Researchers Crack Newton’s Elusive ‘3-Body’ Problem That Has Baffled Scientists for Centuries

Posted by in categories: information science, space

It’s been nearly 350 years since Sir Isaac Newton outlined the laws of motion, claiming “For every action, there is an equal and opposite reaction.” These laws laid the foundation to understand our solar system and, more broadly, to understand the relationship between a body of mass and the forces that act upon it. However, Newton’s groundbreaking work also created a pickle that has baffled scientists for centuries: The Three-Body Problem.

After using the laws of motion to describe how planet Earth orbits the sun, Newton assumed that these laws would help us calculate what would happen if a third celestial body, such as the moon, were added to the mix. However, in reality, three-body equations became much more difficult to solve.

Jan 5, 2020

Artificial intelligence turns brain activity into speech

Posted by in categories: information science, robotics/AI

Fed data from invasive brain recordings, algorithms reconstruct heard and spoken sounds.

Jan 4, 2020

FDA Approves UVA-Developed Artificial Pancreas

Posted by in categories: biotech/medical, information science

The breakthrough system combines a glucose sensor, insulin pump and a smart control algorithm to allow Type 1 diabetes patients to continually regulate blood-sugar levels.

Jan 3, 2020

“We’re working on a cure for the grandest disease on the planet: biological ageing”

Posted by in categories: biotech/medical, information science, life extension

The great Elizabeth Parrish on ageing the most sinister disease on earth… I hate it when words are used to make aging sound like a normal sickness or a great sickness, Such as grandest??? Or most Important disease??? The decomposer disease that Woman-man has called natural aging all these years has been in reality a clandestine plague so complicated yet so easily seen by the naked eye if certain scholars-textbooks do not get in the way…

Aging is The Eukaryotic Cellular pandemic plague AEWR has named the Senesonic-Sensonic plague. A disease that causes all of our cells to age nearly at the same rate causing our cells to have to regenerate the day long or the body drops.

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Jan 1, 2020

Google AI Beats Doctors at Breast Cancer Detection—Sometimes

Posted by in categories: biotech/medical, health, information science, robotics/AI

Google’s health research unit said it has developed an artificial-intelligence system that can match or outperform radiologists at detecting breast cancer, according to new research. But doctors still beat the machines in some cases.

The model, developed by an international team of researchers, caught cancers that were originally missed and reduced false-positive cancer flags for patients who didn’t actually have cancer, according to a paper published on Wednesday in the journal Nature. Data from thousands of mammograms from women in the U.K. and the U.S. was used to train the AI system.

But the algorithm isn’t yet ready for clinical use, the researchers said.

Jan 1, 2020

How Google AI Is Improving Mammograms

Posted by in categories: biotech/medical, health, information science, robotics/AI

In a study published Jan. 1 in Nature, researchers from Google Health, and from universities in the U.S. and U.K., report on an AI model that reads mammograms with fewer false positives and false negatives than human experts. The algorithm, based on mammograms taken from more than 76,000 women in the U.K. and more than 15,000 in the U.S., reduced false positive rates by nearly 6% in the U.S., where women are screened every one to two years, and by 1.2% in the U.K., where women are screened every three years. The AI model also lowered false negatives by more than 9% in the U.S. and by nearly 3% in the U.K.

Working with medical experts, engineers at Google Health have created an AI model that lowers false positive and false negative rates for mammogram breast cancer screening.