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Archive for the ‘information science’ category: Page 111

Oct 28, 2022

When AI “Played” Math, It Cracked an Internet Chokepoint

Posted by in categories: information science, internet, mathematics, robotics/AI

An artificial intelligence system from Google’s sibling company DeepMind stumbled on a new way to solve a foundational math problem at the heart of modern computing, a new study finds. A modification of the company’s game engine AlphaZero (famously used to defeat chess grandmasters and legends in the game of Go) outperformed an algorithm that had not been improved on for more than 50 years, researchers say.

The new research focused on multiplying grids of numbers known as matrices. Matrix multiplication is an operation key to many computational tasks, such as processing images, recognizing speech commands, training neural networks, running simulations to predict the weather, and compressing data for sharing on the Internet.

Oct 27, 2022

Listening to Equation-of-State Changes

Posted by in categories: information science, physics, space

Simulations indicate that postmerger gravitational waves from coalescing neutron stars could allow researchers to hear the phase transitions between exotic states of matter.

Oct 27, 2022

New study shows how to learn the equations of cell migration

Posted by in categories: biotech/medical, information science

When you cut yourself, a mass migration begins inside your body: Skin cells flood by the thousands toward the site of the wound, where they will soon lay down fresh layers of protective tissue.

In a new study, researchers from the University of Colorado Boulder have taken an important step toward unraveling the drivers behind this collective behavior. The team has developed an equation learning technique that might one day help scientists grasp how the body rebuilds skin, and could potentially inspire new therapies to accelerate wound healing.

“Learning the rules for how respond to the proximity and relative motion of other is critical to understanding why cells migrate into a wound,” said David Bortz, professor of applied mathematics at CU Boulder and senior author of the new study.

Oct 27, 2022

How Do You Solve a Problem Like a Proton? You Smash It to Smithereens — Then Build It Back Together With Machine Learning

Posted by in categories: information science, robotics/AI

Berkeley Lab scientists have developed new machine learning algorithms to accelerate the analysis of data collected decades ago by HERA, the world’s most powerful electron-proton collider that ran at the DESY national research center in Germany from 1992 to 2007.

Oct 27, 2022

Scientists Say They’ve Figured Out a Way to Read Thoughts Using an MRI Machine

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

Researchers claim to have built a “decoder” algorithm that can reconstruct what somebody is thinking just by monitoring their brain activity using MRI.

Oct 26, 2022

Advanced alien civilizations haven’t contacted us because of the age of our Sun

Posted by in categories: alien life, information science

Could this be the reason why we haven’t spotted them yet?

Believers in the Drake Equation may have found just the right explanation for why alien civilizations haven’t been spotted by humanity yet. A new study published by U.S.-based researchers states that alien civilizations are likely looking for particular types of stars when trying to establish an intra-galactic base, and our Sun simply does not meet their criterion, Universe Today.


SETI does not make sense

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Oct 25, 2022

Decoder uses fMRI brain scans to reconstruct human thoughts

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

Researchers at the University of Texas at Austin have developed a decoder that uses information from fMRI scans to reconstruct human thoughts. Jerry Tang, Amanda LeBel, Shailee Jain and Alexander Huth have published a paper describing their work on the preprint server bioRxiv.

Prior efforts to create technology that can monitor and decode them to reconstruct a person’s thoughts have all consisted of probes placed in the brains of willing patients. And while such technology has proven useful for research efforts, it is not practical for use in other applications such as helping people who have lost the ability to speak. In this new effort, the researchers have expanded on work from prior studies by applying findings about reading and interpreting brain waves to data obtained from fMRI scans.

Recognizing that attempting to reconstruct brainwaves into individual words using fMRI was impractical, the researchers designed a decoding device that sought to gain an overall understanding of what was going on in the mind rather than a word-for-word decoding. The decoder they built was a that accepted fMRI data and returned paragraphs describing general thoughts. To train their algorithm, the researchers asked two men and one woman to lie in an fMRI machine while they listened to podcasts and recordings of people telling stories.

Oct 24, 2022

Hard Sciences Being Shaken by Machine Learning

Posted by in categories: information science, particle physics, robotics/AI

Latest News Machine Learning Tech news

Particle physicists have taught algorithms to solve previously unsolvable issues.

Oct 22, 2022

I Made a 3D Renderer with just redstone!

Posted by in category: information science

Hey everyone! I upgraded a previous redstone build to support 3D Wireframe Rendering! Thanks everyone who suggested this, it was a lot of fun! bigsmile

!!! WATCH PART 1 HERE!!!
https://youtu.be/vfPGuUDuwmo.

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Oct 22, 2022

Tentacle robot can gently grasp fragile objects

Posted by in categories: entertainment, information science, robotics/AI

If you’ve ever played the claw game at an arcade, you know how hard it is to grab and hold onto objects using robotics grippers. Imagine how much more nerve-wracking that game would be if, instead of plush stuffed animals, you were trying to grab a fragile piece of endangered coral or a priceless artifact from a sunken ship.

Most of today’s robotic grippers rely on embedded sensors, complex feedback loops, or advanced machine learning algorithms, combined with the skill of the operator, to grasp fragile or irregularly shaped objects. But researchers from the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) have demonstrated an easier way.

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