Archive for the ‘information science’ category: Page 2

Oct 29, 2022

In Defence of Strong AI: Semantics from Syntax

Posted by in categories: information science, robotics/AI

Next, you seem to assume that when I catch a ball, my mind solves equations unconsciously, brining together inertia, gravity, air resistance to calculate my response. You may be right, but I don’t think most neuroscientist agree with you. That’s another computationalist prejudice. Rather than solving equations, my nervous system uses experience and extrapolation through repeated trial and improvement to hone a skill in extrapolating paths; no equations involved. As I say, I could be wrong, it’s an empirical question. But as far as I know, the balance of evidence and theory supports my interpretation.

The meaning of semantics is not just that it means something, but that it can be used to make statements about the world, beyond the formal system used to express that meaning. That, too, is definitional.

Your main argument seems like a really desperate move to sustain the computationalist faith that you assert at the beginning in the face of huge, perhaps insuperable difficulties.

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Oct 28, 2022

Meta what?

Posted by in categories: augmented reality, big data, computing, evolution, futurism, information science, innovation, internet, life extension, machine learning, Mark Zuckerberg, posthumanism, singularity, virtual reality

When in 2015, Eileen Brown looked at the ETER9 Project (crazy for many, visionary for few) and wrote an interesting article for ZDNET with the title “New social network ETER9 brings AI to your interactions”, it ensured a worldwide projection of something the world was not expecting.

Someone, in a lost world (outside the United States), was risking, with everything he had in his possession (very little or less than nothing), a vision worthy of the American dream. At that time, Facebook was already beginning to annoy the cleaner minds that were looking for a difference and a more innovative world.

Today, after that test bench, we see that Facebook (Meta or whatever) is nothing but an illusion, or, I dare say, a big disappointment. No, no, no! I am not now bad-mouthing Facebook just because I have a project in hand that is seen as a potential competitor.

I was even a big fan of the “original” Facebook; but then I realized, it took me a few years, that Mark Zuckerberg is nothing more than a simple kid, now a man, who against everything and everyone, gave in to whims. Of him, initially, and now, perforce, of what his big investors, deluded by himself, of what his “metaverse” would be.

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Oct 28, 2022

Scientist develops an open-source algorithm for selecting a dictionary of a neurointerface

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

Associate Professor of the Department of Information Technologies and Computer Sciences at MISIS University, Ph.D., mathematician and doctor Alexandra Bernadotte has developed algorithms that significantly increase the accuracy of recognition of mental commands by robotic devices. The result is achieved by optimizing the selection of a dictionary. Algorithms implemented in robotic devices can be used to transmit information through noisy communication channels. The results have been published in the peer-reviewed international scientific journal Mathematics.

The task of improving the object (audio, video or electromagnetic signals) classification accuracy, when compiling so-called “dictionaries” of devices is faced by developers of different systems aimed to improve the quality of human life.

The simplest example is a voice assistant. Audio or video transmission devices for remote control of an object in the line-of-sight zone use a limited set of commands. At the same time, it is important that the commands classifier based on the accurately understands and does not confuse the commands included in the device dictionary. It also means that the recognition accuracy should not fall below a certain value in the presence of extraneous noise.

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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.

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