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Archive for the ‘information science’ category: Page 173

Apr 21, 2020

Introduction to Genetic Algorithm and Python Implementation For Function Optimization

Posted by in categories: genetics, information science

Here, in this article, I will try to give you an idea of how a genetic algorithm works and we will implement the genetic algorithm for function optimization. So, let’s start.

Apr 21, 2020

Military artificial intelligence can be easily and dangerously fooled

Posted by in categories: information science, military, robotics/AI, sustainability

Last March, Chinese researchers announced an ingenious and potentially devastating attack against one of America’s most prized technological assets—a Tesla electric car.

The team, from the security lab of the Chinese tech giant Tencent, demonstrated several ways to fool the AI algorithms on Tesla’s car. By subtly altering the data fed to the car’s sensors, the researchers were able to bamboozle and bewilder the artificial intelligence that runs the vehicle.

Apr 21, 2020

New AI algorithm brings us closer than ever to controlling machines with our minds

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

Researchers from Carnegie Mellon and the University of Pittsburgh today published research showing how they’d solved a frustrating problem for people who use a brain-computer interface (BCI) to control prosthetic devices with their thoughts.

While the research itself is interesting – they created an algorithm that keeps the devices from constantly needing to be re-calibrated to handle the human brain’s fluctuating neuronal activity – the real takeaway here is how close we are to a universal BCI.

BCIs have been around for decades in one form or another, but they’re costly to maintain and difficult to keep working properly. Currently they only make sense for narrow use – specifically, in the case of those who’ve lost limbs. Because they’re already used to using their brain to control an appendage, it’s easier for scientists and researchers to harness those brainwaves to control prosthetic devices.

Apr 20, 2020

Scientists use olive oil to discover new universal physics law

Posted by in categories: information science, particle physics

The research team, which also included Rodriguez’w PhD students Zou Geng and Kevin Peters, increased and decreased the distances between the mirrors at different speeds and noted how light transmitted through the cavity was affected. They saw that the direction in which the mirrors moved influenced how much light got through the cavity, finding that “the transmission of light through the cavity is non-linear.” This behavior of light, called hysteresis, is present in the phase transitions of boiling water or magnetic materials.

The scientists also increased the speed with which the oil-filled cavity opened and closed, observing that under such conditions the hysteresis was not always present. This allowed them to extrapolate a universal law. “The equations that describe how light behaves in our oil-filled cavity are similar to those describing collections of atoms, superconductors and even high energy physics,” elaborated Rodriguez, adding: “Therefore, the universal behavior we discovered is likely to be observed in such systems as well.”

Apr 19, 2020

How AI Is Expanding The Applications Of Robo Advisory

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

For the last couple of years, Artificial Intelligence (AI) has been changing many fields and increasing efficiency by using improved datasets. One of those areas where AI has accelerated evolution is the robo-advisory, which is a field having extensive financial big data to analyze.

Robo-advisors are the systems that use algorithms to automatically perform investment decisions or tasks which are mostly done by human advisors. “Robo advisors are a potential solution to the complexities of financial decision making,” said Jill E. Fisch, a law professor at the University of Pennsylvania at a conference of Pension Research Council.

In the main scheme, robo-advisors are merging customers’ information such as their financial goals, risk tolerances, timeframes, with the right asset allocation that qualifies customer’s needs. While making this merge, they use many algorithms including machine learning models to create the best fit for the customer. In the process of timeframe, they take lots of actions as well such as rebalancing the portfolio or performing tax-loss harvesting. This automatically increases efficiency while taking decisions at the right time for the portfolio.

Apr 16, 2020

New Earth-sized planet found in habitable sweet-spot orbit around a distant star

Posted by in categories: alien life, information science

Researchers have discovered a new Earth-sized planet orbiting a star outside our solar system. The planet, called Kepler-1649c, is only around 1.06 times larger than Earth, making it very similar to our own planet in terms of physical dimensions. It’s also quite close to its star, orbiting at a distance that means it gets around 75% of the light we do from the Sun.

The planet’s star is a red dwarf, which is more prone to the kind of flares that might make it difficult for life to have evolved on its rocky satellite’s surface, unlike here in our own neighborhood. It orbits so closely to its star, too, that one year is just 19.5 of our days — but the star puts out significantly less heat than the Sun, so that’s actually right in the proper region to allow for the presence of liquid water.

Kepler-1649c was found by scientists digging into existing observations gathered by the Kepler space telescope before its retirement from operational status in 2018. An algorithm that was developed to go through the troves of data collected by the telescope and identify potential planets for further study failed to properly ID this one, but researchers noticed it when reviewing the information.

Apr 15, 2020

Artificial intelligence that can evolve on its own is being tested by Google scientists

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

O,.o singularity here we come :3.


“It’s extremely exciting to see if it can turn up any algorithms that we haven’t even thought of yet, the impact of which to our daily lives may be enormous,” one computer expert told Newsweek.

Continue reading “Artificial intelligence that can evolve on its own is being tested by Google scientists” »

Apr 14, 2020

Researchers design intelligent microsystem for faster, more sustainable industrial chemistry

Posted by in categories: chemistry, engineering, information science, robotics/AI, sustainability

The synthesis of plastic precursors, such as polymers, involves specialized catalysts. However, the traditional batch-based method of finding and screening the right ones for a given result consumes liters of solvent, generates large quantities of chemical waste, and is an expensive, time-consuming process involving multiple trials.

Ryan Hartman, professor of chemical and at the NYU Tandon School of Engineering, and his laboratory developed a lab-based “intelligent microsystem” employing , for modeling that shows promise for eliminating this costly process and minimizing environmental harm.

In their research, “Combining automated microfluidic experimentation with machine learning for efficient polymerization design,” published in Nature Machine Intelligence, the collaborators, including doctoral student Benjamin Rizkin, employed a custom-designed, rapidly prototyped microreactor in conjunction with automation and in situ infrared thermography to study exothermic (heat generating) polymerization—reactions that are notoriously difficult to control when limited experimental kinetic data are available. By pairing efficient microfluidic technology with machine learning algorithms to obtain high-fidelity datasets based on minimal iterations, they were able to reduce chemical waste by two orders of magnitude and catalytic discovery from weeks to hours.

Apr 13, 2020

Using artificial intelligence to search for new exotic particles

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

Nowadays, artificial neural networks have an impact on many areas of our day-to-day lives. They are used for a wide variety of complex tasks, such as driving cars, performing speech recognition (for example, Siri, Cortana, Alexa), suggesting shopping items and trends, or improving visual effects in movies (e.g., animated characters such as Thanos from the movie Infinity War by Marvel).

Traditionally, algorithms are handcrafted to solve complex tasks. This requires experts to spend a significant amount of time to identify the optimal strategies for various situations. Artificial neural networks — inspired by interconnected neurons in the brain — can automatically learn from data a close-to-optimal solution for the given objective. Often, the automated learning or “training” required to obtain these solutions is “supervised” through the use of supplementary information provided by an expert. Other approaches are “unsupervised” and can identify patterns in the data. The mathematical theory behind artificial neural networks has evolved over several decades, yet only recently have we developed our understanding of how to train them efficiently. The required calculations are very similar to those performed by standard video graphics cards (that contain a graphics processing unit or GPU) when rendering three-dimensional scenes in video games.

Apr 12, 2020

For First Time in History, AI Learns to Translate Silent Human Brain Activity into Text for Locked-In Syndrome Patients

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

Neuroscientists have just created an artificially intelligent algorithm that detects human brain activity and translates it into English sentences—and they said it was the first time such translations could be done on a 1:1 speed with natural human speech; faster-than-light.