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Sound and light waves can be used in silicon chips for more efficient computers

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A new step in the context of increasingly efficient silicon-based computers seems to have been taken by researcher Avi Zadok of the Faculty of Engineering Sciences at Bar-Ilan University. One of the biggest problems with modern computers whose functions have been extended to include photonics is that optical signals, like electrical signals, move too fast.

Sometimes slower motion may be better, as explained in the press release: “Important signal processing activities, such as accurate selection of frequency channels, require data to be delayed at timescales of tens of nano-seconds. Given the high speed of light, optical waves spread over many meters at these time intervals. It is not possible to accept these path lengths in a silicon chip. It is not realistic. In this race, fasting does not necessarily win.”

One way of overcoming a similar problem is to use acoustic waves: the signal in question can be converted from the electrical domain into an acoustic wave. Because the speed of sound is lower, the new converted signal can have the necessary delay at tens of micrometers instead of meters. After propagation, the same delayed signal can then be converted back into an electrical signal.

This is what Zadok is trying to do with photonic computers, especially a system that combines light and sound in standard silicon, even if the same concept can be applied to any type of substrate, not just silicon.

Zadok himself adds in the press release: “Acoustics is a missing dimension in silicon chips because the acoustics can perform specific tasks that are difficult to perform only with electronics and optics. For the first time, we have added this dimension to the standard silicon photonics platform. The concept combines the communication and bandwidth of light with the selective processing of sound waves.”

This progress can be useful in applications related to 5G.


See also:

https://www.nature.com/articles/s41467-019-12157-x

Image source:

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Janice Walker

Janice Walker is a biologist (having graduated from Prescott College in 2013) and an experienced writer. She currently works as a pharmacist, contributing research and content to Hplex Science News during her nights and weekends. During her time at Prescott College she was an active contributor to her student journal and hopes to grow Hplex Science News up as a well established, popular science blog.
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Science

Artificial intelligence passes the third grade scientific test for the first time

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A software based on artificial intelligence has passed an eighth American school test (comparable to the third year of high school), according to an article in the New York Times. It is the first time that artificial intelligence has passed a test of this level.

It’s been a few years since hundreds of computer scientists entered a competition to create artificial intelligence that can pass a test of this level, but the only one to pass seems to have been the Allen Institute for Artificial Intelligence.

In fact, this Seattle Institute has created a new artificial intelligence system that seems to have passed the scientific test by correctly answering more than 90% of the questions. The software, called Aristo, is designed to mimic the logic of human decision-making.

And it is perhaps precisely for this reason that he managed to overcome not only the questions that made a “simple” information search possible (something that even Google can do now if the questions are very simple), but also questions that needed a real reasoning, essentially the classic and simple “problems” that primary or secondary school students have to solve, issues that, however, require the use of logic.

The standardized scientific tests used in schools are increasingly being used to assess the level of artificial intelligence and the manufacturers themselves see them as excellent benchmarks for understanding the progress and level their software achieves. These types of tests are considered more important than the classic tests based on games such as chess or backgammon.

The latter may, in fact, be governed by the rules to learn, but a scientific test, a series of questions that also includes the use of logic, is more difficult to overcome. Jingjing Liu, one of the Microsoft researchers who has also worked on various Allen Institute initiatives based on artificial intelligence, seems to be cautious and openly declares that it is not yet possible to compare such technology with real human students of the third degree: their ability to reason, at least for the moment, is still superior.

However, the progress that has been made with Aristo can already be used in the short term in a range of different services, ranging from the answers that an Internet search engine can provide to the various tasks that a digital assistant can perform. However, the progress made in artificial intelligence, especially in neural networks that can understand the natural language thanks to models built on the basis of huge amounts of data, does not seem to deny it.


See also:

https://allenai.org/aristo/

Image source:

https://miro.medium.com/max/4000/1*DcHlT-ImdvYaJZL7LWDUUA.jpeg

Janice Walker

Janice Walker is a biologist (having graduated from Prescott College in 2013) and an experienced writer. She currently works as a pharmacist, contributing research and content to Hplex Science News during her nights and weekends. During her time at Prescott College she was an active contributor to her student journal and hopes to grow Hplex Science News up as a well established, popular science blog.
---
602-317-6122
[email protected]
Janice Walker
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Scientists discover new geometric models that are more resistant to shocks and explosions

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A method to make materials more resistant to vibration and shock, for example during earthquakes, was developed by a group of engineers at the University of California in San Diego.

Professor Veronica Eliasson and her colleagues have discovered during several experiments that have seen the use of a particular device that generates powerful explosions in the laboratory, a particular structural conformation that can reduce the energy of shock waves and therefore to reduce the total damage.

In particular, they discovered that certain grooves in the geometric models used reduced the impact of the so-called “reflected shock wave.” “This research can also be used in military and civil applications to design materials and buildings to better withstand high-intensity explosions,” says Christina Scafidi, one of the researchers working on the project.

Another researcher involved in the research, aerospace engineer Alexander Ivanov, says in the press release: “The coal industry has had many fatal accidents and we believe this research is a valid reason to protect workers from eruptions that can easily spread throughout an entire coal mine. If the entire coal wall could be covered with these solid geometric obstacles, this would be an economical way to protect all miners. ”

Janice Walker

Janice Walker is a biologist (having graduated from Prescott College in 2013) and an experienced writer. She currently works as a pharmacist, contributing research and content to Hplex Science News during her nights and weekends. During her time at Prescott College she was an active contributor to her student journal and hopes to grow Hplex Science News up as a well established, popular science blog.
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602-317-6122
[email protected]
Janice Walker
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Algorithm recognizes bullies and molesters on Twitter with an accuracy of 90%

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A new algorithm that recognizes bullies and online attackers has been developed by a group of researchers from the University of Binghamton. Specifically, the researchers developed an algorithm that, with an accuracy of 90% according to the press release, recognizes the bullies on Twitter.

More and more IT and Artificial Intelligence laboratories and researchers are spending their time trying to develop methods for automatically recognizing bullying and aggression on the internet, in order, quite clearly, to benefit even large companies, they keep the social networks that, at least for the time being, mostly use human moderators.

Jeremy Blackburn, an American university computer scientist, is trying to bridge this gap by analyzing the behavioral patterns of “bullies” on Twitter and comparing them to those of “normal” users. It is precisely for this reason that the researcher, together with his colleagues, has created special crawlers to collect data from Twitter faster and more efficiently.

He then relied on natural language processing algorithms and other tools already available for social network analysis and was able to develop an algorithm that automatically classifies two models of offensive behavior online: cyberbullying and cyber aggression.

The accuracy of the algorithm would be 90%. The algorithm is able to identify tricky behavior, for example users who launch threats make racist comments to other users.


See also:

https://www.researchgate.net/publication/334624617_Detecting_Cyberbullying_and_Cyberaggression_in_Social_Media

Image source:

https://marketingland.com/wp-content/ml-loads/2014/07/twitter-logo-small-1920.png

Janice Walker

Janice Walker is a biologist (having graduated from Prescott College in 2013) and an experienced writer. She currently works as a pharmacist, contributing research and content to Hplex Science News during her nights and weekends. During her time at Prescott College she was an active contributor to her student journal and hopes to grow Hplex Science News up as a well established, popular science blog.
---
602-317-6122
[email protected]
Janice Walker
Continue Reading
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