The back of the robot has computers and eight multidirectional thrusters that help it carefully maneuver the sites of fragile sunken ships.

When an operator at the ocean's surface uses controls to direct OceanOneK, the robot's haptic (touch-based) feedback system causes the person to feel the water's resistance as well as the contours of artifacts.

OceanOneK's realistic sight and touch capabilities are enough to make people feel like they're diving down to the depths -- without the dangers or immense underwater pressure a human diver would experience.

Stanford University roboticist Oussama Khatib and his students teamed up with deep-sea archaeologists and began sending the robot on dives in September. The team just finished another underwater expedition in July.

Refer : https://edition.cnn.com
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1. What is the main idea of the article?
     - (CNN)A robot created at Stanford University in California is diving down to shipwrecks and sunken planes in a way that humans can't. Known as OceanOneK, the robot allows its operators to feel like they're underwater explorers, too.
2.What did you learn from the article?
     - Using technology to facilitate human beings is very important. Because robots that do not have feelings to do things that humans can't do. Allows humans to take advantage of robots in abundance.
3.Do you recommend the article to your classmates? Why/Why not?
     - Recommended because in the future, if classmates want to use various technologies, they can take this news as a case example.

Until now the most commonly used dummy has been based on the average male build and weight.

However, women represent about half of all drivers and are more prone to injury in like-for-like accidents.

The dummy that is sometimes used as a proxy for women is a scaled-down version of the male one, roughly the size of a 12-year-old girl.

At 149cm tall (4ft 8ins) and weighing 48kg (7st 5lb), it represents the smallest 5% of women by the standards of the mid-1970s.

However, a team of Swedish engineers has finally developed the first dummy, or to use the more technical term - seat evaluation tool - designed on the body of the average woman.

Their dummy is 162cm (5ft 3ins) tall and weighs 62kg (9st 7lbs), more representative of the female population.
Refer : https://www.bbc.com/news/technology-62877930
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1. What is the main idea of the article?
     - Since the 1970s, crash test dummies - mechanical surrogates of the human body - have been used to determine car safety.
2. What did you learn from the article?
      - Driving safety is very important to avoid accidents. The use of robots to experiment with driving, so they can replace humans while driving is good.
3. Do you recommend the article to your classmates? Why/Why not?
     - Recommended because most of my classmates have cars and they should know if an accident happens when if they are not careful.

But can the system really make your perfect fragrance?

BBC foreign correspondent Anna Holligan tries it out for herself.
Refer : https://www.bbc.com/news/av/technology-63216155
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1. What is the main idea of the article?
     - A company in the Netherlands is using artificial intelligence to produce personalised perfumes.
2. What did you learn from the article?
     - Is our world evolving into where artificial intelligence are now capable of design odors for humans?
3. Do you recommend the article to your classmates? Why/Why not?
     - Not recommended because I think creating perfume from artificial intelligence It's not very interesting.

“The artificial intelligence research community doesn’t necessarily have a complete understanding of what neural networks are doing; they give us good results, but we don’t know how or why,” said Haydn Jones, a researcher in the Advanced Research in Cyber Systems group at Los Alamos. “Our new method does a better job of comparing neural networks, which is a crucial step toward better understanding the mathematics behind AI.”
Refer :
https://scitechdaily.com/new-method-exposes-how-artificial-intelligence-works/
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1. What is the main idea of the article?
     - Artificial IntelligenceDOELos Alamos National Laboratory
2. What did you learn from the article?
     - The brain network of artificial intelligence is very complex and creative. People are developing more and more quality artificial intelligence every day.
3. Do you recommend the article to your classmates? Why/Why not?
     - Recommended I think the data of artificial intelligence will be useful to my classmates someday.

As described in a paper to be published today (October 17) in Nature Machine Intelligence, the new model, called CODE-AE, can screen novel drug compounds to accurately predict efficacy in humans. In tests, it was also able to theoretically identify personalized drugs for over 9,000 patients that could better treat their conditions. Scientists expect the technique to significantly accelerate drug discovery and precision medicine.
refer : https://scitechdaily.com/artificial-intelligence-can-accurately-predict-human-response-to-new-drug-compounds/
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1. What is the main idea of the article?
     - A novel artificial intelligence model could significantly improve the accuracy and reduce the time and cost of the drug development process.
2. What did you learn from the article?
     - Artificial intelligence is a multi-talented robot that can be used to treat people well and accurately.
3. Do you recommend the article to your classmates? Why/Why not?
     - Not recommended, because I don't think this news directly benefits my classmate.

Quantum computers have generated a lot of buzz and for good reason. The futuristic computers are designed to mimic what happens in nature at microscopic scales. This means they have the power to better understand the quantum realm and speed up the discovery of new materials, including pharmaceuticals, environmentally friendly chemicals, and more. However, experts say it is still a decade away — or more — before practical quantum computers are available. What are researchers to do in the meantime?

A new study describes how machine learning tools, run on classical computers, can be used to make predictions about quantum systems and therefore help scientists solve some of the trickiest physics and chemistry problems. While this notion has been proposed before, the new report is the first to mathematically prove that the method works in problems that no traditional algorithms could solve. Led by Caltech, the study was published on September 23 in the journal Science.
Refer : https://scitechdaily.com/conventional-computers-can-learn-to-solve-tricky-quantum-problems-in-physics-and-chemistry/
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1. What is the main idea of the article?
     - Physicists prove that classical machine learning models can improve predictions about quantum materials.
2. What did you learn from the article?
     - The developments in quantum research are more advanced than many people think. Because it leads to new discoveries that will benefit our world greatly in the future.
3. Do you recommend the article to your classmates? Why/Why not?
      - Not recommended, because I don't think this news directly benefits my classmate.