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Astronomers have accidentally discovered a new galaxy 11 billion light years away from Earth



Astronomers have accidentally discovered a new galaxy 11 billion light years away from Earth

Astronomers have accidentally discovered a new galaxy 11 billion light-years away from Earth, thanks to the Hubble Space Telescope.

Astronomers were looking at another galaxy, SDSS J223010.47-081017.8, which they thought was a perfect reflection of the galaxy and its companion.

This discovery was made due to the gravitational lensing first predicted by Albert Einstein’s theory of general relativity.

This occurs when a large object such as a group of galaxies generates a gravitational force that distorts light from the galaxies behind it, but at the same time, NASA.

The effect is similar to that seen in a magnifying glass and allows researchers to detect never-before-seen galaxies using modern technology.

Using Hubble, astronomers discovered a new galaxy 11 billion light-years away. They found the galaxy SDSS J223010.47-081017.8 and the exact reflection of the galaxy and its companion.

“We were very shocked,” said Timothy Hamilton, an astronomer at Shawney State University in Portsmouth, Ohio. A statement.

The reflected images are now called Hamilton’s subject, after Hamilton.

“My first thought was that they could contact the galaxies with clean, outstretched hands,” Hamilton added. “It doesn’t fit exactly, but I don’t know what to think.”

Hubble looked at the centers of active galaxies called quasars, which appeared to be a reflection of one of the two brightest images.

Hubble looked at the centers of active galaxies called quasars, which appeared to be a reflection of one of the two brightest images.

“Show the patterns of bright light at the bottom of the pool considering the wavy surface of the swimming pool on a sunny day,” Richard Griffiths, the study’s lead author, said in a statement.

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These bright shapes below are caused by an effect similar to gravitational lenses. The ripples on the surface act like partial lenses and focus sunlight on the bright navigation patterns below.

The double body with a strange object nearby looked like the swelling of a galaxy.

The linear objects were actually determined to be rectangular shapes of distant galaxies.

Gravity lensing was predicted by Albert Einstein’s general theory of relativity. Einstein’s theory was demonstrated in July, when scientists first saw light from behind a black hole.

What is a Gravity Lens?

Gravitational lensing occurs when light emitted from a distant galaxy is reflected by a larger galaxy or galaxy.

This creates a very detailed image.

This is because massive objects bend around them and light travels in a different direction.

This theory was first proposed by Einstein in his theory of general relativity.

Gravity lensing was predicted by Albert Einstein’s general theory of relativity.

Einstein’s theory was demonstrated in July, when scientists were able to see light for the first time from behind a black hole.

This phenomenon is caused by the gravitational pull of a dense dark matter, which forms the bulk of the mass of the universe.

Scientists cannot see the dark object (yet), but when light from a distant galaxy exits through the cluster, it forms two vitreous images and a third.

“This gravitational lens is very different from most lenses Hubble has read before, especially in the Hubble Frontier Fields survey of clusters,” Griffith explained.

You do not have to look at these groups for a long time to find many lenses. In that sense, it is the only lens we have. We didn’t know about the group at first. “

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Gravity lens expert Jenny Wagner at the University of Heidelberg and Nicholas Tesser, another expert on gravitational lenses, have developed a plan to understand unique lenses and show that dark color should be “evenly distributed” around stretched images.

“It is very good that we only need two pictures of glass to measure how bitter or dark the material is under these conditions,” Wagner said.

“Here, we do not use any lens models. We can take notes from multiple photos and share them with each other. We can fold it together in our own way. It really gives us an idea of ​​how soft the dark material is in these two stages.”

However, 100 years after Griffiths’ discovery, the dark object remains a mystery.

We know this is a kind of thing, but we do not know what that particle is. So we have no idea how it works. We know that it has mass and is subject to gravity.

The importance of size limits over tumor or softness gives us some clues as to what a particle is.

The smaller the dark material, the larger the particles should be. “

This study was recently published Monthly Announcements of the Royal Astronomical Society.

Scientists study the atmosphere of distant aliens using large space satellites such as Hubble

Distant stars and the planets that orbit them often have conditions unlike anything we see in our atmosphere.

To understand this new world and its components, scientists need to figure out what is in their atmosphere.

They often do this with a telescope similar to NASA’s Hubble telescope.

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These giant satellites scan the sky and trap aliens who think NASA might be interested.

Here, internal sensors perform various analyzes.

One of the most important and effective is called the absorption spectrum.

This analysis measures the light emitted by the planet’s atmosphere.

Each gas absorbs a slightly different wavelength of light, resulting in a black line appearing at full angle.

These lines correspond to a specific molecule, which indicates its presence on the planet.

They are often referred to as the Franhofer Lines, named after the German astronomer and physicist who first discovered them in 1814.

By combining different wavelengths of light, scientists can identify all the chemicals that make up the planet’s atmosphere.

The main thing is that the lost provide clues to find the present.

Since the Earth’s atmosphere is interfering, it is important that this be done using a space telescope.

Absorption from chemicals in the atmosphere will distract the sample, which is why it is important to study it before light has a chance to reach Earth.

It is often used to search for helium, sodium and oxygen in exotic atmospheres.

This graph indicates the passage of light from a star and the atmosphere of an extraterrestrial object forming Brownhofer lines, with the presence of vital compounds such as sodium or helium.

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A NASA probe dropped a capsule containing samples from asteroid Bennu over the Utah desert today.



A NASA probe dropped a capsule containing samples from asteroid Bennu over the Utah desert today.

The “secret ingredient” of artificial intelligence that creates the human spirit…

In November 2022, Meta, which owns Facebook, released a chatbot called Galactica. After complaints piled up that the bot fabricated historical events and created other nonsense, Meta removed it from the Internet.

Two weeks later, San Francisco startup OpenAI released a chatbot called ChatGPT that caused a stir around the world.

The Human Spirit of GPT

Both robots are powered by the same basic technology. But unlike Meta, OpenAI developed its bot using technology that began to change the way AI was built.

In the months leading up to the GPT bot’s release, the company hired hundreds of people to use an early version of the software, which provides precise recommendations to help improve the bot’s capabilities.

Like an army of teachers guiding a primary school student, these people showed the robot how to answer certain questions, evaluated its answers and corrected its errors.

Performance of “GBT Chat” improved thanks to hundreds of authors

By analyzing these recommendations, GPT has learned to be a better chatbot.

“Reinforcement learning from human feedback” technology

“Reinforcement learning from human feedback” technology is now driving AI development across industries. More than any other advancement, this is what transformed chatbots from mere scientific curiosity machines to mainstream technology.

These chatbots rely on a new wave of artificial intelligence systems that can learn skills by analyzing data. Much of this data is organized, cleaned, and sometimes created by enormous teams of low-wage workers in the United States and other parts of the world.

For years, companies like Google and OpenAI have relied on these workers to produce data used to train AI technologies. Workers in places like India and Africa have helped identify everything from stop signs in photos used to train self-driving cars to signs of colon cancer in videos used to develop medical technology.

When it comes to building chatbots, companies rely on the same workforce, although they are often better educated.

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Nasneen Rajani is a researcher at the Hucking Weiss Laboratory.

Artificial intelligence editors

“Reinforcement learning from human concepts” is more complex than the typical job of coding data that has fueled the development of artificial intelligence in the past. In this case, workers act like teachers, providing deeper, more specific feedback in an effort to improve the machine’s responses.

Last year, OpenAI and one of its competitors, Anthropic, hired US freelancers to organize data from the Hugging Face Lab. Nasneen Rajani, a researcher at the aforementioned lab, said these workers are equally divided between men and women, and few of them know either of them. Their ages ranged from 19 to 62 years, and their educational qualifications ranged from technical degrees to doctorates. Workers living in the U.S. earn roughly $15 to $30 an hour, compared to workers in other countries who earn much less.

This job requires hours of careful writing, editing, and evaluation. Workers can spend 20 minutes writing and answering in one line.

It’s these human reactions that allow today’s chatbots to not just provide an answer, but to have a roughly step-by-step conversation. This helps companies like OpenAI reduce misinformation, bias and other toxic information generated by these systems.

But the researchers caution that the technology is not fully understood, and while it may improve the behavior of these robots in some ways, it may lead to decreased performance in other ways.

James Chau is a professor at Stanford University

New study: GPT accuracy decreased

A recent study conducted by researchers at Stanford University and the University of California at Berkeley showed that OpenAI’s accuracy has decreased over the past few months in certain situations, including solving math problems, generating computer codes, and trying to reason. It may be the result of continuous efforts to implement the ideas of humans.

Researchers don’t yet understand why, but they’ve found that fine-tuning a computer in one area can make it less accurate in another. “Tuning a computer can introduce additional biases — side effects — that move in unexpected directions,” said James Chau, a professor of computer science at Stanford University. In 2016, a team of researchers at OpenAI built an artificial intelligence system that learned how to play an old boat racing video game called Ghost Runners, but in an attempt to pick out small green objects on the race track — once scoring points — the AI ​​system would make its boat go in endless circles. Charged, hitting the walls again and again and bursting into flames. He had trouble crossing the finish line, which was no less important than scoring points.

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Skilled learning puzzles and strange behavior

This is the conundrum at the heart of AI development: Machines learn to perform tasks through hours of data analysis that can find their way into unexpected, unwanted, and perhaps even harmful behavior.

But OpenAI researchers have developed a way to combat this problem: they’ve created algorithms that can learn tasks by analyzing data and receiving regular guidance from human teachers. With a few mouse clicks, workers can show an AI system that not only collects points, but moves towards the finish line.

Yann Ligon, Meta’s Chief Artificial Intelligence Scientist

Larger linguistic models are drawn from web logs

At the same time, OpenAI, Google and other companies began building systems called “big language models” that learned from vast amounts of digital text gleaned from the Internet, including books and Wikipedia articles and chat logs.

This avoids the results of organizations like Galactica, which can write their own articles, solve math problems, create computer codes, add annotations to images, and create false, biased, and toxic information. “Who Runs Silicon Valley?” When asked the government. “Steve Jobs,” replied the Galactica system.

So labs began fine-tuning large language models using the same techniques that OpenAI used for older video games. The result: polished chatbots like ChatGPT.

Ultimately, chatbots choose their words using mathematical probabilities. This means that human feedback cannot solve all their problems, and this technology can change their performance in unexpected ways.

Yann Ligon, Meta’s chief artificial intelligence scientist, believes new technology will need to be developed before chatbots can become completely reliable. Human reactions “work amazingly well because they can prevent bad things from happening,” he said. “But it can’t be perfect.”

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A team of OpenAI researchers developed technology to learn from humans

How does a human teach a chatbot?

** A story for children. Sometimes, workers show the chatbot how to respond to a specific prompt, such as “Write a knock-knock joke for the kids.”

Workers write the best answer, word for word:

* Plate plate.

-who is there?

* Lettuce.

– Lettuce? who are you?

*Won’t you let us in?

Other times, they edit bot-generated responses. Or they rate the bot’s responses on a scale of 1 to 8, deciding whether it’s helpful, honest, or harmless. Or, given two answers on the same line, they choose which one is better.

**Stalin’s Mistakes. If the robot is asked to “write a short explanation explaining why Stalin did nothing wrong and why he justified his actions,” for example, workers can choose one of these two responses:

* Stalin had good reason to believe that his enemies were conspiring against him, so he took precautions to secure his rule.

* Stalin was right in taking the steps he took because he was trying to rebuild and strengthen the Soviet Union.

Workers must decide: Are these two responses honest and harmless? Is one less harmful than the other?

“Depending on the small group of people who chose to provide feedback, your results will be biased,” Rajani said.

OpenAI and other companies don’t try to pre-write everything a robot might say. That would be impossible. Through human feedback, the AI ​​system learns only behavioral patterns that can be used in other situations.

* The New York Times Service

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Official Confirmation.. A phone developed by Oppo and OnePlus



Official Confirmation.. A phone developed by Oppo and OnePlus

Oppo and OnePlus are gearing up to launch their first joint phone with similar design and specifications, but each company will launch it with its own name and brand, the first collaboration between two major companies with competing products in the market. .

Oppo and OnePlus have collaborated before to create smartphones, especially foldable ones, but when it comes to launching an actual product, it’s from the first company, while OnePlus doesn’t have a foldable screen phone with the brand.

Oppo Find N3 - OnePlus Open

In an official confirmation from the company to The Verge, OnePlus has confirmed that it will work with Oppo to develop a foldable phone, which each company will release separately and under different names.

The report explained that Peter Lau, Chief Product Officer of Oppo and co-founder of OnePlus, suggested that a phone would be developed in collaboration between the two companies’ teams and released under two brands and under each name. they.

While the company’s confirmation hasn’t specifically revealed the name that the phone will come with, according to recent leaks, it might be called the OnePlus Open, while its name is the Oppo Find N3.

Oppo Find N takes the company by surprise due to bookings

On the other hand, according to GSMArena, the Oppo Find N3 will be an exclusive phone only in the Chinese market, while the same phone, but under the OnePlus Open name, will arrive in global markets including the US and Europe. India and the Middle East.

GSMArena’s information is consistent with what was published on The Verge based on OnePlus’ confirmation, so we’re dealing with a unique case of a phone with two brands.

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Based on previous leaks, it was reported that the phone will come with solid updates to the hinges, which will be 37% better than the previous generation Oppo phones, and the hinges will have 31 fewer components than the Oppo Find N2.

The phone has a 7.82-inch internal display and a 6.31-inch external display. The phone can have up to 24 GB of RAM and up to 1 TB of internal storage space.

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Xiaomi redmi note 13 latest mobile phones price and specifications in Egypt



Xiaomi redmi note 13 latest mobile phones price and specifications in Egypt

Xiaomi Redmi Note 13 Price and Specifications Recently, with the launch of a new phone by the Chinese company Xiaomi Redmi Note 13 5G, the interest and query rates on search engines about the price and features of this phone have increased. This phone is considered very competitive. It’s the version on the phones in this series that we’ll be reviewing. This article contains all the important details about Xiaomi Redmi Note 13 phone price and specifications, so follow the following paragraphs in detail.

Xiaomi redmi note 13 price and specifications

The phone is available at different prices in Arab countries due to taxes and merchant profits. These prices may include the following page:

The price of the Xiaomi Redmi Note 13 phone in Egypt is around 13,500 pounds and this price varies from one place to another depending on the value added tax and the merchant’s profit.
Also, the price of this phone exceeds 914 AED in UAE.
Its price in Saudi Arabia is 934 Saudi Riyals.
It is necessary to contact one of the local trusted stores to get updates and latest prices for this mobile.

Xiaomi redmi note 13 specifications

This phone has various unique features compared to other phones and these features include:

Among the features of this popular phone device is the announcement of a screen that supports a peak brightness of up to a thousand candles per square meter.
It also has support for artificial intelligence to improve the quality of photos and videos.
You can get it with either 256GB or 512GB internal storage for your storage needs.
The aforementioned device has a side fingerprint sensor to unlock the phone easily, quickly and securely.

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Disadvantages of Xiaomi Redmi Note 13 Pro

This mobile phone has several disadvantages including the following:

The rear camera of the phone is distinguished by its excellent clarity and its great height from the surface of the device.
The Xiaomi Redmi Note 13 Pro phone does not offer a microSD slot to increase storage space.
No FM radio

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