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Google develops artificial intelligence algorithms that can understand users’ jokes | Technology



Google develops artificial intelligence algorithms that can understand users' jokes |  Technology

After receiving only two jokes, Google says the new algorithms can understand any new joke.

At a recent conference for developers of applications for the Android operating system being developed by technology and Internet service provider Google, the US company unveiled new artificial intelligence algorithms, many of which Cnet reported. .com “website, which specializes in technical issues.

New algorithms developed by Google allow devices to understand users’ jokes, which require more understanding of different meanings of words and human actions.

When a comedian, for example, utters a sarcastic or controversial phrase, the listener simply feels that the tone of voice or body language and other indicators have accumulated meanings to the recipient through human interactions.

But a new method called PALM (the initials of the “Language Paths Model”) allows you to understand the humor of jokes without having to train on AI devices.

After receiving only two jokes, Google says the new algorithms can understand any new joke.

According to a Google report (Reuters), the new algorithm can explain and communicate any new humor.

Understanding jokes and humor is not the ultimate goal of Alphabet Inc. (Google’s parent company), but to enhance the ability of artificial intelligence tools to analyze the nuances of natural language and Google search queries. Can be provided and more complex applications are developed by users faster and more accurately in more languages ​​and populations.

This will increase the ability to communicate with devices by breaking barriers and communicating more seamlessly.

Dong Nguyen, Senior Principal Analyst at Research and Technical Consulting Gardner, said it is difficult to talk to non-experts about what BALM algorithms do, let alone natural language processing; Devices function to some extent as a delivery mechanism for all the wonderful acts that one does.

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Moto G54 Phone Review by Motorola



Moto G54 Phone Review by Motorola

Motorola’s Moto G54 phone is characterized by striking a great balance between price and performance. It’s a mid-range phone, but it comes with powerful features, especially the screen that comes with a refresh rate of up to 120 Hz, and has a higher resolution compared to the previous model. It also has a large battery. It has a capacity of 5,000 mAh and supports higher charging speed compared to the previous model Moto G53.

Here is the review of Moto G54 phone by Motorola to know all the specifications and features of this phone:


The Moto G54 phone comes with a body made of plastic – the back and frame are made of plastic – with a matte back with a smooth texture that is somewhat resistant to fingerprints, and the Motorola logo appears in the middle of the back.

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The smartphone is lightweight and 10 grams lighter than the previous model, weighing only 177 grams.

As for the colors, the Motorola phone comes in four colors: Midnight Blue, Indigo Blue, Mint Green and Glacier Blue.


The Moto G54 phone sports a 6.5-inch IPS LCD screen with a resolution of 2400 x 1080 pixels, a density of 405 pixels per inch and supports a refresh rate of up to 120 Hz.

The Moto G54 offers three refresh rate modes: Auto, 120Hz and 60Hz, and you can adjust these modes manually from Settings.

Performance, battery and charging:

The Moto G54 phone is powered by an octa-core MediaTek Dimensity 7020 processor, manufactured with 6nm technology, with a maximum frequency of 2.2 GHz and an IMG BXM-8-256 graphics processing unit. The phone is available in 8GB of RAM and 256GB of internal storage.

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In terms of performance, the Motorola phone can handle daily tasks at an acceptable pace and you will notice that it delivers good performance without any lag while watching videos on YouTube, browsing social media and playing some games.

The downside is that the phone heats up quickly even without games or heavy applications, but this issue can be fixed with future software updates.

The Moto G54 phone packs a 5,000 mAh battery and supports 15-watt fast charging. The phone will last for a day with moderate usage and you can get a day and a half of battery life with light usage.

Photo Tool:

The Moto G54 phone has a dual-lens rear camera, the primary one with a resolution of 50 megapixels with an f/1.8 lens aperture, and the second one dedicated to precision photography (Macro) It comes with 2 megapixels resolution with f/2.4 lens aperture and these cameras can shoot video in 1080p at 60 frames per second.

The phone also has a single-lens front camera with 16-megapixel resolution and f/2.4 lens aperture and supports video recording at 1080 pixels resolution at 30 frames per second.


Motorola Moto G54 phone is sold at Rs 699 Saudi Riyals.

Here are the full specifications of Motorola Moto G54:


Moto G54

Processor (MediaTek Dimensity 7020) Octa-core and manufactured with 6nm technology.


screen type (IPS LCD) It measures 6.5 inches, has a resolution of 1080 x 2400 pixels and supports a refresh rate of up to 120 Hz.
Internal storage space options

256 GB.


8 GB.
Micro SD card support


Rear camera

Binoculars; The primary has a resolution of 50 megapixels, the second has a resolution of 2 megapixels.
Video shooting

With 1080p resolution at 60 frames per second.

Front camera

A single lens with a resolution of 16 megapixels is capable of shooting video in 1080p at 30 frames per second.
Biometric Insurance Benefits

The fingerprint sensor is built into the side power button.


5G networks,

Bluetooth 5.3 technology,

and Near Field Communication (NFC) technology.

3.5 mm headphones port



Android 13.

5000 mAh, supports 15-watt wired charging technology.


Midnight Blue, Indigo Blue, Mint Green and Glacier Blue.

177 grams.


161.5 x 73.8 x 7.99 mm.

699 Saudi Riyals

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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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