1 . You’ve probably followed a few cute dogs and cats on social media. However, are you aware that Ai-generated pets are also gaining popularity nowadays? They are just as adorable as real dogs and cats but also exhibit human-like characteristics.

Chai Dada, 21, runs an AI-generated dog account called “Shizhuangzhuangya” on Xiaohongshu and has already got more than 10,000 followers. Her AI-generated pet Zhuangzhuang is a fluffy Shiba Inu with a big belly who likes to eat and work out. “Zhuangzhuang is actually a reflection of me,” Chai said. “Its life and mood basically reflect my own.”

To personify the character more, the young content maker places Zhuangzhuang in various daily life scenarios. For instance, responding to the recent increase of “hui nan tian”— the super humid (潮湿的) weather in southern China in spring — Chai posted images of Zhuangzhuangmopping a wet floor, with the caption. “It’s wet everywhere at home”; vividly capturing the mood. In the comments section, many have expressed sympathy (同情), for the poor dog.

“Many scenes may seem ordinary, but when a very lifelike and adorable human-like pet appears in these familiar scenes, it looks interesting,” Chai said. Since Zhuangzhuang closely resembles a human in a dog’s body, many followers have come to believe in its real existence. This has provided Chai with opportunities to monetize by partnering with brands for product advertisements. Aiming to expand her reach, Chai expressed a desire to dive deeper into AI to bring her AI pet to life not just in pictures but also in videos.

She also observed that more and more people like her are becoming AI pet bloggers, which has intensified competition in this industry. To attract more fans, bloggers are constantly learning more AI skills and brainstorming to create more interesting storylines. “I want to develop Zhuangzhuang into an intellectual property and create related cultural and creative products such as dolls and stickers,” said Chai.

3 . Taking a picture of Mars is not easy. Once light bounces off the planet, it can take between 3 to 22 minutes to travel to Earth - so there aren’t truly “live” images of Mars.

But on Friday afternoon, the European Space Agency will offer the closest thing: the first “livestream” of Mars a rare, almost real-time look into space on YouTube, which posts pictures of the planet every 50 seconds as they beam down directly from the camera mounted (安装) on the agency’s Mars Express orbiter (轨道飞行器). We can get a firsthand look at Mars on Friday.

“During Friday’s one-hour livestream, the time between the images being taken from orbit around Mars and appearing on your screen will be about 18 minutes,” James Godfrey, the spacecraft operations manager at the ESA’s mission control center, said in a statement. “That’s 17 minutes for light to travel from Mars to Earth in their current configuration, and about one minute to pass through the wires and servers on the ground. ”

“Normally, we see images from Mars and know that they were taken days before. I’m excited to see Mars as it is now - as close to a Martian(火星人) ‘now’ as we can possibly get!’

In 50-second intervals, the camera shoots across Mars, showing a side of the planet entering night, as well as some clouds billowing out on the comer. The livestream celebrates the 20th anniversary of the Mars Express mission which was launched in 2003 to better understand the planet, as well as search for traces of water.

It’s with this camera, originally meant for engineering purposes, that we’ll get ”live“ images on Friday evening from 18:00 CEST in the first MarsLIVE. What makes this unique, is that it’s a one-hour livestream from Mars   but don’t expect a detailed view of the Red Planet!

4 . Small planetary (行星) bodies is the big focus of space exploration in 2023 and People are eager to solve many of the mysteries about these tiny worlds. In 2023, the launching of two spacecrafts aims to explore some of the solar system’s smaller bodies, in an effort to understand how worlds become suitable habitats for humans to live in.

The first task Jupiter Icy Moons Explorer (JUICE) was launched in April 2023 and is scheduled to land in 2031. This spacecraft from the European Space Agency (ESA) is designed to explore three of Jupiter’s major moons: Europa, Callisto and Ganymede. They are thought to have oceans of liquid water beneath their frozen shells.

“The thing we are most interested in is the liquid oceans and in particular with Ganymede –we don’t know the location, the depth ,the composition of these oceans,” says ESA’s Olivier Witasse, the project scientist. “While JUICE has many goals, the most exciting one is to hunt for life there as water is crucial to life ”.

Due to launch in October 2024 and arrive in 2030, the other spacecraft Psyche from NASA is named after the   asteroid (小行星) it will land. Researchers believe Psyche to be an exposed iron core of a young planet. Studying planetary cores is nearly impossible on actual planets because they are so deep underground, so Psyche could present a unique opportunity.

“The core is always crucial. For the Earth, it creates magnetic field and gives off heat,” says one of the researchers of Psyche, “One of the ways to answer why Earth is habitable is to study how it was built, and Psyche is part of that story. We don’t know what we’re going to find, and if blessed, we’re going to be completely surprised because there was no previous data.”

Habitability (宜居性) in our solar system is still a huge mystery, but the two spacecrafts should bring us one step closer to understanding it.

5 . Russia is launching a new module (舱), Nauka, for the International Space Station (ISS) after over a decade of delays. The ISS comprises modules and equipment from different space agencies including Europe, Japan and Canada. Still, the main part of the station is composed of two main sections: a Russian segment (部分) and a US segment.

The Nauka module is set to lift off from Baikonur Cosmodrome in Kazakhstan on top of a Proton-M rocket at around 1500 GMT, along with a new robotic arm for the station created by the European Space Agency. At 13 metres long and weighing more than 20 tonnes, Nauka, also called the Multipurpose Laboratory Module, will be among the largest in Russia’s half. After launch, Nauka will take eight days to reach the ISS. Once attached, it will act as a new hub for the Russian segment of the station.

“Nauka is a science laboratory, and it also provides a lot of important service systems, including a new toilet and sleeping compartments for the crew,” says Anatoly Zak, editor of RussianSpaceWeb.com. “It’s a step in making the Russian segment more independent (from the US segment).”

The launch of Nauka has been a long time coming, with construction of the module beginning in the 1990s. Technical and supply issues since then have seen development stumble(绊倒). “It’s much more complex than anything the Russian space programme has tried to build in the last few years,” says Zak.

6 . In the Pixar movie Up, a fun cartoon dog called Dug wears a magical collar which can detect and translate his barks and cries into fluent human speech. Humans have always been fascinated by the potential to communicate with the animals. This week, an article in the New York Times documented major efforts from a group of researchers using machine-learning algorithms (算法) to analyze the different calls of whales, chickens, bats, cats, and more.

There are several ways to train AI systems now. Typically, Al systems learn through training with labeled data of human language which can be well supplied by the Internet. But analyzing animal language is different. Scientists have to instruct software programs on what to look for, and how to organize the data. This process requires matching gained vocal (发声的) recordings with the visual social behaviors of animals. A group studying Egyptian fruit bats, for example, also used video cameras to record the bats themselves to provide context for the calls.

Many critics of this approach point out two weaknesses of current AI language models: being unable to truly understand the relationships between words and the objects in the real world, and scientists’ little understanding of animal societies. Al language models for humans rely on a computer mapping out the relationship between words and the contexts they could appear in. But these models have their own weak points, and can sometimes be a black box—researchers know what goes in and comes out, but don’t quite understand how the algorithm is arriving at the conclusion.

Another factor that researchers should take into account is that animal communications might not work at all like human communications. There might be unique elements to animal language due to physiological and behavioral differences.

Making a Translator for animals has been a popular project that’s been in the works for the last decade. Although some software has shown some success in identifying the basic vocabulary of certain animals, it’s still a far cry from understanding the complex animal languages.

9 . Could an app tell if a first date is just not that into you? Engineers at the University of Cincinnati say the technology might not be far off. They trained a computer—using data from reparable technology that measures respiration, heart rates and perspiration to identify the type of conversation two people were having based on their physiological responses alone.

Researchers studied a phenomenon in which people’s heart rates, respiration and other autonomic nervous system responses become synchronized (同步的) when they talk or collaborate. Known as physiological synchrony, this effect is stronger when two people engage deeply in a conversation or cooperate closely on a task. “Physiological synchrony shows up even when people are talking over Zoom, an online chat platform,” said study co-author Vesna Novak.

In experiments with human participants, the computer was able to differentiate four different conversations with as much as 75% accuracy. The study is one of the first of its kind to train artificial intelligence how to recognize aspects of a conversation based on the participants’ physiology alone.

“The computer could tell if you’re a bore,” lead author Chatterjee said. “A modified version of our system could measure the level of interest a person is taking in the conversation, how harmonious the two of you are and how engaged the other person is in the conversation.”

Studies have shown that physiological synchrony can predict how well two people will work together to accomplish a task. The degree of synchrony also correlates with how much empathy a patient perceives in a therapist or the level of engagement students feel with their teachers.

“You could probably use our system to determine which people in an organization work better together in a group and which are naturally opposed,” Chatterjee said.

This aspect of affective computing holds huge potential for providing real-time feedback for educators, therapists or even autistic people, Novak said, “There are a lot of potential applications in this space.”