Our species’ incredible capacity to quickly acquire words from 300 by age 2 to over 1, 000 by age 4 isn’t fully understood. Some cognitive scientists and linguists have theorized that people are born with built-in expectations and logical constraints (约束) that make this possible. Now, however, machine-learning research is showing that preprogrammed assumptions aren’t necessary to swiftly pick up word meanings from minimal data.

A team of scientists has successfully trained a basic artificial intelligence model to match images to words using just 61 hours of naturalistic footage (镜头) and sound-previously collected from a child named Sam in 2013 and 2014. Although it’s a small slice of a child’s life, it was apparently enough to prompt the AI to figure out what certain words mean.   

The findings suggest that language acquisition could be simpler than previously thought. Maybe children “don’t need a custom-built, high-class language-specific mechanism” to efficiently grasp word meanings, says Jessica Sullivan, an associate professor of psychology at Skidmore College. “This is a really beautiful study, ” she says, because it offers evidence that simple information from a child’s worldview is rich enough to kick-start pattern recognition and word comprehension.

The new study also demonstrates that it’s possible for machines to learn similarly to the way that humans do. Large language models are trained on enormous amounts of data that can include billions and sometimes trillions of word combinations. Humans get by on orders of magnitude less information, says the paper’s lead author Wai Keen Vong. With the right type of data, that gap between machine and human learning could narrow dramatically.

Yet additional study is necessary in certain aspects of the new research. For one, the scientists acknowledge that their findings don’t prove how children acquire words. Moreover, the study only focused on recognizing the words for physical objects.

Still, it’s a step toward a deeper understanding of our own mind, which can ultimately help us improve human education, says Eva Portelance, a computational linguistics researcher. She notes that AI research can also bring clarity to long-unanswered questions about ourselves. “We can use these models in a good way, to benefit science and society, ” Portelance adds.

Nocturnal (夜间的) exposure to blue light containing short wavelength emissions (450-500 nm) — the kind of light produced by the screens of many devices raises blood sugar levels and increases sugar intake, according to a study performed on Sudanian grass rats.

“Much of the artificial light we are exposed to comes from LED lights and screens, which emit high levels of blue light,” said Anayanci Masis-Vargas from the Universities of Strasbourg and Amsterdam and his colleagues. According to their study, retinal (网膜的) cells of the eye are sensitive to this blue light and directly convey information to areas of the brain that control appetite.

In the study, the scientists exposed diurnal Sudanian grass rats to nighttime blue light (490 nm) and measured their food consumption and glucose (葡萄糖) tolerance the following day. “In order to better model human light exposure, the rats were diurnal, meaning awake during the day and asleep at night, rather than the typical nocturnal laboratory rats which are awake during nighttime hours,” the researchers explained. They found that after only one hour of nocturnal blue light exposure, glucose tolerance was changed in the rats, a warning sign of pre-diabetes.

To investigate what happens with appetite control and food choice after exposure to blue light at night, in the follow-up study, the rats were given the option to choose among a nutritionally balanced food, water, pig fat, and sugar water. After the exposure to blue light, the study authors observed that the rats preferred sugar water and drank more of it that night than during the nights with no blue light exposure. As the experiment continued, the researchers noticed more exposure to blue light caused rats’ heavier bodies as well.

“Limiting the amount of time that we spend in front of screens at night is, for now, the best measure to protect ourselves from the harmful effects of blue light,” Masis-Vargas said. “In case it is necessary to be exposed to device s at night, I would recommend the night mode features on the devices, which turn the screens more orange and less blue or the use of blue light filtering glasses that are already available in the market.”

Across vast areas of the tropics (热带地区) from Southeast Asia to Africa, forests have been cut down in recent decades, but at least in some areas reforestation efforts have been made to take in carbon (碳).

It remains to be seen, however, whether these newly planted forests will manage to survive in the face of changing climate, which will bring more intense heat, lengthened droughts, and occasional wildfires.

To find out, scientists from the University of Hong Kong decided to run hundreds of computer models to explore various results under different conditions. The key aim of the study was to see if carbon stored in these regrown forests would remain locked up, and they have found this will likely be the case even under the most severe climate conditions.

“Our computer models show in many parts of the tropics reforestation is worth it, because these new forests should be able to survive until the end of the century and continue to store extra carbon from the atmosphere in the process,” explains Jed Kaplan, a professor at the university.

However, the role of newly planted forests as a carbon collector in the tropics will have only a limited effect on climate change, especially because many existing forests in the tropics will struggle in the face of rising temperatures and are already losing their ability to store carbon, “Massive tree planting won’t be enough to avoid climate disaster, but it can play a role. And if done with biodiversity and the people who call these forests home, reforestation can have many benefits,” says Alexander Koch, the other author of the study.

“So far we have only been able to look at carbon, but other aspects such as biodiversity in restored forests are also impacted by climate change. Assessing those impacts will be the next step,” he adds.