Lighting has come a long way since Tom Edison lit his first incandescent bulb (白炽灯泡) in the 1880s. LED bulbs are popping up everywhere now, on planes, car headlights, in your phone. And engineers are exploring more ways to use LEDs—everything from wireless data streaming to secure communication systems and in-flight networking.

Engineer Harald Haas, co-founder of pureLiFi, explains how LEDs can be used to transmit information, “LEDs have the property that we can change the light that comes out of an LED very, very quickly. That change in the brightness is what we exploit in order to encode data extremely fast, so that a receiver will then see these changes in the light intensity in a way a human eye would not be able to detect. Then we have algorithms (算法) to recover these changes and get back the data stream.”

There are many advantages to using LEDs to transmit information. For one thing, LEDs can communicate much faster than WiFi. What’s more, the visible light spectrum (频谱) is about ten thousand times larger than the radio spectrum. This would allow communication systems to not only use a spectrum that’s already been set up, but vast amount of free spectrum, which is in cars, in our LED lights at home, in streetlights and so on. “It’s ubiquitous. It’s already there,” Haas says.

LiFi would also be more secure than WiFi. Because light can’t go through walls, people would not be able to log on to LiFi networks in the same way that they’re able to log on to and eavesdrop on (窃听) ongoing WiFi communications. Haas argues that LiFi would also be available in places where communication is typically difficult when we can’t use radio.

One interesting application could be to use car headlights to communicate with other drivers on the road. “We can use these LEDs to transmit data from car to car. Normally you see the car in front of you, but if you were able to relay high-definition video from, say, three cars in front of you, you could see earlier what’s happening. This is a way we can enhance safety on our roads,” Haas says.

Haas and his coworkers foresee the LED light industry changing rapidly in the near future to include additional features. “That is where LiFi plays a key role. From home sensing of interior, you’d find out if people have fallen down and the way you would navigate (导航) indoors. So many, many more applications would be possible with light,” Haas says.

Plants need sunlight for photosynthesis (光合作用), the process of absorbing energy from light to create their own food from carbon dioxide and water. That’s why plants grow and thrive in the warmer months when there is more daylight and are dormant in the colder months.

But this process isn’t particularly efficient and only one percent of the energy contained in sunlight actually ends up in the plant, according to a news release from the University of California, Riverside. Now scientists at the university have found a way to bypass the need for natural photosynthesis and to create food by using artificial photosynthesis. This allows plants to grow in complete darkness. “With our approach we sought to identify a new way of producing food that could break through the limits normally imposed by biological photosynthesis,” corresponding author Robert Jinkerson, a UCR assistant professor of chemical and environmental engineering said in the news release.

The researchers devoted to artificial photosynthesis used a two-step electrocatalytic (电催化) process to convent CO2, water, and electricity into acetate (醋酸盐) — the main ingredient of vinegar — that the plant organisms consumed to grow. The researchers adjusted the electrolyzer, a device that uses electricity to support the growth of food producing organisms. to come up with the highest levels of acetate ever produced by this method.

The new artificial photosynthesis method could be up to 18 times more efficient than sunlight. Experiments showed that a large range of food producing organisms could be grown using this acetate. “We were able to grow food producing organisms without any contributions from biological photosynthesis,” said Elizabeth Hann, a doctoral candidate in the Jinkerson lab and co-lead author of the study. “This technology is a more efficient method of turning solar energy into food, as compared to food production that relics on biological photosynthesis,” she said.

By eliminating the need for sunlight, he potential of this method to increase food supply in regions with less - than ideal growing conditions is almost endless, according to New Atlas.

Food will be able to be grown almost anywhere, including in space and on other planets. “Imagine someday giant vessels growing tomato plants in the dark and on Mars — how much easier would that be for future Martians?” co-author Martha Orozco-Cárdenas, director of the UCR Plant Transformation Research Center said.

While this may be years off, the potential to grow food using artificial photosynthesis has great value in feeding a hungry place where the population is growing and arable land shrinking. This new method increases the efficiency of food production using less land and minimizes the environmental impact on the planet.

Can artificial intelligence uncover a liar? It sounds like science fiction, but such an AI system is possible. The question is: How accurate can it be? Rada Mihalcea, a professor of computer science and engineering at the University of Michigan, has worked on deception detection for about a decade. This is how they constructed one AI deception detector, and how it works.

The first thing that researchers working on artificial intelligence and machine learning need is data. In the case of the work that Mlhalcea did, they began with videos from actual court cases. For example, a defendant speaking in a trial in which they were found guilty could provide an example of deceit; they also used testimony from witnesses as either example of truthful or deceitful statements. Altogether, they used 121 video clips and the corresponding transcripts of what they said—about half represented deceptive statements, and half truthful. It was this data that they used to build machine learning classifiers that ultimately had between a 60 to 75 percent accuracy rate.

One thing the system noticed is the use of pronouns—people who are lying would tend to less often use the word ‘I’ or ‘we’, Mihalcea explains. “Instead, people who are lying would more often use ‘you,’ ‘yours,’ ‘he,’ ‘they,’ and ‘she.’” That’s not the only linguistic signal: someone telling a lie would use “stronger words” that “reflect certainty,” she says. Examples of those types of words are “absolutely,” and “very,” while interestingly, people telling the truth were more likely to use words such as “maybe” or “probably.” “I think people who are deceptive would try to make up for the lie they are putting forward,” she says, “and so they try to seem more certain of themselves.” As for gestures, she points out that someone being deceitful would more likely look directly into the eyes of the person questioning them. They also tended to use both hands when gesturing. Instead of just one—also, she suspects, as part of trying to be convincing.

However, Mlhalcea’s work is “far from perfection,” she concedes. “As a researcher, we are excited we were able to get to 75 percent accuracy.” But looked at another way, that’s an error rate of one in four. Ultimately, she sees technology like this as being assistive for people—it could, for example, indicate that it noticed something “unusual” in a speaker’s statement, and then perhaps have a person “investigate more.”