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The new low-tech transportation method could help scientists in Africa assess if malaria-carrying mosquitoes are resistant to a common insecticide.

Research is needed on how ocean carbon removal methods — such as iron fertilization and direct capture — could impact the environment.

Lab-grown diamonds can form at atmospheric pressure in a liquid of gallium, iron, nickel and silicon.

A method to force fruit flies to move shows the insects’ stepping behavior and holds clues to other animals’ brains and movement.

March 11 marks the fourth anniversary of the World Health Organization’s declaration that the COVID-19 outbreak was a pandemic. COVID-19 hasn’t gone away, but there have been plenty of actions that suggest otherwise.

In May 2023, WHO announced COVID-19 was no longer a public health emergency (SN: 5/5/23). The United States shortly followed suit, which meant testing and treatments were no longer free (SN: 5/4/23). And on March 1 of this year, the U.S. Centers for Disease Control and Prevention loosened their isolation guidelines for people with COVID-19. Now the CDC says infected people can be around others as soon as a day after a fever subsides and symptoms are improving, even though someone is contagious during an infection for six to eight days, on average (SN: 7/25/22).

These outward signs of leaving the pandemic chapter behind neglect to acknowledge how many people cannot (SN: 10/27/21). Nearly 1.2 million people have died in the United States from COVID-19. Close to 9 million adults have long COVID. Nearly 300,000 children have lost one or both parents.

There has been little official recognition in the United States of the profound grief people have experienced and continue to experience. There is no federal monument to honor the dead — mourners have constructed their own memorials. A resolution to commemorate the first Monday of March as “COVID-19 Victims Memorial Day” awaits action by the U.S. Congress.

Many people are coping not just with the deaths of family and friends from COVID-19, but with how the pandemic robbed them of the chance to say goodbye to loved ones and grieve with their family and community. Researchers are studying the extent to which these losses rippled out into society and how the pandemic interrupted the grieving process.

Emily Smith-Greenaway, a demographer at the University of Southern California in Los Angeles, was part of team that estimated that for every one COVID-19 death, there are nine bereaved family members (SN: 4/4/22). Sarah Wagner, a social anthropologist at George Washington University in Washington, D.C., leads a project called Rituals in the Making, which is examining how the pandemic disrupted rituals and the experience of mourning through interviews with mourners and death care workers, among other research methods. Science News spoke with Smith-Greenaway and Wagner about their work. The interviews have been edited for length and clarity.

SN: Why is it important to estimate the number of close family members affected by COVID-19 deaths?

Smith-Greenaway: We typically quantify mortality events in terms of numbers of casualties. By shedding light explicitly on the concentric circles of people surviving each of the deaths, we offer a much more experiential perspective — the burden that a large-scale mortality event imposes on those who are still alive. It also allows us to kind of rescale the true sense of the magnitude of the crisis.

[With the number of deaths today,] our model demonstrates that about 10.5 million people have lost a close relative to COVID, [which includes] grandparents, parents, siblings, spouses and children. We’re not even capturing cousins, aunts, uncles. Think about how many children lost teachers or how many neighbors or friends or coworkers [died]. This is an underestimate when we’re thinking about the many people who are affected by each single death.

SN: What motivated the Rituals in the Making project?

Wagner: We began in May of 2020, and this was this period of heightened pandemic restriction and confinement. We posed what we saw as a fundamental question: How do we mourn when we cannot gather? Particularly in that first year, we were focused on the rituals around funeral, burial and commemorative practice and how they would be impacted and changed by the pandemic. In the last two years, [the project] has included the ways in which misinformation also compounds individual grief and more collective mourning.

A throughline in the research is that this mourning was interrupted and constrained by the conditions of the pandemic itself, but also troubled by politicization of the deaths. And then [there’s] this expectation that we move on, we push past the pandemic, and yet we have not acknowledged the enormity of the tragedy.

SN: Why are rituals and memorials important to grieving?

Wagner: We think about rituals as providing a means to respond to rupture. We are able to come together, gathering to stand before a coffin to say goodbye, or to have a wake, to sit down and have a meal with the bereaved. They are about providing an opportunity to remember and honor that loved one. But they are also about the living — a way of supporting the surviving family members, a way of helping them out of the chasm of that grief.

Memorials [such as a day of remembrance or a monument] are a nation saying, we recognize these lives and we anoint them with a particular meaning. We think about memorials as forms of acknowledgement and a way of making sense of major tragedies or major sacrifices.

In the context of the pandemic, the rituals that are broken and [the lack of] memorials at that national level help us see that the mourners have been left in many ways to take memory matters into their own hands. The responsibility has been pushed onto them at these acute moments of their own grief.

SN: How has the pandemic impacted survivors and the grieving process?

Smith-Greenaway: Societies have demographic memory. There is a generational effect any time we have a mortality crisis. A war or any large-scale mortality event lingers in the population, in the lives and memories of those who survived it.

This pandemic will stay with us for a very long time. [There are] young people who remember losing their grandma, but they couldn’t go see her in the hospital, or remember losing a parent in this sudden way because they brought COVID-19 home from school. So many lives were imprinted at such an early stage of life.

Wagner: Whether we are talking to the bereaved, members of the clergy, health care workers or staff from funeral homes, people describe the isolation. It is incredibly painful for families because they weren’t able to be with their loved one, to be able to touch someone, to hold their hand, to caress a cheek. People were left to wonder, “was my loved one aware? Were they confused? Were they in pain?” [After the death], not being able to have people into one’s home, not being able to go out. That sort of joy of having other people around you in your depths of grief — that was gone.

As the study progressed, [we learned about] the impact political divisiveness had on people’s grief. [Families were asked,] did the person have underlying health issues? What was the person’s vaccination status? It was as if the blame was getting shifted onto the deceased. Then to be confronted with, “this is all just a hoax,” or “[COVID-19 is] nothing worse than a bad cold.” To be a family member, and to struggle for recognition in the face of these conversations that their loved ones’ death and memory is not just dismissed, but in a way feels denied.

SN: How can society better support the need to grieve?

Smith-Greenaway: Bereavement policies are not very generous, as we would expect in America. Sometimes it’s one, two or three days. They’re also very restrictive, where it has to be a particular relation.

Think about kids. I’m a professor at a university. There’s this callous joke that college students just tell you their grandmother died because they don’t want to turn something in. This reflects how we treat bereavement as a society, especially for young people. Kids’ grief can often be misunderstood. It’s perceived to be bad behavior, that they’re acting out. I think we need comprehensive school policies that take better care to recognize how many kids are suffering losses in their lives.

Wagner: We’re enveloped in this silence around pandemic death. I think there’s a willingness to talk about the pandemic losses in other realms, the economic losses or the loss of social connection. Why is there this silence around 1.2 million deaths — the enormity of the tragedy?

If you know someone who has lost a loved one to COVID-19, talk to them about it. Ask them about that loved one. Just being an active part of conversations around memory can be a beautiful act. It can be a restorative act.

Apart from the northward advance of killer bees in the 1980s, nothing has struck as much fear into the hearts of headline writers as the ascent of artificial intelligence.

Ever since the computer Deep Blue defeated world chess champion Garry Kasparov in 1997, humans have faced the prospect that their supremacy over machines is merely temporary. Back then, though, it was easy to show that AI failed miserably in many realms of human expertise, from diagnosing disease to transcribing speech.

But then about a decade ago or so, computer brains — known as neural networks — received an IQ boost from a new approach called deep learning. Suddenly computers approached human ability at identifying images, reading signs and enhancing photographs — not to mention converting speech to text as well as most typists.

Those abilities had their limits. For one thing, even apparently successful deep learning neural networks were easy to trick. A few small stickers strategically placed on a stop sign made an AI computer think the sign said “Speed Limit 80,” for example. And those smart computers needed to be extensively trained on a task by viewing numerous examples of what they should be looking for. So deep learning produced excellent results for narrowly focused jobs but couldn’t adapt that expertise very well to other arenas. You would not (or shouldn’t) have hired it to write a magazine column for you, for instance.

But AI’s latest incarnations have begun to threaten job security not only for writers but also a lot of other professionals.

“Now we’re in a new era of AI,” says computer scientist Melanie Mitchell, an artificial intelligence expert at the Santa Fe Institute in New Mexico. “We’re beyond the deep learning revolution of the 2010s, and we’re now in the era of generative AI of the 2020s.”

Generative AI systems can produce things that had long seemed safely within the province of human creative ability. AI systems can now answer questions with seemingly human linguistic skill and knowledge, write poems and articles and legal briefs, produce publication quality artwork, and even create videos on demand of all sorts of things you might want to describe.

Many of these abilities stem from the development of large language models, abbreviated as LLMs, such as ChatGPT and other similar models. They are large because they are trained on huge amounts of data — essentially, everything on the internet, including digitized copies of countless printed books. Large can also refer to the large number of different kinds of things they can “learn” in their reading — not just words but also word stems, phrases, symbols and mathematical equations.

By identifying patterns in how such linguistic molecules are combined, LLMs can predict in what order words should be assembled to compose sentences or respond to a query. Basically, an LLM calculates probabilities of what word should follow another, something critics have derided as “autocorrect on steroids.”

Even so, LLMs have displayed remarkable abilities — such as composing texts in the style of any given author, solving riddles and deciphering from context whether “bill” refers to an invoice, proposed legislation or a duck.

“These things seem really smart,” Mitchell said this month in Denver at the annual meeting of the American Association for the Advancement of Science.

LLMs’ arrival has induced a techworld version of mass hysteria among some experts in the field who are concerned that run amok, LLMs could raise human unemployment, destroy civilization and put magazine columnists out of business. Yet other experts argue that such fears are overblown, at least for now.

At the heart of the debate is whether LLMs actually understand what they are saying and doing, rather than just seeming to. Some researchers have suggested that LLMs do understand, can reason like people (big deal) or even attain a form of consciousness. But Mitchell and others insist that LLMs do not (yet) really understand the world (at least not in any sort of sense that corresponds to human understanding).

In a new paper posted online at arXiv.org, Mitchell and coauthor Martha Lewis of the University of Bristol in England show that LLMs still do not match humans in the ability to adapt a skill to new circumstances. Consider this letter-string problem: You start with abcd and the next string is abce. If you start with ijkl, what string should come next?

Humans almost always say the second string should end with m. And so do LLMs. They have, after all, been well trained on the English alphabet.

But suppose you pose the problem with a different “counterfactual” alphabet, perhaps the same letters in a different order, such as a u c d e f g h i j k l m n o p q r s t b v w x y z. Or use symbols instead of letters. Humans are still very good at solving letter-string problems. But LLMs usually fail. They are not able to generalize the concepts used on an alphabet they know to another alphabet.

“While humans exhibit high performance on both the original and counterfactual problems, the performance of all GPT models we tested degrades on the counterfactual versions,” Mitchell and Lewis report in their paper.

Other similar tasks also show that LLMs do not possess the ability to perform accurately in situations not encountered in their training. And therefore, Mitchell insists, they do not exhibit what humans would regard as “understanding” of the world.

“Being reliable and doing the right thing in a new situation is, in my mind, the core of what understanding actually means,” Mitchell said at the AAAS meeting.

Human understanding, she says, is based on “concepts” — basically mental models of things like categories, situations and events. Concepts allow people to infer cause and effect and to predict the probable results of different actions — even in circumstances not previously encountered.

“What’s really remarkable about people, I think, is that we can abstract our concepts to new situations via analogy and metaphor,” Mitchell said.

She does not deny that AI might someday reach a similar level of intelligent understanding. But machine understanding may turn out to be different from human understanding. Nobody knows what sort of technology might achieve that understanding and what the nature of such understanding might be.

If it does turn out to be anything like human understanding, it will probably not be based on LLMs.

After all, LLMs learn in the opposite direction from humans. LLMs start out learning language and attempt to abstract concepts. Human babies learn concepts first, and only later acquire the language to describe them.

So LLMs are doing it backward. In other words, perhaps reading the internet might not be the correct strategy for acquiring intelligence, artificial or otherwise.

In the mountains of southern Spain, one type of thistle plant seems to have built-in air conditioning.

The flowers of the thistle Carlina corymbosa are, on average, about 3 degrees Celsius cooler than the surrounding air, ecologist Carlos Herrera reports February 13 in Ecology. The most extreme cooling — sometimes up to 10 degrees C — occurs during the hottest part of the day. This means when the air temperature reaches a sweltering 45° C, the plant’s flowers can remain close to a relatively cool 35° C.

“Those are substantial coolings relative to the air next to it,” says Christopher Still, an ecologist at Oregon State University in Corvallis who was not involved in the work. “It’s a nice, careful study.”

In Spain’s Sierra de Cazorla mountain range, scorching summers leave many plants dead, dried out or dormant. This brown sea is intermittently broken by bursts of yellow, as C. corymbosa improbably peeks its flowers above the vegetation. When Herrera, of the Spanish National Research Council in Sevilla, touched one of the flower heads during the peak of the day’s heat on a recent trek, he found it pleasantly cool.

Herrera was there to study the relationship between the region’s plants and their pollinators. He bent to touch the thistle because he “was checking for the presence of nectar in the flower head,” he says, and then became curious about why the flower felt chilled.

Using an electric thermometer, he measured the temperatures of seven different thistles across two sites and multiple days per flower. He found the flowers consistently cooled down as the day grew hotter.

Many plants cool down by passively allowing water to evaporate through pores, a process called transpiration that is analogous to humans beating the heat by sweating (SN: 2/27/06). Most research has focused on how leaves keep cool, but in many cases, leaves don’t get colder than the surrounding air. When they do, Herrera reports, the difference in temperature is less drastic than seen in the thistle flowers.

There’s probably some truth to the idea that the thistle cools itself down more than leaves, but because flowers and leaves are measured differently, it’s hard to say for sure, Still says.

Because the thistles started cooling down at the hottest part of the day, it’s possible that the plants are actively turning a self-refrigerating mechanism on and off.

The idea that plants might be controlling their internal temperatures took off in the late 1980s, and is known as “limited homeothermy.” However, this is a rare skill among plants, Still says. A 2022 study he led found no evidence that leaves in forest canopies across North and Central America were cooler than the air around them.

Both Herrera and Still think that something about the thistle flower’s shape and structure enables it to cool off so effectively.

Herrera suspects that as water within the thistle evaporates, it takes heat with it, and because of the flower’s physical form, that heat isn’t being replaced by the sun’s warmth. This might allow the plant to cool below the air temperature. Herrera dubs this the “botijo effect,” because “it is the same principle by which porous sweating pitchers” — called botijos in Spanish — “cool themselves in dry, hot air.” This idea needs to be tested, however.

Herrera and Still are both curious to know if being cooler than the surrounding air provides any benefit to the thistle, such as by attracting pollinators trying to escape the oppressive summer heat. Herrera plans to see if other thistles in southern Spain show the same cooling effect and has also mapped out an experiment to probe how limiting the plant’s access to water may influence its cooling ability.

“There’s a lot of value in old-fashioned naturalism,” Still says. “This one study could lead to lots of cool follow-on work.”