A new algorithm capable of inferring goals and plans could help machines better adapt to the imperfect nature of human planning.
In a classic experiment on human social intelligence by psychologists Felix Warneken and Michael Tomasello (see video below), an 18-month old toddler watches a man carry a stack of books towards an unopened cabinet. When the man reaches the cabinet, he clumsily bangs the books against the door of the cabinet several times, then makes a puzzled noise.
Circa 2011 o.o
A green sea slug appears to be part animal, part plant. It’s the first critter discovered to produce the plant pigment chlorophyll.
The sneaky slugs seem to have stolen the genes that enable this skill from algae that they’ve eaten. With their contraband genes, the slugs can carry out photosynthesis — the process plants use to convert sunlight into energy.
Contemporary robots can move quickly. “The motors are fast, and they’re powerful,” says Sabrina Neuman.
Yet in complex situations, like interactions with people, robots often don’t move quickly. “The hang up is what’s going on in the robot’s head,” she adds.
Perceiving stimuli and calculating a response takes a “boatload of computation,” which limits reaction time, says Neuman, who recently graduated with a Ph.D. from the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL). Neuman has found a way to fight this mismatch between a robot’s “mind” and body. The method, called robomorphic computing, uses a robot’s physical layout and intended applications to generate a customized computer chip that minimizes the robot’s response time.
A new method to reason about uncertainty might help artificial intelligence to find safer options faster, for example in self-driving cars, according to a new study to be published shortly in AAAI involving researchers at Radboud University, the University of Austin, the University of California, Berkeley, and the Eindhoven University of Technology.
The researchers have defined a new approach to so-called ‘uncertain partially observable Markov decision processes, or uPOMDPs. In layman’s terms, these are models of the real world that estimate the probability of events. A self-driving car, for example, will face many unknown situations when it starts driving. To validate the artificial intelligence of self-driving cars, extensive calculations are run to analyze how the AI would approach various situations. The researchers argue that with their new approach, these modeling exercises can become far more realistic, and thus allows AI to make better, safer decisions quicker.
A McGill-led research team has identified a new species of praying mantis thanks to imprints of its fossilized wings. It lived in Labrador, in the Canadian Subarctic around 100 million years ago, during the time of the dinosaurs, in the Late Cretaceous period. The researchers believe that the fossils of the new genus and species, Labradormantis guilbaulti, helps to establish evolutionary relationships between previously known species and advances the scientific understanding of the evolution of the most ‘primitive’ modern praying mantises. The unusual find, described in a recently published study in Systematic Entomology, also sheds light on wing evolution among mantises and their relatives more generally.
Digging through mountains of rubble
The research team, which included members from the Muséum national d’Histoire naturelle in Paris, and the Musée de paléontologie et de l’évolution in Montreal, found the specimens during fieldwork at an abandoned iron mine located in Labrador, near Schefferville (Quebec).
A new study shows that humans express a powerful hormone during exercise and that treating mice with the hormone improves physical performance, capacity and fitness. Researchers say the findings present new possibilities for addressing age-related physical decline.
The research, published on Wednesday in Nature Communications, reveals a detailed look at how the mitochondrial genome encodes instructions for regulating physical capacity, performance and metabolism during aging and may be able to increase healthy lifespan.
“Mitochondria are known as the cell’s energy source, but they are also hubs that coordinate and fine-tune metabolism by actively communicating to the rest of the body,” said Changhan David Lee, assistant professor at the USC Leonard Davis School of Gerontology and corresponding author of the study. “As we age, that communication network seems to break down, but our study suggests you can restore that network or rejuvenate an older mouse so it is as fit as a younger one.”
Scientists in Beijing may be one step closer to having the answer to living longer and reversing the effects of ageing. A group of biologists at the Chinese Academy of Sciences say they have developed a world-first new gene therapy and have been running tests on mice. It involved screening around 10000 genes in search of particularly strong drivers of cellular ageing. They identified 100 genes in that pool, but the one that really stood out was the kat7. They then inactivated that kat7 gene in the livers of mice, Professor Qu Jing explained some of their findings: “These mice show after six to eight months, they show overall improved appearance and grip strength and most importantly they have extended lifespan for about 25%.” Kat7 is one of tens of thousands of genes found in the cells of mammals. The scientists also tested the function of the gene in human stem cells, human liver cells and more. So far there have been no side effects of cellular toxicity. Despite this, the method still has a long way to go from being ready for human trials and will require a lot of funding and much more research. “In the end we do hope that we can find a way to delay ageing even by a very minor percentage we want to delay the human ageing in the future.” For now, there’s no final answer to cheating death, but the scientists plan on testing the function of kat7 in other cell types of humans and other organs of mice.
How do stars form?
We know they form from massive structures called molecular clouds, which themselves form from the Interstellar Medium (ISM). But how and why do certain types of stars form? Why, in some situations, does a star like our Sun form, versus a red dwarf or a blue giant?
Nearly every galaxy hosts a monster at its center—a supermassive black hole millions to billions times the size of the Sun. While there’s still much to learn about these objects, many scientists believe they are crucial to the formation and structure of galaxies. What’s more, some of these black holes are particularly active, whipping up stars, dust and gas into glowing accretion disks emitting powerful radiation into the cosmos as they consume matter around them. These quasars are some of the most distant objects that astronomers can see, and there is now a new record for the farthest one ever observed.
A team of scientists, led by former UC Santa Barbara postdoctoral scholar Feige Wang and including Professor Joe Hennawi and current postdoc Riccardo Nanni, announced the discovery of J0313-1806, the most distant quasar discovered to date. Seen as it would have appeared more than 13 billion years ago, this fully formed distant quasar is also the earliest yet discovered, providing astronomers insight into the formation of massive galaxies in the early universe. The team’s findings were released at the January 2021 meeting of the American Astronomical Society and published in Astrophysical Journal Letters.
Quasars are the most energetic objects in the universe. They occur when gas in the superheated accretion disk around a supermassive black hole is inexorably drawn inwards, shedding energy across the electromagnetic spectrum. This releases enormous amounts of electromagnetic radiation, with the most massive examples easily outshining entire galaxies.
