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Among the smartest animals on Earth, octopuses are unique for being utterly weird in their evolutionary path to developing those smarts. Philosopher Peter Godfrey-Smith has called the octopus the closest thing to an alien that we might encounter on Earth, and their bizarre anatomy speaks to this: An octopus’ mind isn’t concentrated in its head but spread throughout its body. Their tentacles are packed with neurons that endow each one with a hyperaware sense of touch, as well as the ability to smell and taste. Marine biologists have remarked that each tentacle sometimes seems like it has a mind of its own. Every octopus is a tactile thinker, constantly manipulating its surroundings with a body so soft it almost seems liquid. 

All of these things are surprising, at least in theory, because scientists have learned to associate intelligence with vertebrates and a tendency to socialize. Octopuses are either asocial or partially social — and all of them are invertebrates. This raises an obvious question: How did octopuses become so smart?

Scientists know surprisingly little about this subject, as a great deal of the research on octopus neuroanatomy up to this point has focused on one species, the European common octopus (Octopus vulgaris) — which has about as many neurons in its body as a dog. Thanks to the scientists behind a new study in the scientific journal Current Biology, we now know more about the neural wiring of four very different types of octopuses (or, in one case, octopus-like animals): the vampire squid (Vampyroteuthis infernalis), which dwells in the deep sea and is technically neither an octopus nor a squid; the blue-lined octopus (Hapalochlaena fasciata), a venomous creature that keeps to itself while roaming the ocean at night; and “two diurnal reef dwellers,” Abdopus capricornicus and Octopus cyanea (also known as the day octopus). 

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Octopus (Getty Images/sko)

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The Beresheet crash-landed on Earth’s Moon in 2019. Part of the ill-fated Israeli lunar lander’s payload was a bunch of tardigrades, or “water bears.” These organisms are under a millimeter long and can survive extreme cold and radiation by expelling nearly all their moisture before entering a nearly death-like state. The Beresheet tardigrades may have survived the crash and could, potentially, be resurrected by being reintroduced to water.

The tardigrades—sometimes called moss piglets—are safely asleep and probably not running amok on the surface of the Moon. But, in general, scientists, governments, and space agencies around the world agree that bringing Earth’s life to extraterrestrial locales, or vice versa, isn’t great.

A new paper builds on the growing body of literature about this cosmic no-no and draws on the burgeoning field of invasion science—the research of how, on Earth, non-native species spread to and alter new locations. The zebra mussel’s spread across North America through its ability to outcompete native species is a classic example.

Right now, when it comes to other celestial bodies, humans are more likely to find or introduce microorganisms rather than filter-feeders (or anything big). “The ecosystem concept is a very general concept. It doesn’t just apply to lakes or forests,” Anthony Ricciardi—a McGill University biologist and one of the authors of the paper—told Ars.

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Europa could harbor complex life, and we’ll have to take care to avoid any cross-contamination.

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Electric vehicles have the potential to substantially reduce carbon emissions, but car companies are running out of materials to make batteries. One crucial component, nickel, is projected to cause supply shortages as early as the end of this year. Scientists recently discovered four new materials that could potentially help—and what may be even more intriguing is how they found these materials: the researchers relied on artificial intelligence to pick out useful chemicals from a list of more than 300 options. And they are not the only humans turning to A.I. for scientific inspiration.

Creating hypotheses has long been a purely human domain. Now, though, scientists are beginning to ask machine learning to produce original insights. They are designing neural networks (a type of machine-learning set up with a structure inspired by the human brain) that suggest new hypotheses based on patterns the networks find in data instead of relying on human assumptions. Many fields may soon turn to the muse of machine learning in an attempt to speed up the scientific process and reduce human biases.

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Machine learning techniques can help researchers develop novel hypotheses. Credit: Getty Images

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After spending 1,909 Martian sols on the Red Planet, NASA’s Curiosity rover was suffering from a slight malfunction.

The robot’s drill stopped working while Curiosity was on Mars’ Vera Rubin ridge at the base of Mount Sharp. The rover had collected a sample of Martian dirt, and the team behind the mission decided to go a different route.

Instead of dropping the sample into one of the cups in the sample carousel, they dropped it into a cup pre-filled with a chemical mixture. The molecules released from the cup were then trapped and analyzed, revealing organic molecules on Mars that no space agency had previously detected.

The scientists detailed their discovery in a study published Monday in the journal Nature Astronomy.

Maëva Millan, a postdoctoral fellow at NASA’s Goddard Spaceflight Center and lead author of the new study, explains that the initial motivation behind the experiment was to have a reference for future chemistry experiments conducted on Mars samples.

“This experiment was definitely successful,” Millan tells Inverse. “While we haven’t found what we were looking for, biosignatures, we showed that this technique is really promising.”

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The Curiosity rover was recently joined by NASA’s Perseverance rover which landed on Mars on February 18.NASA

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