CLOSE
Original image
© Jorge González and Pablo Lara

Silly Little Arms Evolved at Least Twice in Dinosaurs

Original image
© Jorge González and Pablo Lara

Nature is a bit like a film director or an artist. If you look carefully at its entire body of work, the same motifs emerge again and again: bioluminescence. The Golden Ratio. And, apparently, lumbering animals with ridiculously tiny arms. Scientists say Tyrannosaurus rex and the newly discovered species Gualicho shinyae developed their absurd forelimbs separately at different points in history. Their report was published today in the journal PLOS One. 

Akiko Shinya is chief fossil preparator at The Field Museum in Chicago. In 2007, she and her colleagues were rummaging around the fossil-dense rocks in Argentina’s Huincul Formation. The trip was going terribly—so terribly that some members of the party had begun joking that they’d been cursed by the local goddess Gualichu, bringer of misfortune. As the expedition drew to a close, Shinya and her colleague Peter Makovicky were losing hope. Speaking in a press statement, Shinya remembered that “ ... Pete joked, ‘It’s the last day, you’d better find something good!’” Right after he said that, Shinya says, she uncovered some very unusual fossilized bones. “I could tell right away that it was good.”  

Good, yes. Easily identifiable? No. The team had not uncovered an entire skeleton (a very rare find), but they had found enough pieces to determine that the owner of the bones was pretty darn weird.

Image credit: © Jorge González and Pablo Lara

In life, the theropod dinosaur would have been about the size of a polar bear, with strong legs, powerful jaws, and leeeeetle teeny arms. 

The newcomer is “kind of a mosaic dinosaur,” Makovicky said. “It has features that you normally see in different kinds of theropods. It’s really unusual—it’s different from the other carnivorous dinosaurs found in the same rock formation, and it doesn’t fit neatly into any category.” 

And yes, T. rex is the new dinosaur’s cousin, but only in the way that Yao Ming and Julianne Moore are yours. The two species descend from completely different branches of the theropod family tree. In fact, G. shinyae appears to occupy its own branch entirely. The researchers argue in their paper that the dinosaur’s unique jumble of traits means that it is not only its own species but also its own genus. They named their find Gualicho shinyae, after the bothersome goddess who got in their way and the determined researcher who overcame her.

Know of something you think we should cover? Email us at tips@mentalfloss.com.

Original image
iStock
arrow
technology
Google's AI Can Make Its Own AI Now
Original image
iStock

Artificial intelligence is advanced enough to do some pretty complicated things: read lips, mimic sounds, analyze photographs of food, and even design beer. Unfortunately, even people who have plenty of coding knowledge might not know how to create the kind of algorithm that can perform these tasks. Google wants to bring the ability to harness artificial intelligence to more people, though, and according to WIRED, it's doing that by teaching machine-learning software to make more machine-learning software.

The project is called AutoML, and it's designed to come up with better machine-learning software than humans can. As algorithms become more important in scientific research, healthcare, and other fields outside the direct scope of robotics and math, the number of people who could benefit from using AI has outstripped the number of people who actually know how to set up a useful machine-learning program. Though computers can do a lot, according to Google, human experts are still needed to do things like preprocess the data, set parameters, and analyze the results. These are tasks that even developers may not have experience in.

The idea behind AutoML is that people who aren't hyper-specialists in the machine-learning field will be able to use AutoML to create their own machine-learning algorithms, without having to do as much legwork. It can also limit the amount of menial labor developers have to do, since the software can do the work of training the resulting neural networks, which often involves a lot of trial and error, as WIRED writes.

Aside from giving robots the ability to turn around and make new robots—somewhere, a novelist is plotting out a dystopian sci-fi story around that idea—it could make machine learning more accessible for people who don't work at Google, too. Companies and academic researchers are already trying to deploy AI to calculate calories based on food photos, find the best way to teach kids, and identify health risks in medical patients. Making it easier to create sophisticated machine-learning programs could lead to even more uses.

[h/t WIRED]

Original image
Land Cover CCI, ESA
arrow
Afternoon Map
European Space Agency Releases First High-Res Land Cover Map of Africa
Original image
Land Cover CCI, ESA

This isn’t just any image of Africa. It represents the first of its kind: a high-resolution map of the different types of land cover that are found on the continent, released by The European Space Agency, as Travel + Leisure reports.

Land cover maps depict the different physical materials that cover the Earth, whether that material is vegetation, wetlands, concrete, or sand. They can be used to track the growth of cities, assess flooding, keep tabs on environmental issues like deforestation or desertification, and more.

The newly released land cover map of Africa shows the continent at an extremely detailed resolution. Each pixel represents just 65.6 feet (20 meters) on the ground. It’s designed to help researchers model the extent of climate change across Africa, study biodiversity and natural resources, and see how land use is changing, among other applications.

Developed as part of the Climate Change Initiative (CCI) Land Cover project, the space agency gathered a full year’s worth of data from its Sentinel-2A satellite to create the map. In total, the image is made from 90 terabytes of data—180,000 images—taken between December 2015 and December 2016.

The map is so large and detailed that the space agency created its own online viewer for it. You can dive further into the image here.

And keep watch: A better map might be close at hand. In March, the ESA launched the Sentinal-2B satellite, which it says will make a global map at a 32.8 feet-per-pixel (10 meters) resolution possible.

[h/t Travel + Leisure]

SECTIONS

arrow
LIVE SMARTER
More from mental floss studios