CLOSE
Original image
Semyon Grigoriev/Northeastern Federal University via Wired.co.uk

Scientists Find Blood in 10,000 Year Old Mammoth Remains

Original image
Semyon Grigoriev/Northeastern Federal University via Wired.co.uk

An incredible discovery by scientists from Russia's Northeastern Federal University in Yakutsk could pave the way for mammoth clones. On an expedition to an island north of Siberia, in frigid 14 degree Fahrenheit temperatures, the researchers found the carcass of a 10,000-year-old female mammoth—and it still had liquid blood.

In an interview with Wired, Semyon Grigoriev, chairman of the university's Museum of Mammoths and head of the expedition, said that the blood—which he described as "very dark"— was found "in ice cavities below the belly and when we broke these cavities with a pick, the blood came running out."

Analysis revealed that the beast, which was discovered on one of the Lyakhovsky Islands in the Novosibirsk archipelago, was between 50 and 60 years old when it died. The lower part of the body—including the stomach, lower jaw, and tongue—was embedded in pure ice, while the upper torso and two legs were preserved in the tundra's soil (these remains were gnawed on by both prehistoric and modern predators). The trunk, which scientists said was the worst preserved part of the specimen, was found separately from the body. Scientists believe the mammoth may have been running from predators and fell through the ice.

Gregoriev described fragments of muscle tissue found outside the body as having "a natural red color of fresh meat"; that extraordinary preservation is due to the remains' location in ice, as well as the fact that the carcass didn't thaw and then freeze again. Gregoriev believes the blood was liquid even in the freezing weather because "it can be assumed that the blood of mammoths had some cryo-protective properties."

The scientist told the Siberian Times (which also has more photos) that "we have taken all possible samples: samples of blood, blood vessels, glands, soft tissue, in a word—everything that we could," from the remains. "Luckily we had taken with us on our expedition a special preservative agent for blood." Still, it's not known if the blood contains the cells necessary for cloning. 

The university plans to take a team of international scientists to study the remains this summer.

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